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Speaker 1: These are the yeays of our lives. Busy and happy

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Speaker 1: are not the same thing. We too rarely question what

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Speaker 1: makes the heart seeing. We work, then we rest, but

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Speaker 1: rarely we play and often don't realize there's more than

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Speaker 1: one way. So this is a platform to hear and

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Speaker 1: explore the stories of those who found lives They adore,

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Speaker 1: the good.

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Speaker 2: Bad and ugly.

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Speaker 1: The best and worst day will bear all the facets

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Speaker 1: of seizing your yea. I'm Sarah Davidson or a spoonful

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Speaker 1: of Sarah, a lawyer turned fu entrepreneur who swapped the

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Speaker 1: suits and heels to co found matcha Maiden and matcha

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Speaker 1: Milk bar.

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Speaker 3: Cz The Ya is.

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Speaker 1: A series of conversations on finding a life you love

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Speaker 1: and exploring the self doubt, challenge, joy and fulfillment along

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Speaker 1: the way. Lovely yighborhood, Welcome to the second segment of

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Speaker 1: our second miniseries for the year, showcasing some incredible women

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Speaker 1: in science thanks to Lareels for Women in Science Fellowship program.

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Speaker 1: While our running miniseries wasn't sequential and could be listened

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Speaker 1: to in any order, I'd recommend going back to last

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Speaker 1: week's episode for the full introduction to the program. And

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Speaker 1: the landscape before digging into this one. A stat that

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Speaker 1: definitely deserves another mention, however, is that only twenty eight

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Speaker 1: percent of researchers today are women, with less than twenty

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Speaker 1: percent making up the most senior leadership positions, and only

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Speaker 1: three percent of scientific Nobel prizes have been awarded to women.

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Speaker 1: So Larel, a company brought to life by scientists one

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Speaker 1: hundred years ago, are dedicated to changing those statistics and

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Speaker 1: have awarded five outstanding women in the industries broadly referred

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Speaker 1: to as STEM science, technology, engineering, mathematics and medicine a

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Speaker 1: fellowship to help them further their groundbreaking research. One of

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Speaker 1: the biggest challenges for women in these areas is a

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Speaker 1: lack of exposure to career paths and role models. So

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Speaker 1: Larel has also created a Girls in Science program to

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Speaker 1: highlight for school students how diverse, dynamic, and deeply impactful

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Speaker 1: pathways in science can be. And since the in person

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Speaker 1: events for this Girls and Science program unfortunately weren't able

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Speaker 1: to go ahead, I am so very honored that these

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Speaker 1: CZA episodes will take their place and be distributed to

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Speaker 1: young schoolgirls who are just starting to think about their

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Speaker 1: own ways. Tya so that a new generation of young

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Speaker 1: scientists might see a future for themselves in these industries.

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Speaker 1: Our first two guests last week absolutely bowled me over.

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Speaker 1: Doctor Mardoch Shaibarney was an Iranian battery engineer working on

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Speaker 1: cleaner alternatives to lithium batteries, and doctor Kirsty Nash was

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Speaker 1: a marine biologist looking at the relationship between changing nutrient

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Speaker 1: production from fisheries and coral reefs on one hand, and

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Speaker 1: micronutrient deficiencies in humans when they consume those products on

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Speaker 1: the other. This week, our three mini interviews focus more

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Speaker 1: on medical breakthroughs in the areas of epilepsy, neuroscience, cardiovascular

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Speaker 1: health and anxiety. First up, we have doctor Pip Carola,

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Speaker 1: who is doing incredible work tracking the unique cycles of

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Speaker 1: epilepsy with wearable and mobile devices. Pip has been working

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Speaker 1: to track people's individuals seizure cycles, leading to new breakthroughs

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Speaker 1: in seizure forecasting technology, which is now being piloted in

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Speaker 1: a world first mobile and wearable app to tell people

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Speaker 1: when they have a higher or lower chance of having

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Speaker 1: a seizure. Absolutely groundbreaking. I'll let Pip tell you the

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Speaker 1: rest herself. I'm not quite sure I even understood all

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Speaker 1: of it, but I hope you find her as fascinating

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Speaker 1: as I do.

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Speaker 2: Doctor Coroli, Welcome to the show.

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Speaker 4: Thanks for having me.

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Speaker 1: I'm so excited to have you here today. It's such

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Speaker 1: a privilege. And I was just saying on one of

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Speaker 1: the other recordings that if I had heard from women

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Speaker 1: like you earlier in my career, things could have been

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Speaker 1: very different.

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Speaker 2: Right.

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Speaker 1: Well, to begin with you, at CZA, we're fascinated by

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Speaker 1: what we call path ya's which is how you get

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Speaker 1: into your industry, particularly given that there are you know,

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Speaker 1: probably more barriers for women getting into science and technology

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Speaker 1: than there are for men. But what I'd love to

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Speaker 1: start with is for you to give us a bit

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Speaker 1: of a lay person's explanation of what you're working on,

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Speaker 1: the landscape that you're currently in and it's impact for

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Speaker 1: the world. So we can get a lay of the

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Speaker 1: land and understand, you know, what your specialty is, and

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Speaker 1: be as blown away as I have been by all

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Speaker 1: the wonderful things that you're doing. So talk to us

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Speaker 1: about the work you're doing now, and then we'll kind

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Speaker 1: of work backwards from there.

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Speaker 4: Sure.

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Speaker 5: Yeah, So I am currently a senior research fellow in

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Speaker 5: biomedical engineering. My work uses digital health, so that means

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Speaker 5: mobile apps and devices like wearables, also implantable devices to

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Speaker 5: improve the lives for people with epilepsy. Epilepsy is a

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Speaker 5: massive problem worldwide. I think it's one of the most

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Speaker 5: common and certainly most serious neurological conditions. It affects people

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Speaker 5: of all ages. And what really goes on for people

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Speaker 5: is they have seizures at times that they can't predict

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Speaker 5: and that's very dangerous and very disruptive to their lives.

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Speaker 5: So it can mean they're unable to drive, or exercise,

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Speaker 5: ride a bike, all sorts of things we take for

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Speaker 5: granted can become really dangerous, even life threatening, And my

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Speaker 5: work is about ll My research is around understanding when

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Speaker 5: seizures are going to happen and to provide a forecast,

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Speaker 5: like a way the forecast to tell people when they're

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Speaker 5: at a higher or lower chance of having a seizure

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Speaker 5: and just plan their lives around that and give them

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Speaker 5: more certainty.

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Speaker 1: Oh my gosh, I can imagine that would be an

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Speaker 1: absolute game changer for people who have been at the

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Speaker 1: mercy of these unpredictable seizures in their lives. To be

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Speaker 1: able to have some kind of certainty or a heads

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Speaker 1: up before anything dangerous happens. It was just so fascinating

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Speaker 1: to read your work in tracking people's seizure cycles and

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Speaker 1: you know that the recurrence might be three weeks or

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Speaker 1: eight days or you know whatever. The kind of forecasting

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Speaker 1: is that now it's being piloted in a world first app,

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Speaker 1: like a wearable app. Does that tell people when they

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Speaker 1: have like a higher or lower chance? Are there like windows?

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Speaker 1: And I think it's through a company called Sea Is

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Speaker 1: that right?

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Speaker 4: That's right?

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Speaker 5: Yeah, So I work with an industry partner. Seeah, they're

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Speaker 5: involved in the epilepsy diagnostic space, but they also with

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Speaker 5: Syra I developed the mobile app that we're using as

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Speaker 5: a forecasting tool and a management app. And the way

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Speaker 5: it works. You hit the nail on the head when

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Speaker 5: you said it's about tracking people's cycles. And for a

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Speaker 5: long time, people thought seizures were completely random, no way

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Speaker 5: to predict them. They just sort of strike out of

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Speaker 5: the blue. But one of our key discoveries in this

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Speaker 5: area was that actually there are these really interesting rhythms

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Speaker 5: that underlie when people have go into a high risk

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Speaker 5: state or also go into a low risk state and

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Speaker 5: it's very individual for different people.

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Speaker 4: So one person might.

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Speaker 5: Have sort of every couple of weeks. For someone else

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Speaker 5: that might be ten days, for someone else that might

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Speaker 5: be a month. And it's a little bit like how

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Speaker 5: we all have circadian rhythms that most people have heard about.

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Speaker 5: It effects when we sleep and wake. It affects everything

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Speaker 5: in our body, really, but we're discovering these longer rhythms.

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Speaker 5: It also effect when people are going to have siezures,

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Speaker 5: and that's what we're tracking. When we talk about tracking

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Speaker 5: people's risk or tracking their cycles, we're tracking that individual

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Speaker 5: rhythm that is affecting their siezures and showing that to

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Speaker 5: them in the app.

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Speaker 1: Oh my gosh, that just blows my mind. I think

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Speaker 1: one of the most exciting things about this sort of industry,

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Speaker 1: and not just in medical technology but just science in general,

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Speaker 1: is that the impact of your work is so measurable.

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Speaker 1: Like when we say you know, there's a breakthrough, it's

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Speaker 1: an actual global breakthrough in something that's never happened before.

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Speaker 1: Because so often in business, you know, my advice to

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Speaker 1: people is you don't have to reinvent the wheel, like,

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Speaker 1: don't worry about creating something brand new. But in science,

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Speaker 1: you guys are literally creating brand new things that fill

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Speaker 1: a gap, that have a huge impact on people's quality

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Speaker 1: of life. So I get goosebumps just hearing these stories.

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Speaker 1: So doing it day to day must be enormously satisfying.

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Speaker 1: Can you talk to us about how you got into

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Speaker 1: this area, because I've also seen a bit of a

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Speaker 1: common theme has been that, like I mentioned, if i'd

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Speaker 1: heard from women like you, I might have had a

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Speaker 1: different perception of a career in science or understood, you know,

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Speaker 1: all the different areas you could go into rather than

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Speaker 1: just always being in a lab or always being you know,

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Speaker 1: with beakers and all that kind of thing. Like how

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Speaker 1: did you actually, you know, originally become interested in the

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Speaker 1: world of science, How did that lead into medical technology?

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Speaker 1: What did you do at UNI? Like what was your

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Speaker 1: pathway into where you are today?

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Speaker 5: Yeah, that's a good question, and it's quite hard to

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Speaker 5: sort of pinpoint because looking back, it feels like just

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Speaker 5: a series of happy accidents. But I think it mostly

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Speaker 5: comes down to the people I met along the way. So,

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Speaker 5: you know, right back in high school, I was sort

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Speaker 5: of fortunate to have a really great mass teacher, So

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Speaker 5: I really enjoyed mass because of her. So I got

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Speaker 5: into maths and I think if you asked me in

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Speaker 5: high school what my dream job was, it was to

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Speaker 5: be a writer for the New Scientist or Cosmos or something,

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Speaker 5: because I loved writing, but I was interested in science.

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Speaker 1: Oh my gosh, that's all I love New Scientists.

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Speaker 5: Yeah, so that didn't happen, but yet, Yeah, I gravitated

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Speaker 5: towards that kind of engineering science y degree at university.

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Speaker 4: And then in my final.

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Speaker 5: Year project at university just happened to meet or happened

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Speaker 5: to get involved with a project with some neurologists who

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Speaker 5: were working on a system that monitored brain waves.

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Speaker 3: Wow.

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Speaker 5: And then that led into my PhD. I think I

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Speaker 5: chose to do a PhD at the time because there

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Speaker 5: weren't that many jobs for biomedical engineers. We were sort

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Speaker 5: of it was the first time that degree had been

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Speaker 5: offered at the university.

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Speaker 4: It was all still a bit new.

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Speaker 5: It's quite a different scene now in Melbourne and in Australia,

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Speaker 5: but at the time it was a bit new.

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Speaker 4: So I got.

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Speaker 5: Into research because there wasn't jobs.

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Speaker 4: In the field I was interested in.

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Speaker 5: But it turned out I was great at research and

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Speaker 5: I loved it and I'm really really privileged now to

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Speaker 5: be able to do the academic, pure blue sky discovery research,

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Speaker 5: but have these great industry partners that actually are able

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Speaker 5: to translate things into devices and sort of enable me

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Speaker 5: to work directly with patients and help people with affletsy.

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Speaker 1: It's so interesting that you use the word happy accident,

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Speaker 1: because I think that's something that I mean, I use

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Speaker 1: that every single time I describe my own journey, but

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Speaker 1: in every guest, in every industry we've had. Really, I

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Speaker 1: think when you're younger, you have this perception that there's

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Speaker 1: a really linear pathway to career X, Y and z,

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Speaker 1: rather than you know, science is the broadest category, and

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Speaker 1: what you fall into it doesn't have to be because

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Speaker 1: you knew when you were younger you had epilepsy and

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Speaker 1: you wanted to solve your problem, or your mum had

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Speaker 1: epilepsy and you wanted to solve the gap. You know,

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Speaker 1: you can fall into things at any time in your

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Speaker 1: life through the most random pathways, but find something you

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Speaker 1: never knew that could fascinate you so much.

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Speaker 4: Yeah.

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Speaker 5: Absolutely, And the people who you meet often really sort

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Speaker 5: of nudge your pathway as well.

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Speaker 1: And I think that's why science is so exciting because

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Speaker 1: there seems to be like, I mean, neurology in itself

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Speaker 1: is like then narrowing it down into neurology of epilepsy. Like,

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Speaker 1: there's just so many ways you can move and apply

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Speaker 1: your skills, and I certainly didn't understand that. You know,

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Speaker 1: when I was first deciding what kind of career path

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Speaker 1: I would take, I just genuinely thought i'd been a

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Speaker 1: love coat with peakers, although that would also.

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Speaker 2: Be kind of fun.

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Speaker 1: I didn't realize you could be on you know, making

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Speaker 1: apps and stuff like that. That's so cool.

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Speaker 4: No, that's right.

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Speaker 5: I see, I was quite interested in medicine, and I

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Speaker 5: didn't realize there was another way to work in a

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Speaker 5: medical space and not be a doctor, which didn't really

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Speaker 5: appeal to me. But biomedical engineering is perfect, really, it's absolutely.

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Speaker 5: I think a lot of medicine now, more than people realize,

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Speaker 5: actually involves engineers and devices and signal processing and a

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Speaker 5: lot of things that are not traditional medicine.

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Speaker 4: Yeah.

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Speaker 2: Absolutely, And I love that.

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Speaker 1: You know, your love for science has been fostered so

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Speaker 1: much to the point where your daughter is named after

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Speaker 1: Ada Lovelace, who is a mathematician recognized as the first

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Speaker 1: computer programmer, and I think it's really exciting that young

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Speaker 1: women in this generation won't necessarily face the not only barriers,

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Speaker 1: but just lack of visibility of female scientists or engineers

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Speaker 1: or medical kind of researchers. They just, i think, see

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Speaker 1: themselves or see their possible futures in other women around them,

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Speaker 1: rather than having to imagine it. So what are some

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Speaker 1: of the barriers that you have faced along the way.

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Speaker 1: Has it been harder as a woman moving into science?

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Speaker 1: Are there any tips or strategies for young women aspiring

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Speaker 1: to a career in science that you would like to

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Speaker 1: pass on.

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Speaker 4: Yeah, I guess it's hard to sort of see.

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Speaker 5: The challenges when you're in them. I mean, the biggest

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Speaker 5: thing is just visibility. So I've been really fortunate that

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Speaker 5: I have had a lot of great women role models

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Speaker 5: in science ahead of our department, the head.

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Speaker 4: Of our school.

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Speaker 5: There's a lot of really trailblazing women in research and

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Speaker 5: academia around me, which is great. Back in school, I

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Speaker 5: think I was only one of two girls in our

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Speaker 5: physics class, and that's sort of something that you hear commonly.

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Speaker 5: You feel like an outsider, and then you feel less

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Speaker 5: confident to pursue that pathway.

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Speaker 4: Yeah, just visibility, it's really.

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Speaker 5: Important and I can hope, I hope I can be

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Speaker 5: that role model for other girls.

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Speaker 4: Looking to start out a pathway. I think a tip

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Speaker 4: I would give for people is it's.

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Speaker 5: Really important to have mentors. And we often seek out

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Speaker 5: women in stam as our mentors, but I think don't

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Speaker 5: underestimate the importance of having male mentors in your space

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Speaker 5: as well. I've received some of the best career advice

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Speaker 5: from male colleagues, especially when it comes for things like

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Speaker 5: applying for a promotion or things like that. So, yeah,

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Speaker 5: just diversity in your mentors is really important.

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Speaker 1: I think that's such great advice in any industry, but

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Speaker 1: particularly in areas that are traditionally you know, women are

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Speaker 1: still in the minority because you do tend to see

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Speaker 1: feminism or helping with the female movement as only turning

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Speaker 1: to other women. But they're a male feminists in the

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Speaker 1: workplace who will be incredibly necessary to generate change also,

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Speaker 1: So I think that's really valuable advice. What about the

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Speaker 1: fact that you know you've had a child in your career,

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Speaker 1: has motherhood been a difficult like taking a break from

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Speaker 1: research in a field that's very cutting edge, and like

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Speaker 1: now now, now you know, how did you find that?

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Speaker 5: As a woman, it's scary, especially because you know, I'm

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Speaker 5: thinking about having more children and it's sort of how

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Speaker 5: do you time it. It's really hard to take time

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Speaker 5: out of research and get off the conference circuit for

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Speaker 5: a while, and you get quite nervous about losing relevance

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Speaker 5: and just the networking opportunities and dropping behind. Weirdly enough,

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Speaker 5: because the birth of AID are coincided with a global pandemic,

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Speaker 5: everyone was in that lockdown boat where they're missing out

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Speaker 5: on a lot of the conferences and networking opportunities.

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Speaker 4: And I have.

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Speaker 5: Had pretty good support with getting back to work again,

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Speaker 5: something the pandemic's helped with because of all the remote

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Speaker 5: working that's going on. So I've actually been able to

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Speaker 5: take some meetings from home with my daughter and things

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Speaker 5: like that.

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Speaker 4: Be interested to see how it plays out with.

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Speaker 5: Subsequent children, but it definitely makes me nervous, and I

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Speaker 5: sort of have an eye out for grant that support

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Speaker 5: women getting back into work after starting a family, or

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Speaker 5: the specific grants where you can hire post stock and

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Speaker 5: things to help you while you're on maternity leave to

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Speaker 5: just keep things turning over and keep your publications going

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Speaker 5: and that sort of thing. So that just forward planning like.

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Speaker 1: That, and I think that's really exciting too, because I

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Speaker 1: don't imagine that's been around, you know, or maybe a

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Speaker 1: generation ago, that women having children and taking a break

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Speaker 1: in their science careers would have been able to access

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Speaker 1: grants like that. And even this fellowship with Loril, I

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Speaker 1: mean this is quite new but quite revolutionary for the industry.

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Speaker 1: For you know, a beauty company to be investing in

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Speaker 1: women in science and then investing in sharing your knowledge

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Speaker 1: with girls in science at the school age level. I

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Speaker 1: think that's so important. So what's the fellowship allowed you

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Speaker 1: to do in your research that you might not have

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Speaker 1: been able to do otherwise.

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Speaker 5: Yeah, well, the fellowship, I mean a call out for

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Speaker 5: how amazing it is to have research funding that you

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Speaker 5: can use to support childcare if that's what you need.

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Speaker 5: That's not sort of always the case, but it's really

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Speaker 5: important to support women. With the fellowship, I'll be using

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Speaker 5: directly for research costs. And so we touched on before

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Speaker 5: how we're using people's individual cycles of seizure risk in

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Speaker 5: forecasting devices. I would really like to go to the

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Speaker 5: next level and see why these cycles are happening. So

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Speaker 5: the Fellowship's going to support a whole range of different

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Speaker 5: imaging techniques. So we're taking samples from people blood samples

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Speaker 5: to liva samples and trying to understand why why are

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Speaker 5: there these unusual, mysterious long term rhythms affecting your seizures,

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Speaker 5: and that I think that will take us to the

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Speaker 5: next step in helping treat epilepsy.

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Speaker 2: Oh my gosh, that's so fascinating.

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Speaker 1: Day to day, what does your research actually look like?

