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Speaker 1: Lieutenant Kevin jen just twenty six years old. Just last week,

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Speaker 1: he announced he was going to get married, got down

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Speaker 1: on one knee and proposed to the love of his life.

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Speaker 1: But instead of planning a wedding, now his beloved sweetheart

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Speaker 1: and family are planning a funeral and I want to

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Speaker 1: know why breaking knees. Right now, we are learning that

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Speaker 1: police have a POI person of interest. Take a listen

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Speaker 1: to the new Haven Police Chief. The new Haven Police

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Speaker 1: departments Hamaside Unit is looking for mister King Swan pon

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Speaker 1: date of birth of four, sixteen, nineteen ninety one. His

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Speaker 1: name is spelled q I n x u a N

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Speaker 1: last named pa N again data birth for sixteen nineteen

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Speaker 1: ninety one. Mister Pong was last seen at the Best

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Speaker 1: Western Hotel to a one Washington Avenue in North Haven.

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Speaker 1: His last known address is one thirty one correction one

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Speaker 1: ninety three Clifton Street in Malden, Massachusetts. We know that

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Speaker 1: mister Pong is a graduate of MIT and has an

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Speaker 1: affiliation with that university. I am asking that the public

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Speaker 1: knows that mister Pong should be considered armed and dangerous

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Speaker 1: and that he that extreme question should be used. If

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Speaker 1: you come in contact with this individual. What happened? Take

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Speaker 1: a listen to this. I heard a gun shot, a

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Speaker 1: woman's scream, several shots after that. The neighbor recalls the

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Speaker 1: harrowing details of what occurred at the corner of Lawrence

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Speaker 1: and Nicole Street at eight thirty Saturday night. Waited about

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Speaker 1: a minute, came out and saw the bodyline there. The

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Speaker 1: decease has been identify as twenty six year old Kevin

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Speaker 1: Jeong of West Haven, Yo University confirms he was a

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Speaker 1: graduate student in their School of Environment. He was a

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Speaker 1: member of the class of twenty twenty two. Multiple witnesses

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Speaker 1: confirmed hearing between three to six shots. I'm still shaking

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Speaker 1: up about it. All night, we were all disbelief, the

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Speaker 1: entire Yale community and many groups and organizations. Jong was

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Speaker 1: a part of her carrying that disbelief as well. Hey guys,

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Speaker 1: you were just hearing our friends at Fox sixty one.

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Speaker 1: This young man, newly engaged Lieutenant Kevin Jien had reached

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Speaker 1: the level of a lieutenant within the army. He drove

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Speaker 1: a tank. He also in the reserves. He also volunteered

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Speaker 1: religiously at his church, Trinity Baptist, about a mile from

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Speaker 1: where he was murdered. They recently engaged, as in about

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Speaker 1: six to seven days engaged. Young man had majored at

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Speaker 1: Washington University and environmental studies, and then it was just

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Speaker 1: a few short months away from getting his master's degree

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Speaker 1: at Yale University the IVY leagues. I looked it up online.

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Speaker 1: It's about sixty five grand all in for one year

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Speaker 1: at Yale in the master's program. His mother had to

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Speaker 1: give up her life and the household expenses of her

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Speaker 1: home in Seattle and moved there. They ended up living

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Speaker 1: together to save money so he could get his master's degree.

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Speaker 1: You think I'm going to sign up for sixty five

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Speaker 1: grand so my kid can get shot down in the road. No,

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Speaker 1: And what is Yale saying, Oh, We're sorry? What about

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Speaker 1: the six murders in the college town in six weeks.

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Speaker 1: Let's get into it, joining me an all star panel

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Speaker 1: to break it down and put it back together again.

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Speaker 1: Wendy Patrick, California prosecutor, author of Red Flags and host

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Speaker 1: of Today with Doctor Wendy on k c b Q.

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Speaker 1: You can find her at Wendy Patrick PhD dot com.

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Speaker 1: Doctor Daniel Bober, who studied and worked at Yale, Chief Psychiatry,

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Speaker 1: Memorial Regional Healthcare Assistant professor at Yale, and you can

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Speaker 1: find him at doctor Daniel Bober on Twitter bo b r.

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Speaker 1: Robert Crispin with a C. Former law enforcement now PI

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Speaker 1: with Crispin's Special Investigations dot com. The medical examiner for

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Speaker 1: the entire state of Florida. Doctor Tim Gallagher you can

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Speaker 1: find him at PATHCAREMD dot com. But straight now to

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Speaker 1: Crime Online dot com, investigative reporter, also with Lead Stories

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Speaker 1: dot com. Alexis Terres Chuck, Alexis, I don't get it.

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Speaker 1: This guy minding his own business. Eight thirty on a

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Speaker 1: Saturday night. I believe he's about a mile from his church,

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Speaker 1: a few minutes away from his new fiance's home. I mean,

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Speaker 1: they've been together over a year, but they were just

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Speaker 1: nearly engaged, and all of a sudden he turns up dead.

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Speaker 1: As I understand, his car had damned, new damage to

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Speaker 1: the back of the car like it had been REI ended.

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Speaker 1: He was shot multiple times and found lyne outside the vehicle.

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Speaker 1: Tell me something I don't know, Alexis well. I don't

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Speaker 1: know if everybody across the country knows, but there was

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Speaker 1: a huge snowstorm in the northeast. So this was not

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Speaker 1: a road. This whole area was covered with snow. Eight

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Speaker 1: thirty on Saturday night. It wasn't like the road was clear.

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Speaker 1: It wasn't like he could have been speeding away or anything.

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Speaker 1: He's driving slowly through the snow and he's there at

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Speaker 1: a corner and the car had damage. It looks as

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Speaker 1: if someone has rear ended him, fresh damage. And as

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Speaker 1: you said, yes, he's just got engaged, got down on

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Speaker 1: one knee, also in the snow, proposed to his girlfriend,

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Speaker 1: give her a rank. He was gushing about how happy

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Speaker 1: he was. He posted all over Facebook. She said, yes,

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Speaker 1: I love her. They met through church and then neighbors

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Speaker 1: say they heard shots. First they heard two shots bring out,

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Speaker 1: and then there was a pause, and then they hear

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Speaker 1: five more in rapid successions. And he's outside of the car.

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Speaker 1: He's not inside. Something happened to make him get out

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Speaker 1: of this car, and these people shot him in cold blood.

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Speaker 1: You are bringing to mind a lot of lines of questioning,

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Speaker 1: avenues of interrogation. I want to deal with the snow,

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Speaker 1: and I want to deal with the pause in the

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Speaker 1: seven shots, two shots, paws and five shots. That is

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Speaker 1: significant for many many reasons, But I want to first

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Speaker 1: deal with the snow. Let me go straight out to

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Speaker 1: you too. Robert Crispin PI, former comp now at Crispin

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Speaker 1: Special Investigations dot com. We know that the crime rate

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Speaker 1: goes down and the colder months and goes up when

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Speaker 1: it gets warm and everybody is more out and about

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Speaker 1: seemingly we go down even more during COVID. But here

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Speaker 1: you've got this town of Behaving, Connecticut. It's the college town,

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Speaker 1: but it's fairly depressed. There's about one hundred and thirty

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Speaker 1: thousand population, and a few years ago a study was

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Speaker 1: conducted one in four people here live in poverty in

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Speaker 1: the shadow of Yale University. But the snow, the deep snow,

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Speaker 1: Alexis Terreschac just reported about that actually should make a

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Speaker 1: difference in this case because it certainly lowers statistically the

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Speaker 1: likelihood of violent crime jump in well, I mean maybe

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Speaker 1: to a point, but until you upset somebody or you

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Speaker 1: piss somebody off, all that goes out the window. Because

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Speaker 1: we've got seven shots. We've got two shots followed by

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Speaker 1: the rest of them. They wanted him dead for whatever reason.

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Speaker 1: But I will tell you about the snow. I love

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Speaker 1: snow when it comes to a crime scene, because the

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Speaker 1: snow as soon as those officers arrive, is going to

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Speaker 1: tell us so much about that crime scene. It's going

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Speaker 1: to give us tire tracks of the offending vehicle. It's

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Speaker 1: going to give us footprints from the shooter. It's going

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Speaker 1: to give us a direction of travel that somebody left

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Speaker 1: in with the car, which is going to allow me

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Speaker 1: or the investigators to go back and start pulling video

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Speaker 1: cameras and backtracking from everybody's house to see where this

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Speaker 1: car came from. Maybe it came out of a drive

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Speaker 1: right down the street. You just don't know. But snow.