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Speaker 1: Is it a lot of time with patients studying them.

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Speaker 1: Is it then a lot of collating, like how is

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Speaker 1: your day kind of split up when you're in a

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Speaker 1: breakthrough area like this?

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Speaker 5: Wells, People who are not in the field would be

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Speaker 5: surprised to know there is a lot of writing and reading.

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Speaker 5: They're constantly, constantly writing publications and trying to tell the story,

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Speaker 5: writing funding applications, So there's a lot of definitely a

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Speaker 5: lot of writing. I spend most of my time when

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Speaker 5: I'm actually doing science computer programming, so doing the science yep, Yeah,

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Speaker 5: writing code to analyze large amounts of data and look

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Speaker 5: at it in new and interesting ways and try and

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Speaker 5: find out which results are important, trying to improve our

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Speaker 5: forecasting techniques and work out how we can get that

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Speaker 5: out there.

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Speaker 4: Into the app.

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Speaker 5: And the more I advance in my career, the more

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Speaker 5: time I spend mentoring and managing other people have PhD

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Speaker 5: students and Masters students and other people are the postdocs

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Speaker 5: who I am directly responsible for, so lots of management

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Speaker 5: as you as you move forward.

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Speaker 3: But it's really great.

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Speaker 5: It's sort of discuss that are all about discovery and

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Speaker 5: trying to work out new ways to do things. So

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Speaker 5: it's really sort of feels quite creative as well.

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Speaker 1: It sounds like it's quite diverse, like there's just so

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Speaker 1: many different parts of your brain that are being drawn

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Speaker 1: on at different times of the day for different tasks,

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Speaker 1: which is for some people. I mean that's ideal.

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Speaker 5: Yeah, Yeah, it can be scary as well, because it's

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Speaker 5: very sort of you have to be quite self motivated.

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Speaker 5: That's especially true when you're doing a PhD. It's your project.

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Speaker 5: You're setting the cadence and you're setting the goals. There's

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Speaker 5: often you know, things go wrong in research and it's just.

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Speaker 4: Not working out.

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Speaker 5: You're going up down dead ends, and that can be

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Speaker 5: stressful because there's no obvious path or there's no obvious

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Speaker 5: right answer, but that also works great for some people

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Speaker 5: as well.

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Speaker 1: What was your initial interest in epilepsy, Like, did you

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Speaker 1: actually have any friends or family who suffered from the condition,

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Speaker 1: or was it literally just because it was an emerging

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Speaker 1: area where you had the skills.

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Speaker 5: I actually did have a couple of sieges when I

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Speaker 5: was a child. Oh my gosh, So I mean that

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Speaker 5: can happen. I grew out of it, luckily. It was

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Speaker 5: like a childhood applepsy, I suppose, but I don't know

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Speaker 5: if that was the reason I was. I was quite young,

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Speaker 5: but I was interested about in the process of going

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Speaker 5: into hospital and having my brain waves measured and understanding that.

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Speaker 5: I think I mentioned my engineering projects involved measuring brain

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Speaker 5: waves from people for a completely different application. Actually it

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Speaker 5: was to measure their brain waves and try and use

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Speaker 5: them to control a computer cursor, so equally.

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Speaker 3: Cool, my gosh.

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Speaker 5: But that was my in to people who understood the signals,

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Speaker 5: those brain signals, which are really really the main sort

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Speaker 5: of signal that we used to die knows epilepsy and

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Speaker 5: manage people's seizures. So it was yeah, I think I

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Speaker 5: just met some fantastic people who offered me the opportunity

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Speaker 5: to work as a research assistant and then do a PhD.

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Speaker 5: And it just grew from there.

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Speaker 2: Wow, that is so fascinating.

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Speaker 1: And again I think to any young girls who are

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Speaker 1: fascinating in science now, like the area that you might

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Speaker 1: end up working in might not have a connection to

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Speaker 1: you necessarily, or might not even be an area of

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Speaker 1: science that's currently being worked on, like the distance between

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Speaker 1: finishing school and getting into UNI, and then like it's

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Speaker 1: so fast moving you just you could end up in

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Speaker 1: any area and then be incredibly specialized in it without

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Speaker 1: kind of realizing earlier in your life.

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Speaker 5: Yeah, and I still feel that there's an opportunity to

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Speaker 5: then move into completely different fields as well. So with

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Speaker 5: these rhythms that we're starting to see in people's siezures,

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Speaker 5: we're able to track them with a whole lot of

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Speaker 5: other kinds of signals as well. Started to use wearables

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Speaker 5: to track people's heart rate and skin temperature, for instance,

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Speaker 5: and that affects their seizure risk as well, so that

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Speaker 5: these signals are relevant. But it means we're also starting

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Speaker 5: to talk to people in cardiology, for instance, to understand

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Speaker 5: that a little bit better, and then you can see

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Speaker 5: how you can just jump into a completely new field,

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Speaker 5: just again by a happy accident, you discovered something in

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Speaker 5: the data that led you in a different direction.

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Speaker 1: For kind of school age girls, in terms of getting

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Speaker 1: exposure to these areas, like, I feel like unless you

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Speaker 1: get access to someone like yourself to hear about the

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Speaker 1: way that you got into it and the different methodologies

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Speaker 1: of measuring heart responses, how would they go about finding

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Speaker 1: out more about these areas in between conventional science or

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Speaker 1: conventional engineering like as their work experience that you can do,

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Speaker 1: or how did you go about meeting new people?

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Speaker 5: That's a tough one. I mean, I think sort of

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Speaker 5: podcasts are great. There's lots of science podcasts that are

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Speaker 5: targeted to know the newest and greatest discovery. I think,

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Speaker 5: especially for girls starting out now in school now, my

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Speaker 5: advice would be to look for those kind of maker

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Speaker 5: spaces that like girls who Code, those kind of meetup

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Speaker 5: groups where they are very entry level for people learning

443
00:23:25,200 --> 00:23:29,160
Speaker 5: to code and tinker with devices. So you know, there's

444
00:23:29,160 --> 00:23:32,960
Speaker 5: sort of nothing to stop someone from taking their own

445
00:23:33,640 --> 00:23:38,440
Speaker 5: fitbit smart watch and deciding to reverse engineering and understand

446
00:23:38,520 --> 00:23:41,159
Speaker 5: their data and do some analysis on it, and just

447
00:23:41,240 --> 00:23:46,480
Speaker 5: that kind of playfulness with data and coding I think

448
00:23:46,680 --> 00:23:50,760
Speaker 5: is a really great way to see what peaques your interests.

449
00:23:50,800 --> 00:23:54,720
Speaker 5: And there's a lot of coding in research now, there's

450
00:23:54,760 --> 00:23:58,600
Speaker 5: a lot of technology, so it's a great skill to

451
00:23:58,680 --> 00:24:02,080
Speaker 5: have in your pot when you're going down that stem pathway.

452
00:24:02,160 --> 00:24:03,960
Speaker 1: Yeah, now I'm like, I want to code. I just

453
00:24:03,960 --> 00:24:06,960
Speaker 1: sort of like drop everything and go into biomedical engineering.

454
00:24:08,160 --> 00:24:12,000
Speaker 1: Are there any other really cool emerging areas of discovery

455
00:24:12,200 --> 00:24:15,680
Speaker 1: or breakthroughs in the biomedical engineering area that you think

456
00:24:15,720 --> 00:24:18,560
Speaker 1: would be worth following if you're interested, or even just

457
00:24:18,600 --> 00:24:21,800
Speaker 1: like I love listening to these podcasts and finding out

458
00:24:21,800 --> 00:24:24,200
Speaker 1: what people are doing in the world, Like what's really

459
00:24:24,200 --> 00:24:25,480
Speaker 1: getting you excited to watch?

460
00:24:25,520 --> 00:24:27,560
Speaker 5: At the moment, I feel like I've been you know,

461
00:24:27,560 --> 00:24:29,000
Speaker 5: I've got a one year old, so I feel like

462
00:24:29,040 --> 00:24:31,040
Speaker 5: I've been a little bit under a rock in the

463
00:24:32,240 --> 00:24:33,560
Speaker 5: scientific what's happening?

464
00:24:33,880 --> 00:24:37,040
Speaker 1: Well, it's the wrong time to ask you, but.

465
00:24:37,320 --> 00:24:40,920
Speaker 5: No, that the having a pandemic has sort of kicked

466
00:24:40,920 --> 00:24:46,240
Speaker 5: off a lot of really innovative like home health technology,

467
00:24:46,440 --> 00:24:50,240
Speaker 5: so things that are cheap and accessible and don't require

468
00:24:50,320 --> 00:24:54,680
Speaker 5: like specialists going into a hospital to collect that sort

469
00:24:54,720 --> 00:24:57,119
Speaker 5: of data or run that test, and that's something that

470
00:24:57,160 --> 00:25:01,080
Speaker 5: people can do at home without exposing them to the hospital.

471
00:25:01,640 --> 00:25:06,520
Speaker 5: I think that's a really cool area. I was attended

472
00:25:06,880 --> 00:25:11,960
Speaker 5: the university's Endeavor Expo. That's the sort of final year

473
00:25:12,000 --> 00:25:15,760
Speaker 5: engineering Master's students display their projects that they've been working

474
00:25:15,760 --> 00:25:18,520
Speaker 5: on all year, and I was blown away to see

475
00:25:18,560 --> 00:25:25,639
Speaker 5: how many sort of interesting diagnostic wearables are coming out now. Yeah,

476
00:25:25,680 --> 00:25:29,800
Speaker 5: really really cool things, things like for monitoring fetal health

477
00:25:29,840 --> 00:25:32,520
Speaker 5: as well during pregnancy. That was really interesting to me

478
00:25:32,560 --> 00:25:35,719
Speaker 5: because that was something I found quite stressful, having a

479
00:25:35,880 --> 00:25:37,440
Speaker 5: pregnancy in a pandemic.

480
00:25:38,400 --> 00:25:39,840
Speaker 4: So there was some cool tech there.

481
00:25:40,880 --> 00:25:45,040
Speaker 5: And yeah, also just amazing the students were able to

482
00:25:45,080 --> 00:25:48,360
Speaker 5: develop this tech without you know, during lockdown. They were

483
00:25:48,359 --> 00:25:52,440
Speaker 5: doing things like prototyping with Lego and plaano and over

484
00:25:52,480 --> 00:25:54,159
Speaker 5: the zoom. It was very impressive.

485
00:25:54,320 --> 00:25:55,600
Speaker 2: Oh that is so cool.

486
00:25:55,960 --> 00:25:58,080
Speaker 1: Like this just makes me so excited. I want to

487
00:25:58,080 --> 00:26:02,000
Speaker 1: be a scientist now. I'm hoping that other people listening

488
00:26:02,040 --> 00:26:04,560
Speaker 1: are getting as excited as I am because that stuff.

489
00:26:04,880 --> 00:26:06,200
Speaker 2: Is so interesting.

490
00:26:06,240 --> 00:26:07,440
Speaker 5: Well it's never too late.

491
00:26:07,480 --> 00:26:10,680
Speaker 1: Right, right, If we do this interview, get in five years,

492
00:26:10,720 --> 00:26:13,160
Speaker 1: maybe I'll be like have become a BIB and medical

493
00:26:13,200 --> 00:26:19,400
Speaker 1: engineer somehow. Is there a quote or kind of mantra

494
00:26:19,640 --> 00:26:22,360
Speaker 1: that you've found has helped you along the way. I'm

495
00:26:22,359 --> 00:26:24,960
Speaker 1: a big fan of motivational quotes, so is there one

496
00:26:24,960 --> 00:26:26,000
Speaker 1: that has guided you?

497
00:26:26,080 --> 00:26:30,359
Speaker 5: Okay, well, I mean this is not a motivational quote

498
00:26:30,359 --> 00:26:32,720
Speaker 5: per se, but this was the quote that I included

499
00:26:32,880 --> 00:26:35,560
Speaker 5: at the start of my thesis, for example, So it

500
00:26:35,640 --> 00:26:39,240
Speaker 5: is something that is I find very central to my research.

501
00:26:40,080 --> 00:26:44,359
Speaker 5: It's actually the first verse of a poem by Emily Dickinson.

502
00:26:45,080 --> 00:26:45,840
Speaker 4: I'll just read it.

503
00:26:47,440 --> 00:26:50,560
Speaker 5: The brain is wider than the sky. For put them

504
00:26:50,640 --> 00:26:54,119
Speaker 5: side by side, the one the other will contain with

505
00:26:54,280 --> 00:26:59,920
Speaker 5: ease and you beside. And that for someone doing real

506
00:27:00,119 --> 00:27:03,439
Speaker 5: arch in to the brain and epilepsy, it sort of

507
00:27:03,520 --> 00:27:08,040
Speaker 5: reminds me how vast and mysterious the brain still is.

508
00:27:08,520 --> 00:27:12,480
Speaker 4: And I think that was sort of good.

509
00:27:11,520 --> 00:27:15,440
Speaker 5: Reminder to have throughout my PhD and now in my research.

510
00:27:16,880 --> 00:27:18,000
Speaker 4: And I think.

511
00:27:17,800 --> 00:27:21,959
Speaker 5: Having a quote, sorry by a writer, by a poet

512
00:27:22,160 --> 00:27:25,280
Speaker 5: rather than a scientist, is also a nice reminder that

513
00:27:25,960 --> 00:27:29,040
Speaker 5: it's really important to sort of get inspired by all

514
00:27:30,200 --> 00:27:33,119
Speaker 5: sorts of fields by you know, writers and artists and

515
00:27:33,119 --> 00:27:36,879
Speaker 5: philosophers as well as well as other scientists, but just

516
00:27:36,920 --> 00:27:41,000
Speaker 5: a reminder of how creative you still are in science.

517
00:27:41,160 --> 00:27:43,720
Speaker 1: I can imagine you'd also get pretty siloed. And that's

518
00:27:43,880 --> 00:27:46,240
Speaker 1: the same in any industry of like scientists hanging out

519
00:27:46,240 --> 00:27:48,520
Speaker 1: with scientists and talking about science all the time. Like,

520
00:27:48,560 --> 00:27:52,000
Speaker 1: you do really need distance, I think, from anything that

521
00:27:52,040 --> 00:27:54,520
Speaker 1: you love doing, even if it's enjoyable and you don't

522
00:27:54,560 --> 00:27:56,679
Speaker 1: want to take a break. I mean the concept of

523
00:27:56,800 --> 00:27:59,760
Speaker 1: play in you know, the CZO podcast is such a

524
00:27:59,760 --> 00:28:04,000
Speaker 1: big thing because I don't think, like I think, our

525
00:28:04,040 --> 00:28:07,200
Speaker 1: incentives to rest or slow down or take breaks, particularly

526
00:28:07,240 --> 00:28:09,720
Speaker 1: in areas that are so fast paced, the incentive gets

527
00:28:09,880 --> 00:28:12,600
Speaker 1: smaller and smaller. But actually you make bigger discoveries when

528
00:28:12,640 --> 00:28:16,640
Speaker 1: you get a bit of distance. Speaking of are there

529
00:28:16,760 --> 00:28:21,959
Speaker 1: any books or shows or movies, we call them recommendations

530
00:28:22,520 --> 00:28:24,800
Speaker 1: that don't have to be related to science. In fact,

531
00:28:24,840 --> 00:28:27,400
Speaker 1: better if they're not. That just made you really happy recently,

532
00:28:27,720 --> 00:28:30,399
Speaker 1: that made you joyful? I kind of think if they

533
00:28:30,440 --> 00:28:33,120
Speaker 1: made you forget what time it is, then they're really

534
00:28:33,160 --> 00:28:33,879
Speaker 1: making you happy.

535
00:28:34,480 --> 00:28:37,159
Speaker 5: Okay, Well, I knew this question was coming, and I

536
00:28:37,240 --> 00:28:39,320
Speaker 5: was thinking, Oh, maybe I'll think of something that makes

537
00:28:39,360 --> 00:28:43,280
Speaker 5: me look really sophisticated. I'm just going to give you

538
00:28:43,400 --> 00:28:46,400
Speaker 5: the really daggy down to earth hats.

539
00:28:46,800 --> 00:28:48,240
Speaker 1: Yes, that's what I want.

540
00:28:49,600 --> 00:28:53,400
Speaker 5: So I recently reread the ober Newton Chronicles by Isabel

541
00:28:53,480 --> 00:28:59,520
Speaker 5: charmedy Ful and it's a huge series. It just made

542
00:28:59,600 --> 00:29:02,120
Speaker 5: me so happy. It brought me back to childhood. I

543
00:29:02,240 --> 00:29:06,320
Speaker 5: had been revisiting a lot of fantasy novels during the pandemic, just.

544
00:29:06,680 --> 00:29:08,680
Speaker 1: Like beautiful Escape business.

545
00:29:08,800 --> 00:29:09,080
Speaker 6: Yeah.

546
00:29:10,000 --> 00:29:13,400
Speaker 5: And I looked it up and I realized the last

547
00:29:13,440 --> 00:29:16,240
Speaker 5: book had finally come out just a couple of years ago.

548
00:29:16,240 --> 00:29:19,400
Speaker 5: It was sort of a series that started in the

549
00:29:19,440 --> 00:29:22,720
Speaker 5: eighties or even before, and you kept thinking, all right,

550
00:29:22,800 --> 00:29:24,720
Speaker 5: the next book to the last book, but no, there's

551
00:29:24,760 --> 00:29:27,680
Speaker 5: just one more, and they were coming out every five

552
00:29:27,800 --> 00:29:31,800
Speaker 5: or ten years, and so it was finally a complete series.

553
00:29:31,840 --> 00:29:33,560
Speaker 5: And I read it all for the first time, and

554
00:29:33,600 --> 00:29:37,280
Speaker 5: that was very exciting, made me very happy.

555
00:29:37,840 --> 00:29:40,560
Speaker 1: I love that so much. I went back and read

556
00:29:40,720 --> 00:29:43,000
Speaker 1: and watched all of the Harry Potters from the start.

557
00:29:43,680 --> 00:29:46,240
Speaker 1: Like I kind of feel like there are times in

558
00:29:46,280 --> 00:29:50,800
Speaker 1: your life when you want really sophisticated ancient wisdom and like,

559
00:29:50,880 --> 00:29:53,320
Speaker 1: let's go back and reflect on Socrates and all that

560
00:29:53,400 --> 00:29:56,280
Speaker 1: you know, philosophy on life, but most of the time,

561
00:29:56,840 --> 00:29:59,400
Speaker 1: we're all just trying to survive in between working and

562
00:30:00,080 --> 00:30:01,240
Speaker 1: you know, doing stuff.

563
00:30:01,320 --> 00:30:04,000
Speaker 2: So escapism is amazing.

564
00:30:04,240 --> 00:30:05,960
Speaker 1: Like, I think we put a lot of pressure on

565
00:30:06,000 --> 00:30:09,080
Speaker 1: ourselves to be productive even in our leisure time. But

566
00:30:09,440 --> 00:30:10,960
Speaker 1: one of the things I've been doing, which is kind

567
00:30:10,960 --> 00:30:13,400
Speaker 1: of similar to that, is I've been reading Daniel Silva.

568
00:30:13,520 --> 00:30:18,240
Speaker 1: He's got this Israeli crime fighting kind of Massad dude.

569
00:30:18,320 --> 00:30:20,080
Speaker 1: Oh he's not even in the Massad but ex special

570
00:30:20,080 --> 00:30:22,840
Speaker 1: Forces anyway. But he's also a paint restorer, so there's

571
00:30:22,840 --> 00:30:25,280
Speaker 1: a lot of art history in there, and he travels.

572
00:30:24,960 --> 00:30:25,640
Speaker 2: All over the world.

573
00:30:25,720 --> 00:30:27,760
Speaker 1: He's got all these amazing books and I've been reading

574
00:30:27,760 --> 00:30:32,320
Speaker 1: them like nothing else. But then I just ordered there's

575
00:30:32,360 --> 00:30:34,240
Speaker 1: like forty books or something, and I've been reading from

576
00:30:34,240 --> 00:30:37,760
Speaker 1: twenty onwards and I just ordered like one to twenty

577
00:30:38,160 --> 00:30:40,840
Speaker 1: or one to nineteen. I'm like, oh my god, it's

578
00:30:40,880 --> 00:30:43,560
Speaker 1: explaining all like the connections I've just missed from starting

579
00:30:43,560 --> 00:30:44,800
Speaker 1: halfway through. It's so good.

580
00:30:45,320 --> 00:30:46,840
Speaker 5: I'm busy for a while.

581
00:30:47,320 --> 00:30:52,200
Speaker 1: Ages so good. Well, thank you so much for joining.

582
00:30:52,320 --> 00:30:55,200
Speaker 1: I am so inspired and I can't wait to see

583
00:30:55,200 --> 00:30:57,320
Speaker 1: what you continue to do in this industry and the

584
00:30:57,360 --> 00:30:59,640
Speaker 1: medtech that comes thanks to your incredible research.

585
00:31:00,120 --> 00:31:01,400
Speaker 2: Thank you so much for joining.

586
00:31:01,680 --> 00:31:04,080
Speaker 1: Thanks Sarah, I said this last time, but I've had

587
00:31:04,080 --> 00:31:06,240
Speaker 1: this after every single guest in this series. I just

588
00:31:06,240 --> 00:31:08,600
Speaker 1: want to spend more time around Peep and absorb some

589
00:31:08,680 --> 00:31:09,800
Speaker 1: of her intelligence.

590
00:31:09,880 --> 00:31:11,200
Speaker 2: Spiles Mosis. Hopefully.

591
00:31:12,160 --> 00:31:14,200
Speaker 1: There was a meme going around recently about how some

592
00:31:14,280 --> 00:31:17,960
Speaker 1: jobs involved saving lives or fundamentally improving people's quality of

593
00:31:17,960 --> 00:31:20,960
Speaker 1: life through an invention, and mind involves sending an email

594
00:31:21,000 --> 00:31:23,080
Speaker 1: and sometimes I can't even manage that by myself. So

595
00:31:23,120 --> 00:31:25,960
Speaker 1: I'm getting those feels right now for these incredible women,

596
00:31:26,440 --> 00:31:28,120
Speaker 1: and I hope it's hitting home for you as much

597
00:31:28,120 --> 00:31:31,080
Speaker 1: as it is for me. How infinitely diverse the pathways

598
00:31:31,080 --> 00:31:34,480
Speaker 1: in science can be, with so many areas of specialization,

599
00:31:34,760 --> 00:31:37,040
Speaker 1: and it seems you can really fall into niche areas

600
00:31:37,080 --> 00:31:39,440
Speaker 1: you never quite expected. But it's not set in stone either.

601
00:31:40,000 --> 00:31:43,600
Speaker 1: And our next guest is equally as fascinating, also making

602
00:31:43,640 --> 00:31:46,280
Speaker 1: waves in the medical field in an area that again

603
00:31:46,840 --> 00:31:48,920
Speaker 1: I don't imagine that you set out in high school

604
00:31:48,920 --> 00:31:51,720
Speaker 1: to become this particular kind of scientist, but it's amazing

605
00:31:51,880 --> 00:31:55,040
Speaker 1: that she did. Doctor jar Wen Lee ja Ween grew

606
00:31:55,120 --> 00:31:58,480
Speaker 1: up in the historical region of China, Chian famous for

607
00:31:58,560 --> 00:32:01,080
Speaker 1: its terra Cotta warriors. She went on to study at

608
00:32:01,120 --> 00:32:04,880
Speaker 1: the University of California, Irvine, before moving to Australia, where

609
00:32:04,920 --> 00:32:07,480
Speaker 1: she now works as a lecturer and researcher, leading the

610
00:32:07,520 --> 00:32:11,720
Speaker 1: intravascular imaging program at the University of Adelaide. With over

611
00:32:11,920 --> 00:32:16,680
Speaker 1: twenty million people worldwide each year experiencing acute coronary syndrome,

612
00:32:16,720 --> 00:32:21,960
Speaker 1: including heart attack, Atherosclerotic coronary artery disease or CAD is

613
00:32:22,000 --> 00:32:24,800
Speaker 1: the most common cause of death in middle and high

614
00:32:24,840 --> 00:32:28,720
Speaker 1: income countries worldwide. Although significant progress has been made in

615
00:32:28,720 --> 00:32:33,360
Speaker 1: cardiovascular research, every hour, more than five hundred individuals experience

616
00:32:33,400 --> 00:32:36,800
Speaker 1: heart attacks without even knowing they are at risk. This

617
00:32:37,000 --> 00:32:40,960
Speaker 1: is because our understanding of atherosclerotic plark progression is still

618
00:32:40,960 --> 00:32:44,200
Speaker 1: insufficient and cardiologists do not currently have the tools to

619
00:32:44,280 --> 00:32:48,560
Speaker 1: diagnose high risk patients before their plaques become life threatening.

620
00:32:48,600 --> 00:32:53,440
Speaker 1: And you will learn all about atherosclerotic plaques shortly, Jawan

621
00:32:53,520 --> 00:32:57,280
Speaker 1: will lead an internationally significant project to create the world's

622
00:32:57,440 --> 00:33:02,840
Speaker 1: thinnest cellular resolution intra vascular imaging a catheter otherwise known

623
00:33:02,880 --> 00:33:05,920
Speaker 1: as a very very tiny camera, which will be achieved

624
00:33:06,000 --> 00:33:10,720
Speaker 1: by using novel three D printed micro optics. I don't

625
00:33:10,720 --> 00:33:15,000
Speaker 1: even understand any of that, but how fascinating what a woman.

626
00:33:15,160 --> 00:33:19,440
Speaker 1: I hope you guys enjoy Jaun or doctor Lee, welcome

627
00:33:19,480 --> 00:33:20,120
Speaker 1: to the show.

628
00:33:20,400 --> 00:33:21,640
Speaker 6: Thank you for having me here.

629
00:33:22,200 --> 00:33:24,920
Speaker 1: It is so lovely to have you. I'm so thrilled

630
00:33:25,080 --> 00:33:27,360
Speaker 1: to be able to pick your brains on the incredible

631
00:33:27,400 --> 00:33:30,280
Speaker 1: work that you're doing and why it's just so wonderful

632
00:33:30,440 --> 00:33:32,280
Speaker 1: to have you as part of for Women in Science

633
00:33:32,320 --> 00:33:35,200
Speaker 1: this year. I thought to start off because I can

634
00:33:35,240 --> 00:33:38,440
Speaker 1: barely say or pronounce what you do, let alone actually

635
00:33:38,520 --> 00:33:42,000
Speaker 1: understand what it is. Could you explain to us what

636
00:33:42,200 --> 00:33:46,800
Speaker 1: atherosclerotic coronary artery disease is and what you actually do

637
00:33:46,960 --> 00:33:49,440
Speaker 1: now before we jump into the story of how you

638
00:33:49,560 --> 00:33:50,000
Speaker 1: got there.

639
00:33:50,160 --> 00:33:55,160
Speaker 6: Yes, so I can't do is basically developing higher says

640
00:33:55,800 --> 00:33:59,200
Speaker 6: three D printed camera like like camera but not real

641
00:33:59,240 --> 00:34:02,640
Speaker 6: camera can go inside blabber so and find out what

642
00:34:02,680 --> 00:34:05,560
Speaker 6: at the highest risk of heart attack. And the reason

643
00:34:05,600 --> 00:34:08,520
Speaker 6: we're doing this is because, as you mentioned, carne archy.

644
00:34:08,680 --> 00:34:12,360
Speaker 6: This it's a huge problem worldwide. It's actually the wording

645
00:34:12,440 --> 00:34:14,480
Speaker 6: in course of death and each year there are more

646
00:34:14,560 --> 00:34:17,920
Speaker 6: than twenty million people experiencing left right, and events like

647
00:34:18,000 --> 00:34:21,919
Speaker 6: heart attack. And in Australia alone, every one hour they're

648
00:34:21,960 --> 00:34:25,040
Speaker 6: more than five hundred people experiencing heart attack without even

649
00:34:25,080 --> 00:34:27,560
Speaker 6: knowing they were at risk. So it's a huge problem

650
00:34:27,560 --> 00:34:30,360
Speaker 6: for people. And actually for my family, we have a

651
00:34:30,360 --> 00:34:33,759
Speaker 6: family history of coliney archy disease, carlivosphy disease, and so

652
00:34:33,800 --> 00:34:36,320
Speaker 6: it's really something that I hope we can do something

653
00:34:36,480 --> 00:34:38,360
Speaker 6: so that we can find out what at the highest

654
00:34:38,480 --> 00:34:41,560
Speaker 6: risk and also optimize treatment plan for those patients.

655
00:34:41,640 --> 00:34:43,880
Speaker 2: Oh my gosh, I had no idea.

656
00:34:44,000 --> 00:34:46,080
Speaker 1: It sounds like one of those conditions that is so

657
00:34:46,280 --> 00:34:49,600
Speaker 1: common in society, and like you know the statistics on

658
00:34:49,920 --> 00:34:52,160
Speaker 1: it being the most common cause of death in middle

659
00:34:52,160 --> 00:34:54,640
Speaker 1: and high income countries, but that so many of us

660
00:34:54,680 --> 00:34:55,160
Speaker 1: don't know that.

661
00:34:55,400 --> 00:34:56,280
Speaker 2: It's just crazy.

662
00:34:56,520 --> 00:34:58,560
Speaker 6: Yeah, And like you said, like and we don't know

663
00:34:58,640 --> 00:35:02,439
Speaker 6: that and some people to emergency room, some others I heard.

664
00:35:02,480 --> 00:35:05,320
Speaker 6: Actually there's also studied about this, like twenty percent of

665
00:35:05,400 --> 00:35:08,200
Speaker 6: people didn't even reach hospital and they died before that.

666
00:35:08,400 --> 00:35:10,080
Speaker 3: So it's scary, and it's.

667
00:35:10,120 --> 00:35:13,080
Speaker 6: It's something that if we could do something, it's it

668
00:35:13,160 --> 00:35:15,280
Speaker 6: could be a huge benefit for society.

669
00:35:15,800 --> 00:35:19,719
Speaker 1: Wow, my gosh, what an incredibly impactful area of work

670
00:35:19,840 --> 00:35:23,520
Speaker 1: to find yourself in. So as I understand it, this

671
00:35:23,760 --> 00:35:27,680
Speaker 1: is the world's thinnest intravascular imaging So it's like a

672
00:35:28,320 --> 00:35:31,600
Speaker 1: micro oct yeah, like a camera as you mentioned, it's

673
00:35:31,600 --> 00:35:34,000
Speaker 1: an imaging catheter that you can insert into.

674
00:35:33,880 --> 00:35:37,040
Speaker 6: The Yes, it's coming like easier way to understand. It's

675
00:35:37,040 --> 00:35:39,239
Speaker 6: like a camera, but instead of what we get with

676
00:35:39,400 --> 00:35:42,240
Speaker 6: our phone, like a bigger camera, we actually have a small,

677
00:35:42,360 --> 00:35:46,240
Speaker 6: tiny one printing onto the tip of the optical fiber

678
00:35:46,280 --> 00:35:49,880
Speaker 6: which is size of human hair, so the hair side,

679
00:35:49,920 --> 00:35:53,520
Speaker 6: but actually printing onto there. And there's a really cool technology.

680
00:35:53,600 --> 00:35:56,719
Speaker 6: Actually all or German collaborator inven this one. So we're

681
00:35:56,760 --> 00:35:59,280
Speaker 6: really fortunate to actually working with the best people around

682
00:35:59,320 --> 00:36:02,440
Speaker 6: the world developing this technology. And so my job is

683
00:36:02,480 --> 00:36:05,479
Speaker 6: basically bringing the engineering power and a medical power working

684
00:36:05,600 --> 00:36:09,480
Speaker 6: closer together and working with or clinical cadologies basically those

685
00:36:09,520 --> 00:36:11,600
Speaker 6: who are actually putting this device into patients.

686
00:36:11,640 --> 00:36:11,920
Speaker 5: Wow.

687
00:36:12,160 --> 00:36:14,680
Speaker 1: And so once you do you can get those images.

688
00:36:14,800 --> 00:36:17,399
Speaker 1: Did you say that it shows a risk for heart

689
00:36:17,440 --> 00:36:19,600
Speaker 1: attack or hard events and so you can kind of

690
00:36:19,680 --> 00:36:22,560
Speaker 1: prevent it with lifestyle choices or years.

691
00:36:22,719 --> 00:36:25,960
Speaker 6: Yeah, So at this stage it's not for everyone, like

692
00:36:26,080 --> 00:36:29,200
Speaker 6: not because it's still minimally invasive. It needs to go

693
00:36:29,360 --> 00:36:32,200
Speaker 6: inside the blood vessel, so it's only targeting those who

694
00:36:32,280 --> 00:36:35,759
Speaker 6: are already with some RISS in this disease. And then

695
00:36:35,840 --> 00:36:38,960
Speaker 6: we're looking into how we can actually put it into

696
00:36:39,360 --> 00:36:43,080
Speaker 6: and design the best treatment plan for those patients because

697
00:36:43,120 --> 00:36:45,480
Speaker 6: some of them they may need putting a stand into

698
00:36:45,560 --> 00:36:48,240
Speaker 6: the archery. Some of them may not need that, because

699
00:36:48,280 --> 00:36:51,440
Speaker 6: some of them may actually not benefiting from putting a stand.

700
00:36:52,200 --> 00:36:55,360
Speaker 6: Especially this is the case that one thing I didn't

701
00:36:55,400 --> 00:36:57,239
Speaker 6: know this before I get into this field. I was

702
00:36:57,360 --> 00:37:00,960
Speaker 6: mainly like engineering has manset, only thinking about how to

703
00:37:01,120 --> 00:37:04,120
Speaker 6: build small cameras. But then when we get into field,

704
00:37:04,360 --> 00:37:08,000
Speaker 6: I heard that actually, once we're reaching sixties, most of

705
00:37:08,160 --> 00:37:10,920
Speaker 6: us going to have this plaque atootic pluck. It's like

706
00:37:10,960 --> 00:37:14,560
Speaker 6: a fatty deposit in our artery. But not all of

707
00:37:14,640 --> 00:37:17,759
Speaker 6: them are dangerous. Only a very small amount of them

708
00:37:17,760 --> 00:37:20,480
Speaker 6: are actually dangerous. And that's why this camera is really

709
00:37:20,520 --> 00:37:23,239
Speaker 6: important because it can actually go in to find out

710
00:37:23,440 --> 00:37:25,759
Speaker 6: which is a high risk version, which is the one

711
00:37:25,840 --> 00:37:28,040
Speaker 6: not going to cause heart attack, and for those who

712
00:37:28,120 --> 00:37:31,640
Speaker 6: actually unfortunately having that, then we give them the relatively

713
00:37:31,719 --> 00:37:34,600
Speaker 6: aggressive treatment like putting a stand reopen up the artery,

714
00:37:34,800 --> 00:37:37,319
Speaker 6: but if they don't have this one, there's no need

715
00:37:37,400 --> 00:37:40,600
Speaker 6: to actually overtreating those patients. It's not only cost a

716
00:37:40,640 --> 00:37:42,680
Speaker 6: lot of money, but also for those patients they may

717
00:37:42,719 --> 00:37:46,600
Speaker 6: actually experiencing complications from the treatment side effects from the treatment.

718
00:37:46,719 --> 00:37:47,239
Speaker 2: Oh my gosh.

719
00:37:47,280 --> 00:37:51,000
Speaker 1: Well, I've never even heard of athosclerotic PLUK progression before this.

720
00:37:51,280 --> 00:37:54,000
Speaker 1: But it's so interesting that there's, like, you know, a

721
00:37:54,080 --> 00:37:57,480
Speaker 1: lot of progress in cardiovascular research generally, but this area seems,

722
00:37:57,680 --> 00:38:00,320
Speaker 1: you know, still quite misunderstood. So it's so excited that

723
00:38:00,400 --> 00:38:02,919
Speaker 1: you're working together with such an amazing team of people

724
00:38:03,080 --> 00:38:05,440
Speaker 1: to get some real results that will be life changing.

725
00:38:06,160 --> 00:38:08,840
Speaker 1: But also, I think given that on this show in particular,

726
00:38:08,920 --> 00:38:12,320
Speaker 1: we're really fascinated by pathways or path thea's as I

727
00:38:12,480 --> 00:38:15,040
Speaker 1: like to call them, you mentioned that you sort of

728
00:38:15,200 --> 00:38:19,080
Speaker 1: started off with a much more logistical engineering approach to

729
00:38:19,160 --> 00:38:21,400
Speaker 1: this kind of problem about just creating the camera, And

730
00:38:21,520 --> 00:38:23,680
Speaker 1: I think one of the coolest things to hear about

731
00:38:23,719 --> 00:38:27,120
Speaker 1: from other people is how they stumbled into different areas

732
00:38:27,160 --> 00:38:29,400
Speaker 1: that they never expected. So can you give us a

733
00:38:29,440 --> 00:38:32,560
Speaker 1: quick rundown of your whole journey into the world of science?

734
00:38:32,680 --> 00:38:34,200
Speaker 1: What did you know did you always want to be

735
00:38:34,280 --> 00:38:36,279
Speaker 1: an engineer? How did you kind of get here?

736
00:38:36,640 --> 00:38:39,919
Speaker 6: It's yeah, it's wonderful to actually hear other people's story,

737
00:38:40,000 --> 00:38:43,160
Speaker 6: and for me it's actually really stumbling along the way

738
00:38:43,239 --> 00:38:45,880
Speaker 6: and trying to figure out what's going on. So I

739
00:38:46,040 --> 00:38:49,560
Speaker 6: think I guess I should probays say I started from

740
00:38:49,960 --> 00:38:53,680
Speaker 6: Actually my dad told me engineering is really easy to

741
00:38:53,760 --> 00:38:57,279
Speaker 6: find job, as all Asian parents do. They're actually looking

742
00:38:57,320 --> 00:38:59,960
Speaker 6: into which is an opportunity for their kids to get

743
00:39:00,320 --> 00:39:02,960
Speaker 6: into like a well paid job or go to university.

744
00:39:03,239 --> 00:39:06,880
Speaker 6: But I actually feel like that is a beautiful coincident

745
00:39:06,960 --> 00:39:09,239
Speaker 6: that I get into this engineer and field and what

746
00:39:09,400 --> 00:39:12,120
Speaker 6: then ends up happening was I found Actually it gave

747
00:39:12,200 --> 00:39:15,200
Speaker 6: me the really powerful too that whole can I actually

748
00:39:15,280 --> 00:39:19,200
Speaker 6: develop the right device for condition? Instead of me directly

749
00:39:19,280 --> 00:39:21,920
Speaker 6: being working as a metal doctor, this actually allowed me

750
00:39:22,000 --> 00:39:26,719
Speaker 6: to actually solve all those amad problems on my needs.

751
00:39:26,920 --> 00:39:29,279
Speaker 1: So I think it's also really interesting to hear that

752
00:39:29,480 --> 00:39:32,319
Speaker 1: there is such a medical application of engineering, because often

753
00:39:32,360 --> 00:39:34,480
Speaker 1: you think of engineering and you think of construction or

754
00:39:34,520 --> 00:39:37,520
Speaker 1: you think of buildings. You don't think of tiny little

755
00:39:37,600 --> 00:39:41,960
Speaker 1: cameras and going into vein. So did you start out

756
00:39:42,120 --> 00:39:44,520
Speaker 1: in engineering, thinking that you would go straight into medical

757
00:39:44,600 --> 00:39:47,680
Speaker 1: engineering or how did your kind of entry into this

758
00:39:47,840 --> 00:39:50,680
Speaker 1: particular area happen. Was it during your time at university

759
00:39:50,760 --> 00:39:52,400
Speaker 1: or was it once you got into the workforce.

760
00:39:53,040 --> 00:39:56,880
Speaker 6: Yeah, So I started actually growing that passion for science

761
00:39:57,080 --> 00:39:59,799
Speaker 6: while with even a little kid, because my parents are

762
00:40:00,040 --> 00:40:02,279
Speaker 6: you want biologist, the other one is a medical doctor.