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Speaker 1: I love it the best evidence out there. I agree

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Speaker 1: with you regarding evidence, Member and Jamine. A big deal

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Speaker 1: was made that there were no tracks in the snow

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Speaker 1: outside the base window where it is believed the perpetrator

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Speaker 1: may have entered. Snow. Yes, I was thinking along the

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Speaker 1: lines of if this obviously not a carjacking because they

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Speaker 1: damaged the car and they left the car. But as

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Speaker 1: far as a rear end one, as Alexei's terres Chuck

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Speaker 1: pointed out, there were no high speed road rage incidents.

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Speaker 1: It was too snow. There could be there could be

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Speaker 1: so much more to this that that crash could have

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Speaker 1: been a roost exactly roos to lure him out of

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Speaker 1: the car. Of course, you know this is this takes

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Speaker 1: so much more to look into. You know, he just

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Speaker 1: got engaged, He just went public with his engagement. Was

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Speaker 1: there a crazy jealous X level? What about that, Doctor

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Speaker 1: Daniel Bober? What about the theory? Does this have something

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Speaker 1: to do with the engagement announcement the week before? Jump in? Yeah,

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Speaker 1: the timing is very curious, Nancy, and it's definitely something

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Speaker 1: that I would consider based on when the engagement announcement

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Speaker 1: was made. It doesn't sound like just a completely random event.

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Speaker 1: Crime Stories with Nancy Grace. Guys, we were talking about

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Speaker 1: the death of a twenty six year old young man

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Speaker 1: who had devoted his life to doing something good. His

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Speaker 1: name Lieutenant Kevin jen and he not only had served

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Speaker 1: his country as a tank operator in the Army, he

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Speaker 1: was in the reserves and he was working to find

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Speaker 1: a way to remove mercury from waterways and how to

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Speaker 1: help our world in our environment. He not only worked

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Speaker 1: at a food shelter, he cooked the food and served

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Speaker 1: it to the homeless. A guy totally devoted to his

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Speaker 1: faith a Christianity. He thought he had found his soul

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Speaker 1: mate and she thought the same. Their relationship now cut

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Speaker 1: short due to violence. What happened to Kevin? Take a

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Speaker 1: listen to our friends At Fox sixty one, Police say

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Speaker 1: they received multiple nine reporting gunfire and a person shot

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Speaker 1: in the area of Nash Street and Lauren Street. The

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Speaker 1: victim twenty six year old Kevin Jiang. He was shot

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Speaker 1: multiple times and died on scene. According to police, died

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Speaker 1: on the scene, shot multiple times. A pause in the shooting.

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Speaker 1: As I was discussing earlier with Robert Crispins at Crispins

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Speaker 1: Special Investigations dot Com. While there may not have been

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Speaker 1: a high speed road rage incident with the snow, that

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Speaker 1: could have easily contributed to a rear endure and everything

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Speaker 1: go sideways, what about that theory? Wendy Patrick, California Prosecutor. Yeah,

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Speaker 1: you know, that's one of the theories they're going to

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Speaker 1: be exploring, because what the gunshots tell us, it's the

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Speaker 1: sound of strategy. Two shots followed by five. There's almost

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Speaker 1: an element of planning that you wouldn't necessarily or at

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Speaker 1: all expecting a road rage incident. And I love what

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Speaker 1: our friend Robert Crispin explains, if somebody had intentionally set

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Speaker 1: out to commit this killing, they might think that snowstorm

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Speaker 1: would provide some cover without knowing it actually preserves evidence.

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Speaker 1: So if we've listened to the way those gunshots played out,

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Speaker 1: and we think about it as strategy as opposed to

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Speaker 1: road rage, that may give us some lea eats as

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Speaker 1: to who to look at next and how to begin

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Speaker 1: this investigation. I want to go to doctor Tim Gallagher,

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Speaker 1: a medical exam er, State of Florida. Doctor Gallagher, do

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Speaker 1: you recall the Wayne Williams serial killing case. I do.

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Speaker 1: I believe he was a serial killer from the DC

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Speaker 1: area Attata and in that case, which was tried in

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Speaker 1: the office where I prosecuted, So the first time ever

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Speaker 1: that the use of fiber evidence was allowed in front

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Speaker 1: of a jury. Fiber evidence off many of the victim's

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Speaker 1: body young men matched exactly to fiber in Wayne Williams's

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Speaker 1: car or at his home, like shag carpet type fiber.

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Speaker 1: When you look under a microscope you can see that

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Speaker 1: it looks identical and from that fiber you can determine

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Speaker 1: what type of carpet. Of course, the color you may

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Speaker 1: get blood on it. But from just that fiber, you

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Speaker 1: can find the make, where it's manufactured, where it's sold,

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Speaker 1: and once he yet to where it's sold, you can

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Speaker 1: find who bought it, what kind of car it goes

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Speaker 1: into it it's out of the trunk or the bottom

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Speaker 1: the floor of your car. In this case, I mean,

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Speaker 1: have you ever had a chance to look at five

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Speaker 1: under microscope? Dodge Gallagher? Oh, we do here all the

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Speaker 1: time in OURSI lad, I'm leading up to the car.

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Speaker 1: Witnesses state to correct me if I'm rolling, Alexis tres Chuck.

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Speaker 1: Then they saw quote a shiny new black car playing

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Speaker 1: the scene? Yeah, shiny and black? How did they know

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Speaker 1: it was new? Did have a sticker? Did have one

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Speaker 1: of those h car lot tags on the back? Shiny

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Speaker 1: new black car flowing the scene? Did you? Did you

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Speaker 1: get that too? Alexis? Yeah? And also I find a

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Speaker 1: description of shiny. First of all, it's a thirty at night,

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Speaker 1: so it's dark, right, I've been at there are streetlights,

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Speaker 1: but shiny also again in this like I know it

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Speaker 1: wasn't snowing at that exact second, but it had been

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Speaker 1: a snowstorm. Like, why do these people have such a

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Speaker 1: fancy car? All of a sudden, in the middle of

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Speaker 1: a snowstorm, shiny new black car fleeing the same If

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Speaker 1: there was a rear ender and this was a result

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Speaker 1: of road rage or an accident, or even alluring technique

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Speaker 1: to get Kevin out of the car, there is gonna

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Speaker 1: be paint, black paint on the back of Kevin's car.

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Speaker 1: What about that, doctor Gallagher? And from that paint we

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Speaker 1: can actually determine what kind of car it was, what

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Speaker 1: manufacturer uses this particular compound ingredients in the paint onto

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Speaker 1: what car, and what are the local dealerships, and who

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Speaker 1: bought those cars in the last year. If it's shiny,

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Speaker 1: new and black, bam, well it's true. You know, we

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Speaker 1: could even do better than that. A lot of the times,

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Speaker 1: that will alert the repair body shops in the area.

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Speaker 1: If somebody had a new car, they'd probably want to

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Speaker 1: fix it, you know, and we would alert the body

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Speaker 1: shop owners that if this car presents at your office

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Speaker 1: or at your establishment, that we would like a phone call.

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Speaker 1: And cars can change hands. New cars can change hands.

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Speaker 1: Often it could be a rental car. Maybe that's why

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Speaker 1: it looks new, you know. But somewhere, somewhere alone the

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Speaker 1: line somebody's gonna want to fix, you know, a car

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Speaker 1: with front end damage and said or burn it. Do

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Speaker 1: you remember in the DC mansion murders where a whole

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Speaker 1: family I believe with the Savopolis family was killed and

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Speaker 1: the car had been stolen. I think it was a

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Speaker 1: Porsche And it was no time after that that Porsche

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Speaker 1: was found on fire in a different neighborhood. So that's

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Speaker 1: serial number. We can give the Vin number from a burn.

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Speaker 1: That's even better. If we do find a car, somebody's

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Speaker 1: going to get unload that car. They're gonna fix it,

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Speaker 1: sell it or burn it or get rid of it,

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Speaker 1: put it into a body of water, anything to disconnect

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Speaker 1: them from Kevin's car. So straight out to you, to

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Speaker 1: Robert Crispin, here's the deal. There are entire units within

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Speaker 1: police forces, especially in metropolitan areas, that do nothing but

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Speaker 1: cars because it's so overwhelming. The carfs f by receiving

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Speaker 1: the f by taking chop shops the works. Every year,

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Speaker 1: almost every year, designers change something. It may be subtle