763
00:40:02,560 --> 00:40:04,920
Speaker 6: So they have been actually giving me this kind of

764
00:40:04,920 --> 00:40:08,440
Speaker 6: opportunity and grow that curiosity inside me. So I always

765
00:40:08,480 --> 00:40:10,600
Speaker 6: being a very curious person, like really interesting to know

766
00:40:10,719 --> 00:40:13,440
Speaker 6: like why this thing can work like that, how is

767
00:40:13,680 --> 00:40:17,360
Speaker 6: even being developed? And why this this can actually evolve

768
00:40:17,400 --> 00:40:20,440
Speaker 6: in this way. But the more I work with my

769
00:40:20,640 --> 00:40:23,920
Speaker 6: parents or like observe how they work, I realized, actually

770
00:40:24,160 --> 00:40:27,160
Speaker 6: I like what they're doing, like actually very useful for

771
00:40:27,239 --> 00:40:30,520
Speaker 6: the society and helping people and saving lives. But I

772
00:40:30,600 --> 00:40:32,840
Speaker 6: don't really like the day to day of what medical

773
00:40:32,920 --> 00:40:34,920
Speaker 6: doctor does. Like I'm not that type of like very

774
00:40:35,040 --> 00:40:38,920
Speaker 6: careful and follow the guideline person. I'm more like outside

775
00:40:38,920 --> 00:40:41,200
Speaker 6: the books. So if I become a doctor, I would

776
00:40:41,200 --> 00:40:43,600
Speaker 6: be really big trouble for the hospital. So I'm like,

777
00:40:43,920 --> 00:40:45,920
Speaker 6: why not I do something different? And then when my

778
00:40:46,040 --> 00:40:48,680
Speaker 6: dad was like, oh, engineering is where you can actually

779
00:40:48,800 --> 00:40:51,200
Speaker 6: find either they find a job and we'll pay a job.

780
00:40:51,480 --> 00:40:53,160
Speaker 6: Then I'm like, Okay, I'll just give it a go

781
00:40:53,520 --> 00:40:55,799
Speaker 6: and see how it works. At the beginning, I wasn't

782
00:40:55,880 --> 00:40:58,439
Speaker 6: sure whether it's actually my thing, but then I found

783
00:40:58,480 --> 00:41:02,960
Speaker 6: this niche area, which biomedical engineering. It's basically engineering, but

784
00:41:03,080 --> 00:41:06,200
Speaker 6: also you can use it for medical applications, like combining

785
00:41:06,360 --> 00:41:08,960
Speaker 6: my passions together, like well, I'm good at doing but

786
00:41:09,160 --> 00:41:12,320
Speaker 6: also something that I'm really interested in, and then that

787
00:41:12,520 --> 00:41:14,040
Speaker 6: brings all beautifully together.

788
00:41:14,920 --> 00:41:17,920
Speaker 1: Oh my gosh, you are the perfect perfect person to

789
00:41:17,960 --> 00:41:21,400
Speaker 1: come on this show, because that's everything about CZA, is

790
00:41:21,440 --> 00:41:23,480
Speaker 1: the idea of combining what you love and what you're

791
00:41:23,480 --> 00:41:25,800
Speaker 1: good at and just finding the middle ground. Because I

792
00:41:25,840 --> 00:41:28,200
Speaker 1: think when we graduate, we think there's like four jobs,

793
00:41:28,239 --> 00:41:36,120
Speaker 1: you know, doctor, teacher, pharmacist, engineer, oll what you were doing, lawyer, right, yeah, yeah,

794
00:41:36,800 --> 00:41:39,880
Speaker 1: but there's so many gray areas in between that combine

795
00:41:39,920 --> 00:41:42,239
Speaker 1: all the different ways that people's brains work. And I

796
00:41:42,440 --> 00:41:45,480
Speaker 1: love that you found that beautiful intersection in the middle.

797
00:41:45,760 --> 00:41:48,320
Speaker 1: But also it takes patience. You know, you've got to

798
00:41:48,400 --> 00:41:51,040
Speaker 1: try lots of different things, and there's often a lot

799
00:41:51,080 --> 00:41:53,719
Speaker 1: of barriers. I think along the way, particularly for women

800
00:41:53,880 --> 00:41:56,920
Speaker 1: in science or STEM in general. So how did you

801
00:41:57,080 --> 00:42:00,920
Speaker 1: find coming through as a woman into what I imagine

802
00:42:00,960 --> 00:42:04,040
Speaker 1: has been quite a heavily male dominated industry overall? Have

803
00:42:04,160 --> 00:42:07,040
Speaker 1: you faced any other challenges and how have you kind

804
00:42:07,040 --> 00:42:08,800
Speaker 1: of combatd the challenges that you faced.

805
00:42:09,120 --> 00:42:12,719
Speaker 6: Yeah, so engineering, when people thinking about it, it's really

806
00:42:12,840 --> 00:42:17,760
Speaker 6: male dominated, very masculine, and so I actually really appreciate

807
00:42:17,800 --> 00:42:21,120
Speaker 6: where I'm cont can like being very supported and then

808
00:42:21,320 --> 00:42:24,040
Speaker 6: allow me to actually be a woman sentence women engineer

809
00:42:24,120 --> 00:42:28,200
Speaker 6: and sometimes been treated just as everyone else. But when

810
00:42:28,280 --> 00:42:31,520
Speaker 6: I was doing my major, even though it's very easy

811
00:42:31,880 --> 00:42:34,160
Speaker 6: to find the job like that kind of major, but

812
00:42:34,640 --> 00:42:37,840
Speaker 6: it was not that obvious for me to actually starty

813
00:42:37,880 --> 00:42:41,000
Speaker 6: that major because my class only had two girls. So

814
00:42:41,480 --> 00:42:44,080
Speaker 6: it was really challenging for me to actually in that

815
00:42:44,239 --> 00:42:47,239
Speaker 6: class and feel I belonged there. So one of other

816
00:42:47,320 --> 00:42:51,200
Speaker 6: things I actually keep struggling when I was in college

817
00:42:51,239 --> 00:42:53,520
Speaker 6: and also even during my pH study when I was

818
00:42:53,560 --> 00:42:57,600
Speaker 6: in US, was that how to actually speak up and

819
00:42:58,120 --> 00:43:01,200
Speaker 6: actually feel that I'm still fit in So my way

820
00:43:01,320 --> 00:43:04,920
Speaker 6: back then was actually play small and play invisible. So

821
00:43:05,239 --> 00:43:09,120
Speaker 6: no makeup, no skirt, no dress, just assume I'm just

822
00:43:09,200 --> 00:43:13,560
Speaker 6: one of those bro so I basket with boys and

823
00:43:14,000 --> 00:43:17,520
Speaker 6: most of them look about sports that I've face seeing

824
00:43:18,120 --> 00:43:21,480
Speaker 6: and it works quite well in back then because I

825
00:43:21,560 --> 00:43:24,839
Speaker 6: actually got opportunities to actually really closely working with them

826
00:43:24,880 --> 00:43:27,279
Speaker 6: and learn how to actually work with guys. And then

827
00:43:28,480 --> 00:43:31,759
Speaker 6: now I actually start thinking it's I should be doing

828
00:43:31,840 --> 00:43:34,840
Speaker 6: it very differently, and I actually I should be actually

829
00:43:34,960 --> 00:43:37,839
Speaker 6: helping other girls like my own students, to let them

830
00:43:37,960 --> 00:43:41,120
Speaker 6: realize they can be themselves and they can actually still

831
00:43:41,200 --> 00:43:43,880
Speaker 6: have long hairs, they still have makeups, they're still actually

832
00:43:43,960 --> 00:43:47,440
Speaker 6: looking good. Well, they're actually also doing what they're passionable.

833
00:43:47,600 --> 00:43:50,399
Speaker 6: And I think this is where currently there's a low

834
00:43:50,520 --> 00:43:53,560
Speaker 6: change going on, like the Loyal Fellowship, this is why

835
00:43:53,640 --> 00:43:57,200
Speaker 6: actually supporting us to actually like just be ourselves. Well,

836
00:43:57,280 --> 00:43:59,840
Speaker 6: we've also been very passionate about what we're doing. And

837
00:44:00,040 --> 00:44:03,439
Speaker 6: there are also plenty of programs from like university level,

838
00:44:03,600 --> 00:44:07,719
Speaker 6: state level, national level to supporting woman centers, woman engineering,

839
00:44:08,120 --> 00:44:10,960
Speaker 6: and to actually like I think it's more like career

840
00:44:11,040 --> 00:44:15,080
Speaker 6: development and also mentorship that help us to reach into

841
00:44:15,080 --> 00:44:17,680
Speaker 6: the next level and be more comfortable to play big

842
00:44:18,280 --> 00:44:19,399
Speaker 6: at Jim Big as well.

843
00:44:19,520 --> 00:44:22,960
Speaker 1: Yeah, I love that contrast between the choice to play

844
00:44:22,960 --> 00:44:25,800
Speaker 1: in visible or play small versus coming out and actually

845
00:44:25,840 --> 00:44:28,400
Speaker 1: embracing who you are and playing much bigger on the field.

846
00:44:28,440 --> 00:44:31,040
Speaker 1: Because I think there are particularly in stand but in

847
00:44:31,160 --> 00:44:34,120
Speaker 1: lots of industries that have been traditionally more male dominated.

848
00:44:34,160 --> 00:44:37,160
Speaker 1: I'm sure there are women listening who totally identify with

849
00:44:37,800 --> 00:44:40,320
Speaker 1: just trying to be invisible and blend into the crowd

850
00:44:40,400 --> 00:44:42,279
Speaker 1: and be one of the boys. And I think it's

851
00:44:42,320 --> 00:44:45,040
Speaker 1: so exciting that in this day and age, women aren't

852
00:44:45,160 --> 00:44:47,880
Speaker 1: necessarily expected to do that anymore in order to succeed.

853
00:44:48,480 --> 00:44:51,799
Speaker 1: And there are so many wonderful programs and fellowships and scholarships,

854
00:44:51,880 --> 00:44:55,280
Speaker 1: you know, that allow women to be celebrated in these fields.

855
00:44:55,280 --> 00:44:57,040
Speaker 1: And you're such a great role model for that. So,

856
00:44:57,239 --> 00:45:01,560
Speaker 1: if any young women who are looking into engineering, biomedical engineering,

857
00:45:01,680 --> 00:45:03,839
Speaker 1: or just science in general, what would you give them

858
00:45:03,840 --> 00:45:04,760
Speaker 1: as a piece of advice?

859
00:45:04,920 --> 00:45:07,640
Speaker 6: Now, what I would suggest is the top thing is

860
00:45:07,960 --> 00:45:11,640
Speaker 6: identify some mentors and go and ask them whether they

861
00:45:11,719 --> 00:45:13,680
Speaker 6: want they can be your mentor, or even just ask

862
00:45:13,719 --> 00:45:17,120
Speaker 6: them whether I can have a coffee of launch together,

863
00:45:17,480 --> 00:45:19,719
Speaker 6: and then they will be really happy to help you,

864
00:45:19,960 --> 00:45:22,160
Speaker 6: and then you will get a very beautiful, nice, supporting

865
00:45:22,320 --> 00:45:26,160
Speaker 6: environment and also support group. What I found really beautiful,

866
00:45:26,239 --> 00:45:29,360
Speaker 6: like helpful for my career was actually they're plenty mentors

867
00:45:29,560 --> 00:45:31,880
Speaker 6: help me along the way. Some of them helping me

868
00:45:32,000 --> 00:45:34,839
Speaker 6: with more like the technical part, some of them more

869
00:45:35,040 --> 00:45:38,680
Speaker 6: about like manset shifting, how I actually embrace what I'm doing.

870
00:45:38,960 --> 00:45:41,560
Speaker 6: For example, like my mentor who gave me this book

871
00:45:41,719 --> 00:45:43,120
Speaker 6: and the leading book.

872
00:45:43,640 --> 00:45:44,480
Speaker 5: She is a.

873
00:45:44,520 --> 00:45:48,160
Speaker 6: Professor and she's from Germany and not working in Australia,

874
00:45:48,360 --> 00:45:50,320
Speaker 6: and a couple of years ago she gave me this

875
00:45:50,480 --> 00:45:53,040
Speaker 6: book and she will tell me that her journey and

876
00:45:53,160 --> 00:45:56,600
Speaker 6: also not we become really close more than like mentor

877
00:45:56,680 --> 00:45:59,759
Speaker 6: men team, but more like friends and re sharing all

878
00:45:59,800 --> 00:46:03,480
Speaker 6: the stories, all the troubles, and that really I think

879
00:46:03,560 --> 00:46:06,600
Speaker 6: it's like transformed my career. She gave me this book

880
00:46:06,640 --> 00:46:10,640
Speaker 6: when I was expecting my daughter, and then back then

881
00:46:10,960 --> 00:46:13,640
Speaker 6: I started reading some chapters of this book, for example

882
00:46:13,760 --> 00:46:16,680
Speaker 6: like don't leave until you leave, And then when I

883
00:46:16,880 --> 00:46:19,640
Speaker 6: was taking my maternity I was reading like the chapter

884
00:46:19,800 --> 00:46:21,719
Speaker 6: of ull like how do you have it? Or making

885
00:46:21,800 --> 00:46:24,840
Speaker 6: my partner be a real partner. But when I was

886
00:46:24,960 --> 00:46:29,000
Speaker 6: reading this fact, when I was in I think probably

887
00:46:29,280 --> 00:46:32,800
Speaker 6: undergrads or graduate school, I was more focusing on like

888
00:46:32,880 --> 00:46:35,719
Speaker 6: sitting at the table and how I actually can like

889
00:46:35,800 --> 00:46:39,200
Speaker 6: speak up. So I think really finding good mentors and

890
00:46:39,320 --> 00:46:41,719
Speaker 6: also finding this kind of like good books that we

891
00:46:41,840 --> 00:46:44,759
Speaker 6: can read really helpful and helping us to actually feel

892
00:46:44,800 --> 00:46:47,600
Speaker 6: like we're not alone and we have plenty of supports.

893
00:46:47,680 --> 00:46:50,520
Speaker 6: And I think most girls really williant to help each other.

894
00:46:51,120 --> 00:46:53,960
Speaker 6: Women helping and empowering each other. That's I think that

895
00:46:54,440 --> 00:46:56,560
Speaker 6: I got a lot of support through this journey and

896
00:46:56,640 --> 00:46:57,600
Speaker 6: I'm really grateful of.

897
00:46:57,680 --> 00:47:01,680
Speaker 1: Those absolutely, And I'm so glad and excited that your

898
00:47:01,719 --> 00:47:03,879
Speaker 1: recommendation for this week, because I was going to ask

899
00:47:03,880 --> 00:47:07,239
Speaker 1: you that question is Sheryl Sandberg's book, because Leaning is

900
00:47:07,320 --> 00:47:09,719
Speaker 1: something that I've turned to over and over and over,

901
00:47:10,200 --> 00:47:11,960
Speaker 1: and I found that at different times in my life,

902
00:47:12,000 --> 00:47:15,000
Speaker 1: different chapters are more impactful or I need them more.

903
00:47:15,560 --> 00:47:17,920
Speaker 1: And I think it was from that book I've read

904
00:47:17,960 --> 00:47:20,560
Speaker 1: about when I was a lawyer and facing that kind

905
00:47:20,560 --> 00:47:22,560
Speaker 1: of need to come to the table and find my

906
00:47:22,719 --> 00:47:25,439
Speaker 1: voice and not miss out all the time just because

907
00:47:25,440 --> 00:47:27,520
Speaker 1: I did I wanted to be likable or because I

908
00:47:27,600 --> 00:47:29,640
Speaker 1: wanted to, I don't know, fit in and be invisible.

909
00:47:30,040 --> 00:47:33,320
Speaker 1: The study from Hewlett Packard about women and men applying

910
00:47:33,400 --> 00:47:36,360
Speaker 1: for promotions or putting themselves forward for things really stuck

911
00:47:36,400 --> 00:47:38,839
Speaker 1: with me. And how like men apply for promotions when

912
00:47:38,840 --> 00:47:42,040
Speaker 1: they've got sixty percent of the criteria because they can

913
00:47:42,239 --> 00:47:45,920
Speaker 1: learn forty percent on the go, that's logical, whereas we

914
00:47:46,040 --> 00:47:48,040
Speaker 1: will wait until one hundred or one hundred and twenty

915
00:47:48,040 --> 00:47:50,720
Speaker 1: percent and we've already put ourselves at a disadvantage.

916
00:47:50,760 --> 00:47:52,719
Speaker 2: And that changed my life exactly.

917
00:47:52,880 --> 00:47:55,960
Speaker 6: Yeah. Yeah, and that's really powerful to actually reading all

918
00:47:56,080 --> 00:47:59,640
Speaker 6: those and from someone. Sometimes we can already RACI getting mentors,

919
00:47:59,640 --> 00:48:01,880
Speaker 6: but those books really helpful. And the scad of like

920
00:48:02,120 --> 00:48:05,200
Speaker 6: you're talking to someone and having a really deep conversation

921
00:48:05,320 --> 00:48:08,360
Speaker 6: and as you said, at different stage you found something different,

922
00:48:08,440 --> 00:48:10,200
Speaker 6: like laying different things from the book.

923
00:48:10,320 --> 00:48:11,000
Speaker 2: Yeah, for sure.

924
00:48:11,360 --> 00:48:15,520
Speaker 1: Is there like a particular quote or phrase or kind

925
00:48:15,560 --> 00:48:18,640
Speaker 1: of motivational mantra that's really helped you and guided you

926
00:48:18,880 --> 00:48:19,520
Speaker 1: to get this far?

927
00:48:19,760 --> 00:48:22,280
Speaker 6: I think it also changed verds, like a different stage,

928
00:48:22,320 --> 00:48:25,719
Speaker 6: different time. But what I at this stage when really,

929
00:48:26,160 --> 00:48:29,280
Speaker 6: like I think closely, it resonates with me with actually

930
00:48:29,719 --> 00:48:33,200
Speaker 6: the one that I have no special talents, I only

931
00:48:33,719 --> 00:48:37,480
Speaker 6: passionally cures. You may have heard about this before. It's

932
00:48:37,520 --> 00:48:40,480
Speaker 6: actually by Albert Einstand sometimes it's really funny that he

933
00:48:40,600 --> 00:48:43,960
Speaker 6: thinks he has no special talents. He's really super super smart,

934
00:48:44,160 --> 00:48:46,839
Speaker 6: and I think that's a huge talents compared to many

935
00:48:46,880 --> 00:48:49,640
Speaker 6: our of us. But I think I don't know whether

936
00:48:49,680 --> 00:48:52,520
Speaker 6: I have special talents. But whenever I think about his cold,

937
00:48:52,600 --> 00:48:54,640
Speaker 6: I always told myself, I don't know whether I have

938
00:48:54,760 --> 00:48:57,480
Speaker 6: special talents or some super power. But I know for

939
00:48:57,600 --> 00:49:00,439
Speaker 6: sure is I can be passionately curious. And if I'm

940
00:49:00,640 --> 00:49:03,280
Speaker 6: like that, and if I find the thing, I'm passionate curious,

941
00:49:03,520 --> 00:49:06,920
Speaker 6: no matter how hard it is, no matter how difficult.

942
00:49:06,960 --> 00:49:09,759
Speaker 6: Sometimes we just like we're facing all the hurdles and

943
00:49:09,960 --> 00:49:12,560
Speaker 6: also we have to work really hard and we have

944
00:49:12,640 --> 00:49:14,880
Speaker 6: to juggle all those things. But we feel that we

945
00:49:15,120 --> 00:49:18,400
Speaker 6: actually really passionate and we enjoying what we do, and

946
00:49:18,480 --> 00:49:21,280
Speaker 6: we keep continue waking up feel like energetic again.

947
00:49:21,480 --> 00:49:24,400
Speaker 1: I love that idea if curiosity wins against everything and

948
00:49:24,560 --> 00:49:28,640
Speaker 1: just being endlessly asking questions, because curiosity is what will

949
00:49:28,719 --> 00:49:30,359
Speaker 1: lead you to change the world. I mean, look at

950
00:49:30,400 --> 00:49:33,120
Speaker 1: what you're doing now, the problems you're solving with Like

951
00:49:33,880 --> 00:49:37,799
Speaker 1: intravascular cameras like that can literally put print three day

952
00:49:37,840 --> 00:49:40,800
Speaker 1: print onto the dip of vinada, like that blows my mind.

953
00:49:41,400 --> 00:49:44,239
Speaker 6: Thank you. Yeah, it's really like where I found like

954
00:49:44,480 --> 00:49:46,960
Speaker 6: because I'm great curious, so I don't even need to

955
00:49:47,000 --> 00:49:49,360
Speaker 6: limit it to my own error. And that's why I

956
00:49:49,440 --> 00:49:51,880
Speaker 6: can also go and talk to people who have this

957
00:49:52,040 --> 00:49:55,080
Speaker 6: cool technology. I can talk to clinician and find out

958
00:49:55,239 --> 00:49:58,880
Speaker 6: what exactity is their need because we can invent anything,

959
00:49:59,120 --> 00:50:01,479
Speaker 6: but we actual you want that I think can solve

960
00:50:01,560 --> 00:50:04,680
Speaker 6: their clinical need that works with their clinical workflow.

961
00:50:05,840 --> 00:50:07,920
Speaker 1: And just finally, I'd love to ask you mentioned that

962
00:50:08,000 --> 00:50:11,759
Speaker 1: your mentor helped you with the migrant experience, which is

963
00:50:11,800 --> 00:50:14,720
Speaker 1: another added barrier in a whole new country and culture

964
00:50:14,760 --> 00:50:17,640
Speaker 1: with language barriers in a scientific you know, with all

965
00:50:17,680 --> 00:50:22,200
Speaker 1: this terminology and technical words, having the added barrier for

966
00:50:22,360 --> 00:50:24,440
Speaker 1: you know, women are already facing a lot of challenges

967
00:50:24,640 --> 00:50:26,680
Speaker 1: moving into science. But do you have any advice if

968
00:50:26,719 --> 00:50:29,320
Speaker 1: there are also people who have moved from another country

969
00:50:29,360 --> 00:50:31,720
Speaker 1: to pursue their career, Like, is there anything that helped

970
00:50:31,760 --> 00:50:34,560
Speaker 1: you kind of find your way in a new culture

971
00:50:34,840 --> 00:50:37,160
Speaker 1: and a new country, And actually, how long has it

972
00:50:37,239 --> 00:50:38,800
Speaker 1: been since you came to Australia.

973
00:50:39,120 --> 00:50:42,399
Speaker 6: I have been here six years, so it's a very

974
00:50:42,560 --> 00:50:45,440
Speaker 6: long journey for us to actually feel that we actually

975
00:50:45,520 --> 00:50:49,719
Speaker 6: can fit in and not like actually able to like

976
00:50:50,000 --> 00:50:52,400
Speaker 6: not play small anymore and start I feel like, actually

977
00:50:52,440 --> 00:50:54,800
Speaker 6: we can speak up. It took a long time for

978
00:50:54,960 --> 00:50:57,520
Speaker 6: us to actually do that, and recently I'm still doing

979
00:50:57,560 --> 00:51:00,799
Speaker 6: this kind of transformation for my own life, like how

980
00:51:00,920 --> 00:51:05,440
Speaker 6: I actually can like really embrace that I'm a migrant.

981
00:51:05,520 --> 00:51:08,879
Speaker 6: I have strong accent, but it doesn't stop me from

982
00:51:09,000 --> 00:51:11,720
Speaker 6: actually speaking up. I can still sit at the table,

983
00:51:11,800 --> 00:51:13,960
Speaker 6: I can actually share my story. And one of the

984
00:51:14,040 --> 00:51:16,040
Speaker 6: thing that recent date was actually on Twitter to share

985
00:51:16,160 --> 00:51:18,440
Speaker 6: my story about the struggle I had been through in

986
00:51:18,520 --> 00:51:20,879
Speaker 6: the past one year. A lot of people only hearing

987
00:51:21,040 --> 00:51:24,160
Speaker 6: like all the beautiful and the exciting thing we've been doing,

988
00:51:24,480 --> 00:51:27,080
Speaker 6: how scentiences have been solving this problem, that problem, But

989
00:51:27,200 --> 00:51:30,640
Speaker 6: on the other hand, we actually steal. Like many other migrants,

990
00:51:30,800 --> 00:51:33,320
Speaker 6: we're facing a lot of challenges, especially with this current

991
00:51:33,400 --> 00:51:37,479
Speaker 6: really challenging time because all parents are actually in still

992
00:51:37,520 --> 00:51:41,399
Speaker 6: in China, and all actually we're all relative friends there

993
00:51:41,480 --> 00:51:45,560
Speaker 6: there and basing this kind of like struggles and like

994
00:51:45,800 --> 00:51:48,080
Speaker 6: parents being sick, and also we can have no way

995
00:51:48,120 --> 00:51:51,759
Speaker 6: to go back all that. It's really only who have

996
00:51:51,960 --> 00:51:55,160
Speaker 6: been through that can fully understand that. But What's nice

997
00:51:55,280 --> 00:51:57,480
Speaker 6: I actually through this journey was I found that one

998
00:51:57,480 --> 00:52:00,080
Speaker 6: thing really important was actually let people know that if

999
00:52:00,120 --> 00:52:03,120
Speaker 6: you're struggling, if you're doing something that it's just hard

1000
00:52:03,200 --> 00:52:06,120
Speaker 6: for yourself to digest, other people will be williant to

1001
00:52:06,200 --> 00:52:08,960
Speaker 6: actually help and they will help you find solutions. And

1002
00:52:09,400 --> 00:52:12,480
Speaker 6: this whole process make me realize actually, like there were

1003
00:52:12,560 --> 00:52:15,640
Speaker 6: days that we just don't really know whether we can

1004
00:52:15,800 --> 00:52:18,279
Speaker 6: actually even get exemption to leave the country, whether we

1005
00:52:18,360 --> 00:52:20,719
Speaker 6: can go and see my parents, and what can we

1006
00:52:20,800 --> 00:52:23,280
Speaker 6: do with a two year old, and like all those childcare,

1007
00:52:23,360 --> 00:52:27,000
Speaker 6: all those struggles, and then later on I was like, Okay,

1008
00:52:27,600 --> 00:52:30,319
Speaker 6: I think, even though I don't think I've a role

1009
00:52:30,400 --> 00:52:33,359
Speaker 6: model yet, but if I think about this whole person,

1010
00:52:33,560 --> 00:52:36,160
Speaker 6: what I want to do for my menty, what I

1011
00:52:36,239 --> 00:52:40,080
Speaker 6: want my mente to actually get all from actually working

1012
00:52:40,160 --> 00:52:43,160
Speaker 6: with me and learning from this process was if they

1013
00:52:43,360 --> 00:52:47,160
Speaker 6: actually can see me go and speak up, go and

1014
00:52:47,440 --> 00:52:50,120
Speaker 6: actually reach out for help, then they will be feel

1015
00:52:50,200 --> 00:52:52,439
Speaker 6: more empowered to do this, because if I'm not even

1016
00:52:52,520 --> 00:52:54,960
Speaker 6: doing this, then for them it will be even harder.

1017
00:52:55,239 --> 00:52:58,399
Speaker 6: So I decide, okay, I will just tell my boss,

1018
00:52:58,640 --> 00:53:00,680
Speaker 6: I'll just go and talk to you like hr in

1019
00:53:01,280 --> 00:53:04,759
Speaker 6: our institute and figuring out whether there's a solution, and

1020
00:53:05,280 --> 00:53:07,279
Speaker 6: the moment I go and talk to them, I was

1021
00:53:07,400 --> 00:53:12,240
Speaker 6: so surprised because actually the executive day of our entire faculty,

1022
00:53:12,520 --> 00:53:17,200
Speaker 6: who's really really like a senior position, actually told me, Oh,

1023
00:53:17,280 --> 00:53:19,520
Speaker 6: it's totally not a problem at all if you need

1024
00:53:19,600 --> 00:53:24,080
Speaker 6: to take exceenitive families first and just like really reassure,

1025
00:53:24,360 --> 00:53:27,680
Speaker 6: like make me feel like it's a huge really for us,

1026
00:53:27,920 --> 00:53:30,360
Speaker 6: and we realize even though there's a lot responsibility I

1027
00:53:30,480 --> 00:53:33,359
Speaker 6: have on my shoulder for the research, for all those

1028
00:53:33,600 --> 00:53:38,440
Speaker 6: like supervising students, teaching all those but they're supportive to

1029
00:53:38,520 --> 00:53:40,960
Speaker 6: actually let me to do this remotely. So actually the

1030
00:53:41,040 --> 00:53:44,120
Speaker 6: reason we're moving this interview forward was because I need

1031
00:53:44,200 --> 00:53:47,160
Speaker 6: to go back to see my mom and support her.

1032
00:53:47,239 --> 00:53:49,640
Speaker 6: I don't know what's going to happen in the next

1033
00:53:49,719 --> 00:53:52,800
Speaker 6: few months, and hopefully she will get recovered from this,

1034
00:53:52,960 --> 00:53:55,440
Speaker 6: but whichever way it is, way like we want to

1035
00:53:55,480 --> 00:53:58,120
Speaker 6: be there to support them. I think this probably happens

1036
00:53:58,120 --> 00:54:01,000
Speaker 6: to many immigrants in this stage for life, like we

1037
00:54:01,239 --> 00:54:03,840
Speaker 6: just with the pandemic, ser so much uncertain TV is

1038
00:54:03,880 --> 00:54:06,760
Speaker 6: our life, but we just have to carry on. And also,

1039
00:54:07,280 --> 00:54:10,759
Speaker 6: funny supposed and asking for help and richal because most

1040
00:54:10,920 --> 00:54:13,520
Speaker 6: often people want to help through this process.

1041
00:54:13,760 --> 00:54:15,000
Speaker 2: That's such good advice.

1042
00:54:15,160 --> 00:54:18,080
Speaker 1: I think sometimes in a moment of vulnerability, you actually

1043
00:54:18,160 --> 00:54:21,360
Speaker 1: find more support than you could ever imagine, and you

1044
00:54:21,480 --> 00:54:23,239
Speaker 1: bring a lot of other people along with you on

1045
00:54:23,320 --> 00:54:25,440
Speaker 1: the way because they don't feel alone in their struggles.

1046
00:54:25,480 --> 00:54:27,040
Speaker 1: So it's funny that you don't think you're a role

1047
00:54:27,120 --> 00:54:29,600
Speaker 1: model yet, because I think you would be an amazing

1048
00:54:29,719 --> 00:54:32,000
Speaker 1: role model for so many people and such a worthy

1049
00:54:32,160 --> 00:54:36,160
Speaker 1: part of this fellowship. So Tai Guantiella, you've been really,

1050
00:54:36,280 --> 00:54:39,879
Speaker 1: really amazing and I can't wait to see what else

1051
00:54:39,960 --> 00:54:42,239
Speaker 1: you do and wish you all the best as you

1052
00:54:42,400 --> 00:54:44,600
Speaker 1: head back to China and hope your family are all

1053
00:54:44,680 --> 00:54:45,320
Speaker 1: safe and healthy.

1054
00:54:45,520 --> 00:54:48,360
Speaker 6: Thank you so much, Sarah, thank you much appreciate.

1055
00:54:49,480 --> 00:54:49,600
Speaker 5: Ja.

1056
00:54:49,719 --> 00:54:52,560
Speaker 6: Yeah, thank you, oh, because I hope like you have

1057
00:54:52,640 --> 00:54:55,040
Speaker 6: been laying language like in your school as well.

1058
00:54:55,200 --> 00:54:55,719
Speaker 5: That's nice.

1059
00:54:55,760 --> 00:54:57,120
Speaker 6: So, like Mandarine.

1060
00:54:59,080 --> 00:55:08,600
Speaker 1: Well said, ah, I do, it's mutiful, it's perfect.

1061
00:55:08,840 --> 00:55:12,960
Speaker 6: Yeah, actually pronounce my name Quobol.

1062
00:55:15,360 --> 00:55:18,719
Speaker 1: I don't think so. But your English is so articulate,

1063
00:55:18,960 --> 00:55:21,680
Speaker 1: so eloquent, and you you think that you have a

1064
00:55:21,719 --> 00:55:25,440
Speaker 1: really strong accent, but I could understand even atherosclerotic.

1065
00:55:26,160 --> 00:55:29,520
Speaker 6: It's a really hard world. Like, oh, yeah, I'm so glad.

1066
00:55:29,600 --> 00:55:31,640
Speaker 6: Actually we have to practice that a lot. I work,

1067
00:55:31,719 --> 00:55:34,680
Speaker 6: but yeah, it's really long and yeah, hard to pronounce

1068
00:55:34,719 --> 00:55:40,040
Speaker 6: them yeah, or make your editing power work hard because

1069
00:55:40,080 --> 00:55:42,600
Speaker 6: some of them are like thinking, well I'm speaking, and

1070
00:55:42,680 --> 00:55:44,920
Speaker 6: then just like h and then yeah.

1071
00:55:45,880 --> 00:55:48,880
Speaker 1: What an absolute sweetheart. Jawin was such a delight. We

1072
00:55:49,000 --> 00:55:51,480
Speaker 1: kept chatting for half an hour after finishing recording. I

1073
00:55:51,520 --> 00:55:54,319
Speaker 1: had so much fun with her. And last, but not least,

1074
00:55:54,360 --> 00:55:57,440
Speaker 1: we have another wonderful guest, doctor Olivia Harrison, working on

1075
00:55:57,520 --> 00:56:00,239
Speaker 1: an area close to my heart. Not as literally close

1076
00:56:00,280 --> 00:56:03,800
Speaker 1: to my heart as Jown and her actual intravascular imaging,

1077
00:56:04,280 --> 00:56:09,160
Speaker 1: but close to my heart metaphorically in terms of anxiety. Olivia,

1078
00:56:09,360 --> 00:56:11,840
Speaker 1: who knows what it is like to experience high levels

1079
00:56:11,880 --> 00:56:14,160
Speaker 1: of anxiety, wants to help address some of the gaps

1080
00:56:14,200 --> 00:56:18,080
Speaker 1: in the way individuals identify and perceive their anxiety to

1081
00:56:18,200 --> 00:56:21,600
Speaker 1: better develop treatment and techniques to help manage the symptoms.

1082
00:56:22,160 --> 00:56:25,360
Speaker 1: Olivia has previously done work on the relationship between anxiety

1083
00:56:25,440 --> 00:56:29,160
Speaker 1: and changes in our perception of breathing, and her upcoming

1084
00:56:29,239 --> 00:56:34,000
Speaker 1: studies will investigate treatments such as exercise, and pharmacotherapy and

1085
00:56:34,160 --> 00:56:37,960
Speaker 1: how they relate to improvements in anxiety. I learned so

1086
00:56:38,120 --> 00:56:40,400
Speaker 1: much from this one, and I hope you guys do too.

1087
00:56:41,120 --> 00:56:42,759
Speaker 2: Olivia, Welcome to the show.

1088
00:56:43,040 --> 00:56:44,440
Speaker 4: Thanks very match, Thanks having me.

1089
00:56:44,800 --> 00:56:46,600
Speaker 1: I'm so excited to have you here. And you're our

1090
00:56:46,680 --> 00:56:51,360
Speaker 1: first international recording, which is wonderful. Not too international, not

1091
00:56:51,480 --> 00:56:54,520
Speaker 1: too far away still, I mean we've only just been

1092
00:56:54,600 --> 00:56:57,880
Speaker 1: let out of our five kilometer radius, so I feel like, oh,

1093
00:56:57,960 --> 00:57:03,520
Speaker 1: my gosh, she's an intronet traveler, well on my home office,

1094
00:57:03,640 --> 00:57:04,360
Speaker 1: but sort of.

1095
00:57:06,880 --> 00:57:08,400
Speaker 2: Well, thank you so much for joining us.

1096
00:57:08,480 --> 00:57:13,200
Speaker 1: I'm so so excited about just I think, increasing the

1097
00:57:13,320 --> 00:57:17,480
Speaker 1: visibility for careers in science and showing to any aspiring

1098
00:57:17,520 --> 00:57:19,880
Speaker 1: scientists out there, whether they're starting their career for the

1099
00:57:19,920 --> 00:57:22,760
Speaker 1: first time or they're thinking of switching careers, how many

1100
00:57:22,800 --> 00:57:26,560
Speaker 1: different options and pathways in industries and areas of speciality

1101
00:57:26,600 --> 00:57:29,560
Speaker 1: there are. So can you start by giving us a

1102
00:57:29,600 --> 00:57:32,280
Speaker 1: bit of a lay person's explanation of what you're working

1103
00:57:32,400 --> 00:57:34,160
Speaker 1: on now before we sort of go back to the

1104
00:57:34,200 --> 00:57:36,760
Speaker 1: beginning and trace how you ended up there and it's

1105
00:57:36,880 --> 00:57:39,480
Speaker 1: impact for the broader world, because again, I think that's

1106
00:57:39,520 --> 00:57:42,000
Speaker 1: one of the areas that in our day to day life,

1107
00:57:42,040 --> 00:57:43,880
Speaker 1: we forget that so many of the things that make

1108
00:57:43,920 --> 00:57:46,600
Speaker 1: our lives easier or better in some way are due

1109
00:57:46,600 --> 00:57:49,200
Speaker 1: to scientists like yourself working away in the background.

1110
00:57:49,440 --> 00:57:49,680
Speaker 3: Yeah.

1111
00:57:49,760 --> 00:57:54,560
Speaker 7: Sure, So I'm a neuroscientist and my predominant focus is

1112
00:57:54,640 --> 00:57:58,880
Speaker 7: on mental health and specifically on anxiety. So I focus

1113
00:57:59,040 --> 00:58:01,960
Speaker 7: on the links between the brain and body and how

1114
00:58:02,200 --> 00:58:05,400
Speaker 7: the symptoms of anxiety can actually end up in your body.

1115
00:58:06,080 --> 00:58:08,800
Speaker 3: So if you remember back to the last time you.

1116
00:58:08,840 --> 00:58:11,440
Speaker 7: Might have been really worried about something, and if you

1117
00:58:11,480 --> 00:58:15,200
Speaker 7: think about not only all those thoughts that were racing

1118
00:58:15,240 --> 00:58:17,920
Speaker 7: around in your head, but also how you might have felt.

1119
00:58:18,720 --> 00:58:21,840
Speaker 7: So maybe you felt your heart beat a bit quicker,

1120
00:58:22,400 --> 00:58:25,120
Speaker 7: maybe your palms were a little bit sweety, maybe you

1121
00:58:25,200 --> 00:58:28,080
Speaker 7: felt a little bit light headed, And all of these

1122
00:58:28,160 --> 00:58:30,680
Speaker 7: things are because those symptoms end up in our body,

1123
00:58:31,600 --> 00:58:34,760
Speaker 7: and if we don't notice those or we don't intervene

1124
00:58:34,920 --> 00:58:37,480
Speaker 7: early to stop that happening, it can actually make us

1125
00:58:37,560 --> 00:58:40,920
Speaker 7: feel worse. So if we, for instance, breathe a bit faster,

1126
00:58:41,080 --> 00:58:43,800
Speaker 7: or change our breathing, or really put ourselves in that

1127
00:58:43,880 --> 00:58:47,160
Speaker 7: anxiety state, it makes us feel worse and feeds back

1128
00:58:47,240 --> 00:58:49,479
Speaker 7: to our brain that we should be more anxious about things.

1129
00:58:50,080 --> 00:58:51,080
Speaker 3: So that's what I do.

1130
00:58:51,280 --> 00:58:54,200
Speaker 7: I try and look at that communication between the brain

1131
00:58:54,280 --> 00:58:56,920
Speaker 7: and body and try and understand where it might be

1132
00:58:57,040 --> 00:58:59,880
Speaker 7: going a little bit haywire with anxiety and how we

1133
00:59:00,040 --> 00:59:00,800
Speaker 7: can maybe try.