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Speaker 1: on a car. I mean, come on, look at the bug,

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Speaker 1: the VW bug and look at it now. Hello, that's

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Speaker 1: what I'm talking about, Even if it's subtle the rear

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Speaker 1: ends are changed, like the tail lights, something, the side mirrors,

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Speaker 1: and a good car detective can actually tell you just

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Speaker 1: like that what the make, the model of the year,

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Speaker 1: everything about the car. Based on those subtle changes, you

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Speaker 1: can probably explain it better than I can't. Go ahead

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Speaker 1: us because you know the detectives they deal with this

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Speaker 1: every day. I mean, you know a lot of good cops.

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Speaker 1: You know, see a car going away from when the

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Speaker 1: car hits the brakes, and they can tell you exactly

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Speaker 1: what kind of car, what kind of suv it is,

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Speaker 1: because of where the upper tail light is or or

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Speaker 1: what the size of the middle brake light is, I mean,

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Speaker 1: the make and model of these things. When they deal

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Speaker 1: with it every day, and someone starts to describe a

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Speaker 1: car to you as a late person, they're like, I

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Speaker 1: just remember it had a super bright light and had

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Speaker 1: a really really bright red light at the top in

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Speaker 1: between the two right on the trunk. Well, to me,

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Speaker 1: it's a car. SUVs have them up top. So all

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Speaker 1: these different little you know, leads, and all these different

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Speaker 1: little statements from your witnesses kind of start to put

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Speaker 1: everything together, and it's just how they do it. Take

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Speaker 1: it a vehicle pedestrian crash. You know, the vehicle hits

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Speaker 1: the pedestrian, kills the pedestrian, but he leaves he leaves

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Speaker 1: part of this taillight, I mean part of this headlight

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Speaker 1: where he leaves his rear view mirror on the side.

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Speaker 1: All that can be tracked back to the make modeling

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Speaker 1: kind of card is Robert Crispin? Do you have children?

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Speaker 1: Did you ever watch Aristocrats with them? Occasionally? Okay, we've

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Speaker 1: seen it maybe one hundred hundred times, hundred and five times.

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Speaker 1: This is just like over and over and over. Well,

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Speaker 1: there is a scene in Aristocats and I would probably

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Speaker 1: tell the jury this where there's two dogs, I swear

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Speaker 1: I think their names are Napoleon and Bonaparte, but I'm

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Speaker 1: not sure. And one of them can lift his ear

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Speaker 1: up and he can tell you what's coming. He can

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Speaker 1: tell you if it's Bertram, the evil butler that drugged

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Speaker 1: the kitty cats. He can tell you if it's Jealope,

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Speaker 1: if it's a bicycle, if one tyrus flat. What I'm

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Speaker 1: saying is and a roundabout way, if we can get

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Speaker 1: any idea on this car at all, A good harcop

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Speaker 1: a detective can help determine the make, model, even the year,

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Speaker 1: and we could start tracking this killer climb stories with

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Speaker 1: Nancy Grace who killed Kevin Jian. Guys, take a listen

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Speaker 1: to our friend Antonia Aello at CBS two. A sense

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Speaker 1: of shock and sadness has settled on the Yale University

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Speaker 1: community after the Saturday night's shooting death of grad student

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Speaker 1: Kevin Gia. I don't have a memory of him where

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Speaker 1: he wasn't smiling and happy, and even if you didn't

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Speaker 1: agree with all of his views, he was more than

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Speaker 1: happy to be your best friend. Eight thirty Saturday night,

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Speaker 1: residents in the East Rock neighborhood heard the distinct sound

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Speaker 1: of gunfire. One man spoke to me off camera. I

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Speaker 1: heard like around seven rapid guns shots like I turned

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Speaker 1: the lights off because I was scared. Police say someone

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Speaker 1: shot John multiple times. He was found near his car,

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Speaker 1: which had rear end damage. One possible mode of police

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Speaker 1: or exploring violent escalation after a road rage incident. We're

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Speaker 1: exploring every possibility, including whether or not there was an

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Speaker 1: accident that precipitated this incident, whether or not it was

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Speaker 1: a road rage. We do have very specific leads that

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Speaker 1: we're exploring or we're not ruling anything out at this time.

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Speaker 1: Straight out to doctor Daniel Bober, chief of psychiatry at

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Speaker 1: Memorial Regional Healthcare Systems and assistant professor at Yale, Doctor

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Speaker 1: Daniel Bober, you lived and worked in this area, this

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Speaker 1: exact area for such a long time. Did you hear

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Speaker 1: the neighbors say I was afraid? Isn't it true that

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Speaker 1: you often would wake up at not hearing gunfire? Yes, Nancy,

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Speaker 1: I mean this story is very personal to me, not

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Speaker 1: because just because of the Yale connection, but because he

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Speaker 1: was in the military as well, and I worked with

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Speaker 1: the military. But yes, quite frequently when I was living

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Speaker 1: in New Haven, I heard I heard gunshots all the

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Speaker 1: time at night. So there was definitely its sheriff crime

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Speaker 1: for sure. Now that's obviously not unique to New Haven,

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Speaker 1: and I don't think it has anything to do with Yale,

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Speaker 1: but it was definitely something I experienced when I was

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Speaker 1: living there. You know, I looked up online how much

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Speaker 1: it cost to go to Yale, and I just want

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Speaker 1: to tell you what I learned. Let's see here all

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Speaker 1: at oh right, here we go forty three plus forty

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Speaker 1: three thousand dollars plus to go to the be enrolled

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Speaker 1: in the Master's environment environmental program plus twenty thousand plus

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Speaker 1: four books and necessities. That's the bare minimum. That's about

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Speaker 1: sixty five thousand dollars. Bare minimum. I mean, then I

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Speaker 1: guess you have to eight right, and you have to

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Speaker 1: get back and forth to class. Says Why would anybody

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Speaker 1: pay seventy grand for their baby to be gunned down

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Speaker 1: in the street to go to Yale University? I mean,

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Speaker 1: growing up on a red dirt road, as you know

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Speaker 1: that I did, I guess I dreamed of Ivy League,

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Speaker 1: and I was thrilled to get to go to Mercer

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Speaker 1: and to NYU to complete my legal studies. But I

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Speaker 1: would think long and hard before sending one of my

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Speaker 1: children to such a high crime area Doctor bober Well Again,

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Speaker 1: I mean, I think Newhaven has a lot of depressed areas.

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Speaker 1: There's definitely a lot of crime, but people send their

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Speaker 1: kids there because of the quality of the education and

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Speaker 1: the kind of people that they're going to be exposed

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Speaker 1: to on campus. He may enlighten the person that shot

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Speaker 1: Kevin's young did. I wasn't talking about him, but I

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Speaker 1: was talking about the other fessors and the other students. Yeah,

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Speaker 1: I hear you. I hear you, doctor bow for why

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Speaker 1: did you go to Yale while I went to Yale

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Speaker 1: because you know, they had one of the best psychiatry

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Speaker 1: programs in the country, and I wanted to get the

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Speaker 1: best training so I could, you know, give the best

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Speaker 1: for my patience. And that's where I went. And I

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Speaker 1: had a great experience when I was there, and obviously

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Speaker 1: I was I myself was not a victim of crime,

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Speaker 1: but you know it's no secret that New Haven does

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Speaker 1: have some crime rid in areas for sure. Yeah. I

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Speaker 1: remember taking out loans to go to law school at

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Speaker 1: Mercy University. First they're Walter at George School of Law,

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Speaker 1: and then later I went back for a master's degree

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Speaker 1: in Criminal and Constitutional Law NYU. That costs some money.

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Speaker 1: I remember I would eight one cucumber role, Alexas, you're

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Speaker 1: gonna love this, one cucumber role, one salad and water

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Speaker 1: for dinner while I was paying to go to NYU,

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Speaker 1: and I would sit there and study alone at the

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Speaker 1: sushi bar, eating my one cucumber role. People sacrifice so

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Speaker 1: much to go to name schools. I remember, Alexis how

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Speaker 1: thrilled we all were with my sister got into the

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Speaker 1: Wharton School at University of Pennsylvania. It was just the

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Speaker 1: biggest thing that ever happened to us. We were thrilled.