1134
00:59:00,720 --> 00:59:01,200
Speaker 4: And fix that.

1135
00:59:01,520 --> 00:59:04,800
Speaker 1: Oh my gosh, Well, I'm particularly excited to be speaking

1136
00:59:04,880 --> 00:59:08,800
Speaker 1: with you today about this because I probably for the

1137
00:59:08,960 --> 00:59:11,880
Speaker 1: past five or six years, I had a big health

1138
00:59:11,920 --> 00:59:15,200
Speaker 1: event after a trip to Africa and during I had

1139
00:59:15,240 --> 00:59:17,880
Speaker 1: a gout parasite and became very severely overweight. And I

1140
00:59:17,960 --> 00:59:22,600
Speaker 1: think that activated what had been bouts of anxiety in

1141
00:59:23,000 --> 00:59:24,840
Speaker 1: my younger years, but maybe I hadn't been able to

1142
00:59:24,920 --> 00:59:29,080
Speaker 1: identify that and started a string of quite serious panic attacks.

1143
00:59:29,120 --> 00:59:32,240
Speaker 1: And I think anxiety is a bit of a misnomer

1144
00:59:32,520 --> 00:59:35,880
Speaker 1: because you equate it with anxiousness, which is a normal

1145
00:59:36,160 --> 00:59:39,160
Speaker 1: this emotion, you know, on the spectrum of emotions. But

1146
00:59:39,720 --> 00:59:42,160
Speaker 1: the first panic attack I had, I think I've spoken

1147
00:59:42,160 --> 00:59:45,000
Speaker 1: about this a couple of times. I called an ambulance

1148
00:59:45,000 --> 00:59:47,000
Speaker 1: because I thought I was having a heart attack. I

1149
00:59:47,080 --> 00:59:50,720
Speaker 1: didn't know it could be physiological, but my arms went numb,

1150
00:59:51,200 --> 00:59:54,400
Speaker 1: my lips went blue, I couldn't breathe, and when they

1151
00:59:54,520 --> 00:59:56,280
Speaker 1: told me the paramedics are like, you're just having a

1152
00:59:56,320 --> 00:59:57,600
Speaker 1: panic attack, it's just anxiety.

1153
00:59:57,600 --> 00:59:59,760
Speaker 2: I was like, I'm sorry, I'm dying.

1154
01:00:00,000 --> 01:00:01,560
Speaker 1: An you please take me to the hospital.

1155
01:00:02,520 --> 01:00:05,400
Speaker 7: You're exactly right, this is you know, it's fantastic that

1156
01:00:05,440 --> 01:00:08,200
Speaker 7: we're talking about this more, but the language that we

1157
01:00:08,360 --> 01:00:11,080
Speaker 7: use can be a little bit confusing, because, like you say,

1158
01:00:11,240 --> 01:00:14,040
Speaker 7: being anxious and worried about things is totally normal and

1159
01:00:14,200 --> 01:00:16,040
Speaker 7: what we need to keep us alive. If we took

1160
01:00:16,040 --> 01:00:17,919
Speaker 7: away all the anxiety in the world, that the human

1161
01:00:18,000 --> 01:00:21,120
Speaker 7: race wouldn't exist. So we have to have that, and

1162
01:00:21,600 --> 01:00:24,280
Speaker 7: it's a sort of unfortunate that it's the same wording

1163
01:00:24,600 --> 01:00:27,040
Speaker 7: as anxiety when you have an anxiety disorder.

1164
01:00:27,720 --> 01:00:29,720
Speaker 3: And the other thing I really want to speak to

1165
01:00:29,880 --> 01:00:30,320
Speaker 3: there is.

1166
01:00:30,360 --> 01:00:35,560
Speaker 7: That that dismissive language of oh, it's only anxiety or

1167
01:00:35,600 --> 01:00:39,880
Speaker 7: it's just in your head is really really misleading, because

1168
01:00:40,040 --> 01:00:43,320
Speaker 7: those symptoms are real, they are happening. They're not just

1169
01:00:43,440 --> 01:00:45,400
Speaker 7: in your head. They are in your body. You are

1170
01:00:45,480 --> 01:00:48,400
Speaker 7: having that racing heart, you're having those lips turning blue.

1171
01:00:48,440 --> 01:00:51,560
Speaker 3: They're not fake. So what it shows is that the

1172
01:00:51,600 --> 01:00:54,840
Speaker 3: brain is just really, really powerful and.

1173
01:00:54,920 --> 01:00:57,880
Speaker 7: It can cause those things just from the thoughts that

1174
01:00:58,120 --> 01:01:01,680
Speaker 7: are the origination instead of maybe a pathology like something

1175
01:01:01,760 --> 01:01:03,400
Speaker 7: wrong with your heart in the first place. So it's

1176
01:01:03,440 --> 01:01:05,800
Speaker 7: always really important to get those things checked and to

1177
01:01:05,880 --> 01:01:08,520
Speaker 7: make sure that there's not an underlying pathology. But it

1178
01:01:08,640 --> 01:01:10,280
Speaker 7: doesn't mean those things aren't real.

1179
01:01:10,720 --> 01:01:11,520
Speaker 3: They're really real.

1180
01:01:11,760 --> 01:01:15,040
Speaker 1: Yeah, absolutely, And I really just once I sort of

1181
01:01:15,080 --> 01:01:21,440
Speaker 1: started to understand the physiological and really tangible symptoms of anxiety,

1182
01:01:21,800 --> 01:01:24,720
Speaker 1: I suddenly just regretted how many years I'd spent telling

1183
01:01:24,800 --> 01:01:27,680
Speaker 1: friends who had anxiety when they'd be having an episode

1184
01:01:28,080 --> 01:01:30,200
Speaker 1: or just having a flare up. You know, I'd be like,

1185
01:01:30,320 --> 01:01:33,680
Speaker 1: just get a massage, just calm down, as if that

1186
01:01:33,760 --> 01:01:37,400
Speaker 1: would do anything for their you know, psychological state. But

1187
01:01:37,920 --> 01:01:41,280
Speaker 1: the problem is those things don't even feel relaxing or

1188
01:01:41,360 --> 01:01:45,080
Speaker 1: feel enjoyable when you're in a really heightened anxious state.

1189
01:01:45,240 --> 01:01:49,040
Speaker 1: So it's so wonderful that there are conversations happening and

1190
01:01:49,200 --> 01:01:53,880
Speaker 1: research into these connections. Once you sort of do make

1191
01:01:54,000 --> 01:01:57,480
Speaker 1: those links neurologically, what do you do with the results

1192
01:01:57,520 --> 01:02:00,920
Speaker 1: of that. Is it to tailor the treatment programs, Is

1193
01:02:01,000 --> 01:02:03,959
Speaker 1: it to put into a database. How are we using

1194
01:02:04,000 --> 01:02:04,640
Speaker 1: that information?

1195
01:02:05,120 --> 01:02:06,640
Speaker 3: Yeah, that's a really important question.

1196
01:02:06,960 --> 01:02:09,320
Speaker 7: So what we've done up to now is just try

1197
01:02:09,360 --> 01:02:12,240
Speaker 7: and identify where it might be going wrong. So that's

1198
01:02:12,280 --> 01:02:14,240
Speaker 7: what we've been doing with our recent research, and what

1199
01:02:14,360 --> 01:02:17,320
Speaker 7: we've seen is that people with slightly higher levels of

1200
01:02:17,320 --> 01:02:20,960
Speaker 7: anxiety perfectly normal people with no diagnoses but sort of

1201
01:02:21,040 --> 01:02:24,120
Speaker 7: average levels of anxiety. What we do is we tend

1202
01:02:24,200 --> 01:02:26,760
Speaker 7: to actually tune out of our bodies a little bit.

1203
01:02:26,880 --> 01:02:29,600
Speaker 7: Even though we think we're really hyper aware and we

1204
01:02:29,680 --> 01:02:32,080
Speaker 7: think we're tuning in, we actually are a little bit

1205
01:02:32,240 --> 01:02:34,360
Speaker 7: less sensitive to change this in our body, and we

1206
01:02:34,440 --> 01:02:37,440
Speaker 7: think that can contribute to that sort of perpetuated cycle

1207
01:02:37,520 --> 01:02:40,520
Speaker 7: where you have anxious thoughts and then you have symptoms

1208
01:02:40,520 --> 01:02:42,200
Speaker 7: in your body, and then you have more anxious thoughts.

1209
01:02:42,840 --> 01:02:45,280
Speaker 7: So now what we do with that information is we

1210
01:02:45,400 --> 01:02:48,720
Speaker 7: try and see how treatments that we already have that

1211
01:02:48,840 --> 01:02:51,280
Speaker 7: we know work most of the time, what are they

1212
01:02:51,360 --> 01:02:53,560
Speaker 7: doing and who do they work for. So the two

1213
01:02:53,640 --> 01:02:58,000
Speaker 7: things we're focusing on are exercise and also anti anxiety

1214
01:02:58,120 --> 01:03:00,720
Speaker 7: medication because we know that both of those things work

1215
01:03:00,840 --> 01:03:03,480
Speaker 7: really well for lots of people, but not for everyone,

1216
01:03:03,880 --> 01:03:07,520
Speaker 7: and we don't really know what behaviors they're targeting or

1217
01:03:08,040 --> 01:03:11,080
Speaker 7: what they're allowing you to do to help improve those

1218
01:03:11,120 --> 01:03:14,640
Speaker 7: anxiety symptoms. So the next step is what do our

1219
01:03:14,640 --> 01:03:17,080
Speaker 7: current treatments do and who do they work for? And

1220
01:03:17,240 --> 01:03:19,400
Speaker 7: then we think about how do we make that better,

1221
01:03:19,520 --> 01:03:22,000
Speaker 7: how do we tailor it for each person? How do

1222
01:03:22,120 --> 01:03:25,120
Speaker 7: we really think about what an individual needs and how

1223
01:03:25,160 --> 01:03:27,400
Speaker 7: we can help them the best instead of just giving

1224
01:03:27,440 --> 01:03:30,000
Speaker 7: a blanket, I'll just go for a run and you'll

1225
01:03:30,040 --> 01:03:30,640
Speaker 7: feel better.

1226
01:03:33,960 --> 01:03:36,760
Speaker 1: Oh my gosh, I have been told that quite a

1227
01:03:36,840 --> 01:03:39,560
Speaker 1: few times. And in the height of anxiety, I mean,

1228
01:03:39,840 --> 01:03:42,439
Speaker 1: you really just often don't feel like leaving the house

1229
01:03:42,520 --> 01:03:42,800
Speaker 1: at all.

1230
01:03:43,000 --> 01:03:46,920
Speaker 7: So no, exactly, So can we figure out what is

1231
01:03:47,000 --> 01:03:51,160
Speaker 7: the essence of what's improving there? Is it the feeling

1232
01:03:51,200 --> 01:03:55,560
Speaker 7: of accomplishment going for a run. Is it that sort

1233
01:03:55,560 --> 01:03:57,880
Speaker 7: of feeling of control you get where you have the

1234
01:03:57,960 --> 01:03:59,960
Speaker 7: symptoms in your body, but you know what's causing them.

1235
01:04:00,160 --> 01:04:02,040
Speaker 7: You know you've gone for a run, and you can

1236
01:04:02,080 --> 01:04:03,720
Speaker 7: slow down and make them go away, or you can

1237
01:04:03,760 --> 01:04:05,800
Speaker 7: speed up and make them feel a little bit more intense,

1238
01:04:06,000 --> 01:04:09,120
Speaker 7: that feeling of control. So or is it just that

1239
01:04:09,520 --> 01:04:12,360
Speaker 7: if we give our body these positive symptoms, do we

1240
01:04:12,440 --> 01:04:15,680
Speaker 7: start to retrain our negative thoughts towards them. So we

1241
01:04:15,840 --> 01:04:17,320
Speaker 7: just want to know what it is and then how

1242
01:04:17,360 --> 01:04:19,200
Speaker 7: do we break that down to maybe the first baby

1243
01:04:19,240 --> 01:04:21,360
Speaker 7: step of someone who really doesn't want to leave the house,

1244
01:04:21,400 --> 01:04:23,680
Speaker 7: So who doesn't want to do that? What can we

1245
01:04:23,760 --> 01:04:26,480
Speaker 7: do that will really resonate with that person because it's

1246
01:04:26,520 --> 01:04:27,400
Speaker 7: different for everyone.

1247
01:04:27,640 --> 01:04:27,840
Speaker 6: Yeah.

1248
01:04:27,920 --> 01:04:30,240
Speaker 1: Absolutely, And I think one of the hardest things is

1249
01:04:30,360 --> 01:04:33,320
Speaker 1: how it's really easy to grade a broken arm or

1250
01:04:33,880 --> 01:04:36,000
Speaker 1: you know, in severity, like the spectrum of injury is

1251
01:04:36,080 --> 01:04:39,320
Speaker 1: quite visible and tangible, but with mental health it's so

1252
01:04:39,400 --> 01:04:42,480
Speaker 1: much harder to see and to measure. And so I'm

1253
01:04:42,600 --> 01:04:45,880
Speaker 1: so grateful and excited that there are neuroscientists out there

1254
01:04:46,000 --> 01:04:48,200
Speaker 1: like you actually working on this so that we can

1255
01:04:48,280 --> 01:04:52,480
Speaker 1: understand it a lot better and move forward. What I

1256
01:04:52,520 --> 01:04:55,520
Speaker 1: think is fascinating here is that you know, I often

1257
01:04:55,560 --> 01:04:57,600
Speaker 1: will say, like, don't even worry about it, guys, it's

1258
01:04:57,640 --> 01:05:01,120
Speaker 1: not neuroscience, except that you're an actual new roscientists. So

1259
01:05:02,320 --> 01:05:05,480
Speaker 1: how does one end up as a neuroscientist? Have you

1260
01:05:05,920 --> 01:05:09,120
Speaker 1: always been interested in it? I'm something we're really fascinated

1261
01:05:09,320 --> 01:05:12,520
Speaker 1: at this show about is the nonlinear nature of people's

1262
01:05:12,560 --> 01:05:14,960
Speaker 1: pathways and that you know, you may be someone who

1263
01:05:15,040 --> 01:05:16,760
Speaker 1: woke up at five and knew you wanted to do this,

1264
01:05:16,920 --> 01:05:19,760
Speaker 1: but it's likely that it took lots of diversions and

1265
01:05:19,840 --> 01:05:22,280
Speaker 1: tangents along the way. So how did you get here?

1266
01:05:22,400 --> 01:05:22,920
Speaker 3: Definitely?

1267
01:05:23,200 --> 01:05:26,320
Speaker 7: Mine definitely took a few twists and turns, but all

1268
01:05:26,480 --> 01:05:29,480
Speaker 7: exciting and all made me who I am now. So

1269
01:05:30,200 --> 01:05:32,840
Speaker 7: growing up, I was always really interested in sport. I

1270
01:05:32,960 --> 01:05:35,360
Speaker 7: loved sport, did as much as I could anything I

1271
01:05:35,400 --> 01:05:37,320
Speaker 7: could get my hands on, and so I knew that

1272
01:05:37,400 --> 01:05:39,840
Speaker 7: I really wanted to study that. At university, I wanted

1273
01:05:39,880 --> 01:05:42,440
Speaker 7: to be involved as much as I could, so I

1274
01:05:42,520 --> 01:05:47,120
Speaker 7: studied physical education and exercise science. Really I was a

1275
01:05:47,480 --> 01:05:51,720
Speaker 7: pee student, but I also wanted to do brain control

1276
01:05:51,800 --> 01:05:53,600
Speaker 7: of this. I was interested in a bit more than

1277
01:05:53,720 --> 01:05:56,080
Speaker 7: just the body. I wanted to know about the brain

1278
01:05:56,120 --> 01:05:59,520
Speaker 7: as well. So at university I studied two degrees exercise

1279
01:05:59,560 --> 01:06:03,400
Speaker 7: science and in neuroscience. And it was really cool because

1280
01:06:03,600 --> 01:06:08,240
Speaker 7: it let me do hardcore neuroscience cellular stuff understanding the brain.

1281
01:06:08,440 --> 01:06:11,200
Speaker 3: And then also you go into the exercise science world.

1282
01:06:11,280 --> 01:06:15,200
Speaker 7: And it's messy and you just do things and you

1283
01:06:15,360 --> 01:06:17,680
Speaker 7: stick probes on people and you just get on with

1284
01:06:17,760 --> 01:06:21,320
Speaker 7: it and they're brilliant, So very different to the controlled

1285
01:06:21,480 --> 01:06:24,400
Speaker 7: neuroscience environments. Single cell recordings, things like that, so I

1286
01:06:24,480 --> 01:06:28,960
Speaker 7: got the real full spectrum in my undergraduate degrees. And

1287
01:06:29,080 --> 01:06:31,120
Speaker 7: then I was always interested, like I said, in sports,

1288
01:06:31,120 --> 01:06:33,080
Speaker 7: so I moved into high performance sport and I wanted

1289
01:06:33,160 --> 01:06:35,600
Speaker 7: to know what can help athletes, How can we make

1290
01:06:35,640 --> 01:06:37,400
Speaker 7: them perform better, how can we get the.

1291
01:06:37,400 --> 01:06:40,560
Speaker 3: Most out of them. But as an athlete myself.

1292
01:06:40,280 --> 01:06:44,440
Speaker 7: I always always noticed my breathing when I was exercising.

1293
01:06:44,600 --> 01:06:47,280
Speaker 7: Always it was something that I felt not only was there,

1294
01:06:47,320 --> 01:06:48,880
Speaker 7: but it was also a little bit scary when I

1295
01:06:48,960 --> 01:06:51,479
Speaker 7: was really operating at my max. And I always thought,

1296
01:06:51,920 --> 01:06:54,240
Speaker 7: you know, what's going on here? It can't just be

1297
01:06:54,440 --> 01:06:57,880
Speaker 7: our body limiting all of these sort of physicality when

1298
01:06:57,880 --> 01:06:59,760
Speaker 7: we do exercise. But there's got to be a bit

1299
01:06:59,840 --> 01:07:03,160
Speaker 7: more more than that. So I went over to the

1300
01:07:03,240 --> 01:07:05,640
Speaker 7: University of Oxford to do my PhD. And I did

1301
01:07:05,720 --> 01:07:09,000
Speaker 7: it in neuroscience, but I looked at the perception of

1302
01:07:09,040 --> 01:07:11,400
Speaker 7: breathing in the brain. So it's really interested in where

1303
01:07:11,440 --> 01:07:13,320
Speaker 7: do we perceive this, how do we perceive it as

1304
01:07:13,360 --> 01:07:17,320
Speaker 7: a threat, what happens with people who have chronic lung diseases,

1305
01:07:17,600 --> 01:07:19,840
Speaker 7: and also what happens in athletes. So I did a

1306
01:07:19,880 --> 01:07:21,480
Speaker 7: lot of work on that to try and understand how

1307
01:07:21,560 --> 01:07:24,280
Speaker 7: athletes might process those symptoms from their body differently, which

1308
01:07:24,320 --> 01:07:27,520
Speaker 7: is really cool. And what we saw is that people

1309
01:07:27,520 --> 01:07:29,320
Speaker 7: who do lots of sport are a bit better at

1310
01:07:29,400 --> 01:07:31,919
Speaker 7: predicting what's going to happen to their body. Their brain

1311
01:07:32,040 --> 01:07:34,280
Speaker 7: is a bit more ready for what happens because they've

1312
01:07:34,280 --> 01:07:37,360
Speaker 7: got lots of experience with it. So that was really interesting.

1313
01:07:38,360 --> 01:07:41,280
Speaker 7: And then I was still interested in sort of that

1314
01:07:41,520 --> 01:07:44,560
Speaker 7: more holistic mental health side of things. You know, everyone's

1315
01:07:44,640 --> 01:07:46,680
Speaker 7: after that two percent. How do we make an athlete

1316
01:07:46,720 --> 01:07:49,560
Speaker 7: two percent better so that they can perform at their best?

1317
01:07:49,960 --> 01:07:51,920
Speaker 7: And I was kind of like, what if they're having

1318
01:07:51,960 --> 01:07:55,480
Speaker 7: a bad day, you know, what if it's just not

1319
01:07:55,600 --> 01:07:57,280
Speaker 7: gone well in their personal life.

1320
01:07:58,120 --> 01:07:59,840
Speaker 3: So I always thought there should be a little bit

1321
01:07:59,880 --> 01:08:00,520
Speaker 3: more more than that.

1322
01:08:00,720 --> 01:08:03,200
Speaker 7: And then sort of slowly it sort of dawned on

1323
01:08:03,280 --> 01:08:05,160
Speaker 7: me that it was exercise for mental health.

1324
01:08:05,240 --> 01:08:07,360
Speaker 3: How do we use this as a tool to help people?

1325
01:08:07,760 --> 01:08:10,240
Speaker 3: And that really took lots.

1326
01:08:10,040 --> 01:08:14,760
Speaker 7: Of years of education training to circle back to exercise

1327
01:08:14,840 --> 01:08:17,719
Speaker 7: but in that scheme of mental health. But all along

1328
01:08:17,760 --> 01:08:20,240
Speaker 7: the way, it's been such an incredible journey learning about

1329
01:08:20,280 --> 01:08:23,240
Speaker 7: all these different fields and the beauty of neurosciences. That

1330
01:08:23,400 --> 01:08:27,559
Speaker 7: you do anatomy, physiology, psychology, you do the whole share bang.

1331
01:08:27,960 --> 01:08:31,520
Speaker 7: And so I'm sort of broadly across all of these disciplines,

1332
01:08:31,560 --> 01:08:34,040
Speaker 7: but in a really integrative way, really keen on the

1333
01:08:34,120 --> 01:08:35,880
Speaker 7: whole person and how we can help them.

1334
01:08:36,000 --> 01:08:38,680
Speaker 1: That's so exciting to hear because I think another thing

1335
01:08:38,760 --> 01:08:40,400
Speaker 1: we talk about a lot in the show is the

1336
01:08:41,280 --> 01:08:45,759
Speaker 1: unlikely unions of areas of study that you know, because

1337
01:08:45,840 --> 01:08:49,360
Speaker 1: you silo careers so much when you're in high school,

1338
01:08:49,439 --> 01:08:53,640
Speaker 1: we kind of think of things as very delineated categories.

1339
01:08:53,760 --> 01:08:57,040
Speaker 1: You don't think that you could merge exercise science with neuroscience,

1340
01:08:57,080 --> 01:08:58,680
Speaker 1: you know, I mean, they're both sciences, but you just

1341
01:08:58,720 --> 01:09:00,880
Speaker 1: don't think of You think, oh, well, that's a pe

1342
01:09:01,000 --> 01:09:03,280
Speaker 1: teacher over there, and that's a neuroscientist in a lab

1343
01:09:03,400 --> 01:09:05,639
Speaker 1: over there. And it's so exciting that you can forge

1344
01:09:05,640 --> 01:09:10,240
Speaker 1: a pathway that merges lots of seemingly different areas.

1345
01:09:09,920 --> 01:09:12,920
Speaker 2: And that careers exist in those gray areas in between,

1346
01:09:13,200 --> 01:09:14,000
Speaker 2: I think very much.

1347
01:09:14,080 --> 01:09:17,600
Speaker 3: So I think there it's also so exciting that you

1348
01:09:17,760 --> 01:09:18,320
Speaker 3: can do that.

1349
01:09:18,520 --> 01:09:22,280
Speaker 7: Now you know this idea of a scientist as a

1350
01:09:23,479 --> 01:09:25,479
Speaker 7: guy in a white coat with a test tube that

1351
01:09:25,600 --> 01:09:26,760
Speaker 7: we used to think of.

1352
01:09:27,560 --> 01:09:30,679
Speaker 3: It just doesn't exist anymore. We do our own things.

1353
01:09:30,800 --> 01:09:33,080
Speaker 7: We create new knowledge, and I think being in a

1354
01:09:33,120 --> 01:09:36,320
Speaker 7: field like neuroscience is fantastic because it is new and.

1355
01:09:36,439 --> 01:09:38,360
Speaker 3: So it's really exciting.

1356
01:09:38,439 --> 01:09:41,400
Speaker 7: The opportunities are really boundless, and we're not constrained by

1357
01:09:41,439 --> 01:09:44,120
Speaker 7: some of the other really pure sciences and the way

1358
01:09:44,200 --> 01:09:46,840
Speaker 7: that everything has always been done. You know, things just

1359
01:09:46,960 --> 01:09:50,120
Speaker 7: change rapidly in neuroscience and so we just all race

1360
01:09:50,240 --> 01:09:51,920
Speaker 7: to keep up and try and find something new. It's

1361
01:09:51,960 --> 01:09:52,519
Speaker 7: really exciting.

1362
01:09:52,640 --> 01:09:54,439
Speaker 1: It must be so wonderful to be in an area

1363
01:09:54,560 --> 01:09:57,120
Speaker 1: like I just cannot believe. I mean, we have made

1364
01:09:57,360 --> 01:10:01,120
Speaker 1: such leaps and bounds in scientific technology, general technology, but

1365
01:10:01,240 --> 01:10:03,479
Speaker 1: the fact that we know, what's the percentage of the

1366
01:10:03,560 --> 01:10:06,240
Speaker 1: brain's function that we actually know about it's like a

1367
01:10:06,520 --> 01:10:08,760
Speaker 1: tiny minority of what the brain does. We're at like

1368
01:10:08,920 --> 01:10:11,720
Speaker 1: one percent knowledge, which is like, wow, there's ninety nine

1369
01:10:11,720 --> 01:10:12,360
Speaker 1: percent left.

1370
01:10:13,520 --> 01:10:16,759
Speaker 3: It's really cool. It's yeah, there's so much left to understand.

1371
01:10:17,360 --> 01:10:20,559
Speaker 7: And I think that barrier, like you say, we don't

1372
01:10:20,640 --> 01:10:22,439
Speaker 7: have that readout like you do when you have a

1373
01:10:22,520 --> 01:10:25,280
Speaker 7: broken arm. It's easy to grade those things to see

1374
01:10:25,320 --> 01:10:27,639
Speaker 7: what's happening in the human brain as it functions.

1375
01:10:27,760 --> 01:10:30,559
Speaker 3: Is really challenging and really exciting, and it's tucked away

1376
01:10:30,680 --> 01:10:33,800
Speaker 3: and encased in your head, so it's really hard to see.

1377
01:10:34,400 --> 01:10:36,719
Speaker 3: But that's what makes it really exciting.

1378
01:10:36,880 --> 01:10:39,840
Speaker 7: And you know, I work with lots of anatomists and

1379
01:10:39,920 --> 01:10:42,720
Speaker 7: they're much more happy in a control environment where they're

1380
01:10:42,800 --> 01:10:45,679
Speaker 7: just working on a brain maybe that's already from someone

1381
01:10:45,720 --> 01:10:47,000
Speaker 7: who's deceased or whatever.

1382
01:10:47,040 --> 01:10:49,719
Speaker 3: They're like, it's much easier if it's just just there,

1383
01:10:50,040 --> 01:10:52,240
Speaker 3: you know, doing anything.

1384
01:10:54,920 --> 01:10:59,280
Speaker 1: Just quantifiable and measurable. It's noign entity.

1385
01:11:00,680 --> 01:11:01,560
Speaker 4: And I can see it.

1386
01:11:01,880 --> 01:11:05,040
Speaker 7: And it's great wherecause it's so much more challenging working

1387
01:11:05,120 --> 01:11:09,120
Speaker 7: with the human living people and they're missy and they're

1388
01:11:09,360 --> 01:11:11,000
Speaker 7: all these different systems working together.

1389
01:11:11,120 --> 01:11:12,000
Speaker 3: But that's the beauty of it.

1390
01:11:12,160 --> 01:11:13,120
Speaker 2: Oh so exciting.

1391
01:11:13,200 --> 01:11:17,960
Speaker 1: I actually remember when I was starting psychology and trying to,

1392
01:11:18,479 --> 01:11:20,760
Speaker 1: you know, find the right match, because you know, you

1393
01:11:21,400 --> 01:11:23,800
Speaker 1: often experiment with lots of different psychologists to find the

1394
01:11:23,880 --> 01:11:26,160
Speaker 1: right fit for you. But you have to tell the

1395
01:11:26,240 --> 01:11:28,479
Speaker 1: story every time and give all the context. And I

1396
01:11:28,600 --> 01:11:30,400
Speaker 1: just wish that there was a way I could just

1397
01:11:30,760 --> 01:11:33,439
Speaker 1: like download my brain and just give it to them

1398
01:11:33,479 --> 01:11:36,240
Speaker 1: and be like, so here's my file. You just consult

1399
01:11:36,320 --> 01:11:39,800
Speaker 1: it by yourself will be so easy. So can you

1400
01:11:39,880 --> 01:11:41,280
Speaker 1: invent that place? Because I'd be amazing.

1401
01:11:42,960 --> 01:11:44,160
Speaker 3: I'll put it on the to do list.

1402
01:11:45,040 --> 01:11:49,080
Speaker 1: Yeah. So you mentioned like there are a lot of

1403
01:11:49,160 --> 01:11:51,320
Speaker 1: areas of science where there is still a lot of

1404
01:11:51,680 --> 01:11:54,320
Speaker 1: traditions or conventions all the way things have always been done.

1405
01:11:54,360 --> 01:11:57,560
Speaker 1: And I think STEM as an area of you know,

1406
01:11:58,120 --> 01:12:01,920
Speaker 1: vocation has traditionally been quite male dominated. There are still

1407
01:12:01,920 --> 01:12:06,679
Speaker 1: a lot of misconceptions about the male and a white

1408
01:12:06,720 --> 01:12:08,640
Speaker 1: coat with a test tube or an engineer being on

1409
01:12:08,680 --> 01:12:12,040
Speaker 1: a construction site. And have you experienced any kind of

1410
01:12:12,280 --> 01:12:15,720
Speaker 1: barriers or obstacles in science as a woman, And are

1411
01:12:15,760 --> 01:12:18,720
Speaker 1: there any tips or advice that you would pass on

1412
01:12:18,840 --> 01:12:21,400
Speaker 1: to women who are aspiring to a career in STEM.

1413
01:12:21,479 --> 01:12:24,439
Speaker 7: Yeah, that's a really fantastic question. I think I've been

1414
01:12:24,560 --> 01:12:27,920
Speaker 7: really lucky. I've been incredibly well supported by my family.

1415
01:12:28,160 --> 01:12:31,599
Speaker 7: I've had the most fantastic education, and we were really

1416
01:12:31,760 --> 01:12:33,679
Speaker 7: encouraged to go into STEM subjects.

1417
01:12:33,720 --> 01:12:35,880
Speaker 3: So I know I'm really one of the lucky ones.

1418
01:12:37,160 --> 01:12:41,000
Speaker 7: And I think through experience, I've really seen that it's

1419
01:12:41,080 --> 01:12:45,080
Speaker 7: about finding your strengths as a scientist and using those

1420
01:12:45,160 --> 01:12:47,439
Speaker 7: as best you can, not trying to conform to someone

1421
01:12:47,520 --> 01:12:50,600
Speaker 7: else's version of a scientist. And I think the pandemic's

1422
01:12:50,640 --> 01:12:53,840
Speaker 7: actually really helped us with that because we've seen some

1423
01:12:53,960 --> 01:12:58,559
Speaker 7: of the really active voices communicating this really important science

1424
01:12:58,640 --> 01:13:02,599
Speaker 7: that's let us fight this COVID nineteen pandemic. And we've

1425
01:13:02,600 --> 01:13:05,240
Speaker 7: seen how important it is that it's not just someone

1426
01:13:05,320 --> 01:13:07,640
Speaker 7: in a lab. We have to be able to communicate that.

1427
01:13:07,800 --> 01:13:10,839
Speaker 7: We have to be able to run teams and support

1428
01:13:10,920 --> 01:13:13,120
Speaker 7: everyone towards a shared scientific goal.

1429
01:13:13,600 --> 01:13:15,720
Speaker 3: And that involves so.

1430
01:13:15,840 --> 01:13:18,640
Speaker 7: Many different people in all their different strengths. So it's

1431
01:13:18,680 --> 01:13:22,080
Speaker 7: about finding what you're really comfortable doing and how to

1432
01:13:22,160 --> 01:13:23,840
Speaker 7: make that work for you. So is it that you

1433
01:13:24,000 --> 01:13:26,120
Speaker 7: really love supporting a team, Is it that you love

1434
01:13:26,200 --> 01:13:29,600
Speaker 7: getting everyone together and working on shared ideas, or is

1435
01:13:29,680 --> 01:13:31,719
Speaker 7: it that you love talking about it to your friends

1436
01:13:31,760 --> 01:13:34,000
Speaker 7: and your family or maybe even the wider community. And

1437
01:13:34,080 --> 01:13:36,360
Speaker 7: you're really good at it. You can tell people really

1438
01:13:36,439 --> 01:13:39,880
Speaker 7: complicated scenarios and information and you can make it really

1439
01:13:39,920 --> 01:13:42,639
Speaker 7: easy to understand. That's a huge strength in something that's

1440
01:13:43,040 --> 01:13:47,120
Speaker 7: really valued in today's STEM. Not just doing the maths

1441
01:13:47,240 --> 01:13:50,519
Speaker 7: equations or running the test tubes in the lab.

1442
01:13:50,680 --> 01:13:51,840
Speaker 3: There's so much more than that.

1443
01:13:52,360 --> 01:13:53,760
Speaker 2: Yeah, that's so good to know.

1444
01:13:54,600 --> 01:13:57,599
Speaker 1: Have you found that? I know that, you know, one

1445
01:13:57,640 --> 01:13:59,639
Speaker 1: of the things I talk about in terms of building

1446
01:13:59,680 --> 01:14:02,320
Speaker 1: your pasta is having the right neighborhood, like the right

1447
01:14:02,400 --> 01:14:05,720
Speaker 1: support network and different mentors. And often it will be

1448
01:14:06,040 --> 01:14:09,280
Speaker 1: just one person and one conversation that exposes you to

1449
01:14:09,400 --> 01:14:12,000
Speaker 1: a whole new direction that your scientific career can take.

1450
01:14:12,240 --> 01:14:14,680
Speaker 1: And that can be other women to help you as

1451
01:14:14,720 --> 01:14:18,120
Speaker 1: a woman in science, or male scientists as counterparts. Have

1452
01:14:18,240 --> 01:14:22,120
Speaker 1: you found mentors really helpful and how do you find them?

1453
01:14:22,920 --> 01:14:25,080
Speaker 1: Have you had lots of different mentors or how do

1454
01:14:25,120 --> 01:14:27,479
Speaker 1: you kind of get exposure to new and different scientists?

1455
01:14:27,600 --> 01:14:28,760
Speaker 3: Also a really great question.

1456
01:14:29,320 --> 01:14:32,000
Speaker 7: I tend to really try and say yes to lots

1457
01:14:32,040 --> 01:14:34,719
Speaker 7: of opportunities that come up my kee accent.

1458
01:14:34,920 --> 01:14:40,679
Speaker 1: Yes, it's more impactful when you say in a key exactly.

1459
01:14:41,680 --> 01:14:45,240
Speaker 7: So, Yeah, having exposure and not being afraid to take

1460
01:14:45,280 --> 01:14:47,880
Speaker 7: that leap and go somewhere new for different experiences because

1461
01:14:47,920 --> 01:14:52,080
Speaker 7: every labs run differently, every universities run differently, every company

1462
01:14:52,240 --> 01:14:55,680
Speaker 7: that runs scientific testing has run differently, so you know,

1463
01:14:55,840 --> 01:14:59,760
Speaker 7: grasping those opportunities and talking to people is definitely one

1464
01:14:59,800 --> 01:15:00,679
Speaker 7: of them ways forward.

1465
01:15:00,960 --> 01:15:04,040
Speaker 3: And then I've had lots of wonderful mentors. Right from school.

1466
01:15:04,240 --> 01:15:06,200
Speaker 7: I had a really great teacher who I could talk

1467
01:15:06,280 --> 01:15:08,920
Speaker 7: to about what I thought I wanted to do but

1468
01:15:09,280 --> 01:15:11,519
Speaker 7: wasn't quite sure, and she introduced me to someone who

1469
01:15:11,560 --> 01:15:14,439
Speaker 7: could then help me make some decisions about university, but

1470
01:15:14,560 --> 01:15:16,960
Speaker 7: really just reassure me that it wasn't set in stone.

1471
01:15:17,120 --> 01:15:19,439
Speaker 3: I could change or you can just try this to

1472
01:15:19,479 --> 01:15:20,639
Speaker 3: start with and see how it goes.

1473
01:15:20,760 --> 01:15:24,519
Speaker 7: So I've always had really fantastic mentors, and building that

1474
01:15:24,560 --> 01:15:28,000
Speaker 7: community around you is really really important. I'm really lucky

1475
01:15:28,080 --> 01:15:31,640
Speaker 7: to have a fantastically supportive husband who's also a neuroscientist.

1476
01:15:32,240 --> 01:15:34,000
Speaker 1: So, oh my gosh, two of you.

1477
01:15:34,960 --> 01:15:37,759
Speaker 3: Yep, I have actually three D prints of our brains

1478
01:15:37,880 --> 01:15:38,360
Speaker 3: just over there.

1479
01:15:39,960 --> 01:15:41,560
Speaker 1: That is amazing.

1480
01:15:42,960 --> 01:15:47,160
Speaker 2: Oh please do your pillow talk would be so funny, intellectual.

1481
01:15:47,600 --> 01:15:48,040
Speaker 4: Here we are.

1482
01:15:50,280 --> 01:15:51,799
Speaker 3: Mine's pink and as is blues.

1483
01:15:52,080 --> 01:15:53,400
Speaker 1: That is amazing.

1484
01:15:54,240 --> 01:15:56,120
Speaker 2: Oh my god, how did you get that done?

1485
01:15:57,680 --> 01:16:00,120
Speaker 7: I scanned both of our brains and then sent them

1486
01:16:00,160 --> 01:16:01,040
Speaker 7: off the free DPrinting.

1487
01:16:02,040 --> 01:16:04,320
Speaker 1: Of course you did, of course you did.

1488
01:16:06,439 --> 01:16:07,040
Speaker 2: Oh my gosh.

1489
01:16:07,160 --> 01:16:09,759
Speaker 1: As I get older, it's funny how like at school,

1490
01:16:09,920 --> 01:16:13,640
Speaker 1: there was such a not a stigma, but just a

1491
01:16:13,720 --> 01:16:16,880
Speaker 1: bit of a social attachment to being a nerd. And

1492
01:16:16,960 --> 01:16:19,240
Speaker 1: I've always been like super nerdy, but there's always been

1493
01:16:19,240 --> 01:16:21,200
Speaker 1: that side of me that was like trying to be

1494
01:16:21,280 --> 01:16:23,479
Speaker 1: a jock, and I kind of suppressed the nerdy side.

1495
01:16:23,520 --> 01:16:25,320
Speaker 1: But the older I get them, I'm like, being a nerdy,

1496
01:16:25,439 --> 01:16:27,920
Speaker 1: so frickin cool. You have an actual three D print

1497
01:16:27,960 --> 01:16:31,160
Speaker 1: of your brain, Like that is so amazing.

1498
01:16:31,800 --> 01:16:33,320
Speaker 3: I know that I'm totally the same.

1499
01:16:33,360 --> 01:16:36,720
Speaker 7: At school, I loved science and things, but you I

1500
01:16:36,800 --> 01:16:39,479
Speaker 7: think in an Australia and New Zealand society we kind

1501
01:16:39,520 --> 01:16:42,360
Speaker 7: of try and offseat it by doing to make.

1502
01:16:42,320 --> 01:16:46,880
Speaker 1: Us cool totally. It's like the compromise. It's like, yes,

1503
01:16:46,960 --> 01:16:48,840
Speaker 1: I'm good at you know, in the classroom, but I

1504
01:16:48,920 --> 01:16:51,360
Speaker 1: can totally kick a football around, so I'm fine, exactly,

1505
01:16:51,560 --> 01:16:54,240
Speaker 1: you can accept me into your exactly.

1506
01:16:55,120 --> 01:16:56,920
Speaker 7: There's something to be aware of in something we need

1507
01:16:56,960 --> 01:16:59,479
Speaker 7: to address and that people maybe who are less interested

1508
01:16:59,520 --> 01:17:02,040
Speaker 7: in sports maybe find it a little bit harder to

1509
01:17:02,200 --> 01:17:06,760
Speaker 7: express their wholesome nerdiness, and that should be really celebrated

1510
01:17:06,800 --> 01:17:09,560
Speaker 7: and appreciated when we see how important science it is.

1511
01:17:09,600 --> 01:17:11,960
Speaker 7: I think that's one of the wonderful things that we

1512
01:17:12,120 --> 01:17:14,320
Speaker 7: have to take out of all of this craziness is

1513
01:17:14,400 --> 01:17:16,800
Speaker 7: that science is really important.

1514
01:17:16,360 --> 01:17:18,200
Speaker 3: And it can do amazing things for us.

1515
01:17:18,360 --> 01:17:18,559
Speaker 4: Yeah.

1516
01:17:18,640 --> 01:17:22,280
Speaker 1: Absolutely, And I think the rise of podcasts and YouTube

1517
01:17:22,360 --> 01:17:25,680
Speaker 1: channels and digital media to actually spread the word of

1518
01:17:26,000 --> 01:17:29,080
Speaker 1: what people are doing, like that visibility of what science

1519
01:17:29,160 --> 01:17:31,320
Speaker 1: is actually related to in our lives has been so

1520
01:17:31,520 --> 01:17:34,240
Speaker 1: good because you didn't used to know these things. You

1521
01:17:34,320 --> 01:17:37,719
Speaker 1: couldn't hear from people who had forged pathways, and therefore

1522
01:17:37,760 --> 01:17:41,200
Speaker 1: you couldn't visualize a career or even visualize the impact

1523
01:17:41,240 --> 01:17:43,080
Speaker 1: that other scientists are having on your life. And I

1524
01:17:43,160 --> 01:17:46,040
Speaker 1: think even from these conversations, it's in the been five

1525
01:17:46,080 --> 01:17:49,320
Speaker 1: and it's already changed my perception of how important it

1526
01:17:49,479 --> 01:17:52,559
Speaker 1: is to get younger people into these industries and get

1527
01:17:52,560 --> 01:17:56,000
Speaker 1: them excited about them rather than you know, I think

1528
01:17:56,080 --> 01:17:58,400
Speaker 1: I didn't even know what neuroscience was when I was

1529
01:17:58,439 --> 01:17:59,960
Speaker 1: finishing school exactly alone.

1530
01:18:00,479 --> 01:18:03,679
Speaker 3: It's not really a school topic. But it's really cool.

1531
01:18:04,160 --> 01:18:06,000
Speaker 3: I'm holding my brain, it's really cool.

1532
01:18:06,800 --> 01:18:12,240
Speaker 1: It's so cool. Do you have a favorite motivational quote

1533
01:18:12,360 --> 01:18:14,960
Speaker 1: or mantra that's kind of guided you through your journey

1534
01:18:15,000 --> 01:18:15,920
Speaker 1: that you'd like to pass on?

1535
01:18:16,240 --> 01:18:19,519
Speaker 7: So not a motivational quote, but I heard this just

1536
01:18:19,640 --> 01:18:23,799
Speaker 7: recently on the radio by a physiotherapist, doctor Tanya Clifton

1537
01:18:23,880 --> 01:18:26,000
Speaker 7: Smith in New Zealand, just recently, and I thought it

1538
01:18:26,320 --> 01:18:29,800
Speaker 7: just beautifully encapsulated what I'm trying to do, and it

1539
01:18:30,040 --> 01:18:34,440
Speaker 7: is if in doubt, breathe out. And it's really important

1540
01:18:34,520 --> 01:18:37,759
Speaker 7: because it's sort of tied up exactly with the research

1541
01:18:37,880 --> 01:18:40,920
Speaker 7: that I do that when we get worried, we can

1542
01:18:41,040 --> 01:18:45,439
Speaker 7: basically just inadvertently hold our breath and that can cause

1543
01:18:45,680 --> 01:18:47,880
Speaker 7: all of these things and cause us to feel so

1544
01:18:48,120 --> 01:18:51,439
Speaker 7: much worse and really thinking about it earlier, noticing it

1545
01:18:52,200 --> 01:18:55,840
Speaker 7: and really just thinking okay out slowly because we often

1546
01:18:55,880 --> 01:18:57,840
Speaker 7: hold our breath at the top of our breath, so

1547
01:18:58,040 --> 01:19:01,839
Speaker 7: just thinking if in doubt, breathe and that really centers

1548
01:19:01,960 --> 01:19:05,040
Speaker 7: us and helps our brain to relax our body. So

1549
01:19:05,200 --> 01:19:08,439
Speaker 7: I just thought that beautifully captured what I was trying

1550
01:19:08,479 --> 01:19:08,640
Speaker 7: to do.

1551
01:19:09,080 --> 01:19:10,559
Speaker 2: Oh that's such a good one.

1552
01:19:11,040 --> 01:19:14,880
Speaker 1: And it's so surprising how often you'll find yourself in

1553
01:19:14,960 --> 01:19:17,600
Speaker 1: the middle of not breathing and be like, oh wow, like,

1554
01:19:17,760 --> 01:19:19,880
Speaker 1: how are any of my organs supposed to function right

1555
01:19:19,920 --> 01:19:20,879
Speaker 1: now without oxygen?

1556
01:19:21,560 --> 01:19:22,000
Speaker 6: Exactly?

1557
01:19:22,240 --> 01:19:24,920
Speaker 7: We actually do it when we answer emails too. Let's

1558
01:19:24,960 --> 01:19:28,000
Speaker 7: hold our breathing it's called email opre we just stop.

1559
01:19:29,080 --> 01:19:29,639
Speaker 3: That's a thing.

1560
01:19:30,000 --> 01:19:30,200
Speaker 6: Yeah.

1561
01:19:30,479 --> 01:19:32,040
Speaker 2: I think it's like deep in concentration.

1562
01:19:32,400 --> 01:19:36,880
Speaker 3: Yeah, exactly, exactly, And no matter it's amazing.

1563
01:19:37,000 --> 01:19:39,760
Speaker 7: No matter what you ask someone to do, we're really

1564
01:19:39,800 --> 01:19:42,360
Speaker 7: good at synchronizing our breathing with it. So if you

1565
01:19:42,360 --> 01:19:44,600
Speaker 7: ask someone to tap their fingers, lots of people end

1566
01:19:44,680 --> 01:19:48,760
Speaker 7: up going. So we do it with everything we do.

1567
01:19:48,920 --> 01:19:51,160
Speaker 7: We tend to synchronize. So just being aware that sometimes

1568
01:19:51,240 --> 01:19:53,479
Speaker 7: that can maybe make us feel not so good, or

1569
01:19:53,640 --> 01:19:54,960
Speaker 7: if we wonder why we're.

1570
01:19:54,840 --> 01:19:56,400
Speaker 3: Just feeling a little bit off or a little bit

1571
01:19:56,479 --> 01:19:57,240
Speaker 3: light headed, or we.

1572
01:19:57,280 --> 01:20:00,519
Speaker 7: Can't quite grasp that thought, it's just okay, breathe out

1573
01:20:00,560 --> 01:20:01,559
Speaker 7: and we'll see if that helps.

1574
01:20:01,800 --> 01:20:04,639
Speaker 1: This is the weirdest admission I've ever made. But I've noticed,

1575
01:20:04,720 --> 01:20:07,479
Speaker 1: like I'm a mildly OCD, Like there are certain things

1576
01:20:07,520 --> 01:20:10,800
Speaker 1: that I really like. I really prefer the volume to

1577
01:20:10,840 --> 01:20:12,000
Speaker 1: be on an even number.

1578
01:20:14,640 --> 01:20:19,600
Speaker 3: Right, it should be right otherwise, Yes, but.

1579
01:20:19,680 --> 01:20:21,800
Speaker 1: I've noticed that when I'm running, so I'm training for

1580
01:20:21,880 --> 01:20:24,919
Speaker 1: a half marathon, and getting your breathing right is so important.

1581
01:20:24,960 --> 01:20:27,640
Speaker 1: But because I wanted my in breast and my outbreaths

1582
01:20:27,680 --> 01:20:31,000
Speaker 1: to be four steps, because that's even I would force

1583
01:20:31,080 --> 01:20:33,920
Speaker 1: my breathing into the four, like into the four and four,

1584
01:20:34,040 --> 01:20:36,600
Speaker 1: which didn't work for my body, and I had to

1585
01:20:36,680 --> 01:20:38,439
Speaker 1: adjust it. And I was like, okay, I'll do two

1586
01:20:38,520 --> 01:20:40,760
Speaker 1: and two, and then that wasn't enough, and then so

1587
01:20:40,800 --> 01:20:42,559
Speaker 1: I was like, damn it, it's got to be three

1588
01:20:42,600 --> 01:20:44,360
Speaker 1: and three and I hate threes.

1589
01:20:45,920 --> 01:20:47,760
Speaker 3: I have one piece of advice for you on this.

1590
01:20:48,800 --> 01:20:53,920
Speaker 7: Taylor Swift is excellent to run to right, really great

1591
01:20:54,000 --> 01:20:59,280
Speaker 7: beat for your breathing, and it's just yeah, lots of

1592
01:20:59,360 --> 01:21:00,960
Speaker 7: training to te swift right.

1593
01:21:01,160 --> 01:21:05,200
Speaker 1: Oh my god, you've changed my life. Might get to you, yeah,

1594
01:21:06,360 --> 01:21:11,439
Speaker 1: as well as all the researchers anxiety. But whatever. Final question,

1595
01:21:11,800 --> 01:21:16,360
Speaker 1: do you have a recommendation of a film or a

1596
01:21:16,520 --> 01:21:20,040
Speaker 1: book or a show? And I think importantly, something that

1597
01:21:20,200 --> 01:21:22,600
Speaker 1: maybe isn't related to your career, that gives you the

1598
01:21:22,800 --> 01:21:25,600
Speaker 1: distance and the break to kind of stay fresh. Just

1599
01:21:25,640 --> 01:21:28,520
Speaker 1: something that's made you really happy, that's made you excited.

1600
01:21:28,760 --> 01:21:32,800
Speaker 7: Yep, definitely. I love baking. It is just one of

1601
01:21:32,840 --> 01:21:35,800
Speaker 7: the things that makes me happy. I love making kee

1602
01:21:35,880 --> 01:21:38,360
Speaker 7: we baking, especially because it's so novel.

1603
01:21:38,439 --> 01:21:40,200
Speaker 3: And when I was in Oxford and I lived in

1604
01:21:40,240 --> 01:21:40,840
Speaker 3: Switzerland for.

1605
01:21:40,840 --> 01:21:42,800
Speaker 1: A while, and they were like, what is this? And

1606
01:21:42,960 --> 01:21:45,040
Speaker 1: so it makes me so happy.

1607
01:21:45,800 --> 01:21:48,400
Speaker 7: And so shows like The Great British Bakeoff, or I

1608
01:21:48,439 --> 01:21:50,960
Speaker 7: think in Australia you have the Great Australian Breakoff and

1609
01:21:51,000 --> 01:21:53,080
Speaker 7: they're just back for this next season, and I just

1610
01:21:53,200 --> 01:21:57,440
Speaker 7: find them so relaxing and creative and wonderful.

1611
01:21:57,760 --> 01:22:01,160
Speaker 3: And this real celebration of sharing.

1612
01:22:00,960 --> 01:22:04,360
Speaker 7: Something nice between people and trying to create something just

1613
01:22:04,439 --> 01:22:05,400
Speaker 7: for the sake of eating it.

1614
01:22:05,680 --> 01:22:06,719
Speaker 3: I just think it's lovely.

1615
01:22:07,160 --> 01:22:07,400
Speaker 2: Yeah.

1616
01:22:08,080 --> 01:22:10,360
Speaker 1: I love, you know, encouraging people to do things that

1617
01:22:10,479 --> 01:22:14,120
Speaker 1: aren't necessarily productive, like puzzles. You know, you spend all

1618
01:22:14,160 --> 01:22:15,600
Speaker 1: this time on the puzzle and then you break it

1619
01:22:15,640 --> 01:22:17,160
Speaker 1: at the end. The same with cooking. It's like you

1620
01:22:17,200 --> 01:22:18,600
Speaker 1: spend all this time making this thing and then you

1621
01:22:18,720 --> 01:22:20,639
Speaker 1: just eat it at the end. But it's still fun.

1622
01:22:21,800 --> 01:22:24,519
Speaker 7: I think for me as well, baking is such about sharing.

1623
01:22:25,000 --> 01:22:27,439
Speaker 7: It's about enjoying it with other people and that social

1624
01:22:27,479 --> 01:22:30,120
Speaker 7: connection that you have. And so we actually had to

1625
01:22:30,240 --> 01:22:33,640
Speaker 7: buy a chest freezer for me to put all of

1626
01:22:33,760 --> 01:22:42,320
Speaker 7: my bases committmentally happy to like, I make slice, so

1627
01:22:42,600 --> 01:22:44,479
Speaker 7: it makes really happy to like cut it into like

1628
01:22:44,640 --> 01:22:47,599
Speaker 7: nice pieces and they're all even and then my poor

1629
01:22:47,640 --> 01:22:49,599
Speaker 7: husband has to eat all the scraps and the scratty

1630
01:22:49,680 --> 01:22:50,840
Speaker 7: corners that don't look nice.

1631
01:22:51,120 --> 01:22:53,080
Speaker 1: Yeah, well, obviously there's got to be an even number,

1632
01:22:53,160 --> 01:22:55,599
Speaker 1: and it's going to be perfectly symmetrical.

1633
01:22:55,120 --> 01:22:57,639
Speaker 7: And exactly exactly. And the ones that are not fit

1634
01:22:57,760 --> 01:23:01,320
Speaker 7: for leaving the house here, it's happy to scoop up.

1635
01:23:02,040 --> 01:23:03,120
Speaker 1: Was almost no one sees them.

1636
01:23:03,200 --> 01:23:06,120
Speaker 3: Exactly exactly did they go into his tummy?

1637
01:23:08,360 --> 01:23:11,400
Speaker 1: Well, thank you so much of very very big congratulations

1638
01:23:11,439 --> 01:23:14,320
Speaker 1: on the fellowship as well. I did mean to ask, actually,

1639
01:23:14,439 --> 01:23:17,160
Speaker 1: is there anything in particular in your research that this

1640
01:23:17,320 --> 01:23:19,600
Speaker 1: wonderful fellowship from Loreal has allowed you to do that

1641
01:23:19,680 --> 01:23:21,120
Speaker 1: you might not otherwise have been able to do.

1642
01:23:21,360 --> 01:23:25,200
Speaker 7: What I'm using this for is to buy equipment, and

1643
01:23:25,360 --> 01:23:28,960
Speaker 7: that's really helpful because not many funding bodies want to

1644
01:23:28,960 --> 01:23:32,200
Speaker 7: buy equipment because then you have the ownership problems and

1645
01:23:32,760 --> 01:23:33,599
Speaker 7: all of that as well.

1646
01:23:33,680 --> 01:23:37,000
Speaker 3: And so it's just such a wonderful release to be

1647
01:23:37,040 --> 01:23:38,720
Speaker 3: able to go, no, I need that, and I can

1648
01:23:38,800 --> 01:23:40,439
Speaker 3: buy that, and it's really helpful.

1649
01:23:41,479 --> 01:23:44,439
Speaker 7: So now my students can run multiple tasks at once,

1650
01:23:44,520 --> 01:23:46,760
Speaker 7: and it just makes everyone's life so much easier. So

1651
01:23:47,160 --> 01:23:49,600
Speaker 7: I'm incredibly grateful to just have that freedom and be

1652
01:23:49,680 --> 01:23:52,320
Speaker 7: able to say what do we actually need and we

1653
01:23:52,439 --> 01:23:53,160
Speaker 7: can spend on that.

1654
01:23:53,600 --> 01:23:54,679
Speaker 2: Oh how exciting.

1655
01:23:54,800 --> 01:23:58,320
Speaker 1: Well, congratulations, thank you so much for joining, and thank

1656
01:23:58,360 --> 01:23:59,840
Speaker 1: you so much for the incredible.

1657
01:23:59,400 --> 01:23:59,960
Speaker 2: Work that you're doing.

1658
01:24:00,280 --> 01:24:01,760
Speaker 3: You're right, thanks and all the best.

1659
01:24:02,120 --> 01:24:05,160
Speaker 1: Okay, well, I'm pretty speechless still after hearing from these

1660
01:24:05,240 --> 01:24:08,840
Speaker 1: five outstanding women over the past two episodes. I really

1661
01:24:08,880 --> 01:24:11,000
Speaker 1: think even if you have no interest in ever working

1662
01:24:11,080 --> 01:24:13,360
Speaker 1: in science, their work and the way it could change

1663
01:24:13,400 --> 01:24:15,439
Speaker 1: the world for the better in so many different ways

1664
01:24:15,600 --> 01:24:19,559
Speaker 1: is just incredibly interesting and so inspiring. I truly hope

1665
01:24:19,600 --> 01:24:22,920
Speaker 1: this series does encourage and inspire some future leading scientists

1666
01:24:23,240 --> 01:24:26,719
Speaker 1: to push on with their yay in stem. As always,

1667
01:24:26,720 --> 01:24:29,200
Speaker 1: I'd love to hear what you think or anything you've learned.

1668
01:24:29,280 --> 01:24:31,400
Speaker 1: It's always so great to know what the neighborhood thinks

1669
01:24:31,439 --> 01:24:34,120
Speaker 1: of anything new or a bit different, like a mini series.

1670
01:24:34,120 --> 01:24:36,640
Speaker 1: I hope you guys have enjoyed these last two. They

1671
01:24:36,720 --> 01:24:38,200
Speaker 1: came a little bit hard and fast at the end

1672
01:24:38,200 --> 01:24:39,560
Speaker 1: of the year, but I think we should do a

1673
01:24:39,600 --> 01:24:41,240
Speaker 1: couple more of these. So if there's a theme you're

1674
01:24:41,280 --> 01:24:43,000
Speaker 1: interested in or a group of people you want to

1675
01:24:43,040 --> 01:24:46,320
Speaker 1: hear from, we can definitely look at that in twenty

1676
01:24:46,520 --> 01:24:48,760
Speaker 1: twenty two. Oh my gosh, gross, that's the first time

1677
01:24:48,760 --> 01:24:51,920
Speaker 1: I've said that word. And if you have any specific

1678
01:24:52,080 --> 01:24:53,840
Speaker 1: questions you'd like me to pass on to any of

1679
01:24:53,920 --> 01:24:56,200
Speaker 1: our guests from this series, please flick me a DM

1680
01:24:56,360 --> 01:24:57,880
Speaker 1: or email and I can reach out to them and

1681
01:24:57,960 --> 01:25:00,040
Speaker 1: make that happen. I'm sure they would be so de

1682
01:25:00,080 --> 01:25:02,960
Speaker 1: lighted to speak to any aspiring young scientists out there.

1683
01:25:03,560 --> 01:25:06,160
Speaker 1: Thank you again to the wonderful team at Laurel also

1684
01:25:06,320 --> 01:25:09,040
Speaker 1: for their incredible for Women in Science fellowship and the

1685
01:25:09,080 --> 01:25:12,599
Speaker 1: way it enables this kind of groundbreaking and innovative work

1686
01:25:13,000 --> 01:25:15,200
Speaker 1: that will benefit so many of us or our loved

1687
01:25:15,240 --> 01:25:18,439
Speaker 1: ones in time. We've got just one more episode left

1688
01:25:18,520 --> 01:25:21,760
Speaker 1: for this year. Oh that has flown by, and it's

1689
01:25:21,880 --> 01:25:23,680
Speaker 1: such a good ease. So I will see you all

1690
01:25:23,760 --> 01:25:26,080
Speaker 1: next week and hope you're seizing your yay