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Speaker 1: I'm thinking about Kevin's mother, what she went through moving

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Speaker 1: from I believe it was Seattle to move in with

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Speaker 1: him to help him get through this. I mean, it's

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Speaker 1: a whole family effort to get somebody through an Ivy

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Speaker 1: League school. And he was even actually supporting her. He

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Speaker 1: was taking care of his mom. That's why he moved

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00:25:45,760 --> 00:25:48,119
Speaker 1: her across country so that he could cut down on

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Speaker 1: expenses and they could live together. So she has nothing now.

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Speaker 1: Her son had been murdered, brutally murdered, and he was

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Speaker 1: the one that was taking care of her. This is

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Speaker 1: a wide reading tragedy. It's affecting so many lives. Guys,

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Speaker 1: take a listen to our friend Zenia Maldonado at Fox

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Speaker 1: sixty one. I'll always remember him as being a very just,

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00:26:12,400 --> 00:26:16,879
Speaker 1: welcoming and wholesome individual, and he was very proud to

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Speaker 1: be a part of the community. Jiang was a grand

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Speaker 1: student at the Yale School of Environment. The school holding

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00:26:22,760 --> 00:26:26,600
Speaker 1: a virtual vigil for Jiang Monday night, his parents both

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Speaker 1: in attendance. He gave me a lot of a joy.

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Speaker 1: He's a litty thought theful woman boy picking cuff me

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Speaker 1: and I missed him. Have you all said he's a

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Speaker 1: very very charming we're a friend of me. Jiang served

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Speaker 1: in the US Army National Guard. During the vigil, those

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00:26:52,480 --> 00:26:56,520
Speaker 1: who served beside him sharing memories. Everyone who met him

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00:26:56,640 --> 00:26:59,840
Speaker 1: said that you are so so. They called him dig

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Speaker 1: Jang because he was so energetic all the time. Jang

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00:27:03,160 --> 00:27:06,640
Speaker 1: was a few days away from celebrating his twenty seventh birthday,

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Speaker 1: and he proposed to his fiance Zion Perry, just last week.

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Speaker 1: Perry sharing a statement reading, in part, Kevin was and

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Speaker 1: is a gift from God. Life is so precious and short,

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Speaker 1: and I am so thankful that God brought us together.

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Speaker 1: But strength his family is showing at a time like this,

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Speaker 1: I want to go straight out to Robert Crispin, former

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Speaker 1: law enforcement now at Crispin Special Investigations dot com. What

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Speaker 1: are the cops doing right now? They keep giving statements,

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Speaker 1: They're not releasing a lot of information. I don't think

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Speaker 1: they wanted it to get out that he was outside

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Speaker 1: of the car when he was found sustaining multiple gunshot wounds.

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Speaker 1: All that's intentional that they're not releasing that information, and

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Speaker 1: it's also why they don't release the specific cause of

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00:27:55,040 --> 00:27:58,320
Speaker 1: death in other cases. Obviously we know that our victim

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Speaker 1: was shot and killed. But there's a reason that they're

429
00:28:01,320 --> 00:28:04,760
Speaker 1: not releasing this information because if the bad guy's listening,

430
00:28:05,359 --> 00:28:08,200
Speaker 1: if the leads are still out there, and the evidence

431
00:28:08,240 --> 00:28:10,760
Speaker 1: is still out there, we don't want that campered with

432
00:28:11,000 --> 00:28:14,040
Speaker 1: or destroyed or altered in any way should we should

433
00:28:14,080 --> 00:28:17,960
Speaker 1: we find it. So there's a reason when they don't

434
00:28:18,000 --> 00:28:20,280
Speaker 1: tell you how somebody died. We just have a dead

435
00:28:20,320 --> 00:28:23,160
Speaker 1: body inside an apartment somewhere. Because if we do get

436
00:28:23,200 --> 00:28:25,359
Speaker 1: a victim, I mean, we do get a suspect and

437
00:28:25,400 --> 00:28:28,000
Speaker 1: we go to interview him, only the suspect's going to

438
00:28:28,119 --> 00:28:30,760
Speaker 1: know exactly the facts of that case when he goes

439
00:28:30,840 --> 00:28:33,960
Speaker 1: to when he goes to confess to us, Yeah, you

440
00:28:34,000 --> 00:28:35,439
Speaker 1: know what I did. I shot him in the head

441
00:28:35,480 --> 00:28:38,120
Speaker 1: and I shot him twice in the leg because he

442
00:28:38,280 --> 00:28:41,480
Speaker 1: upset me. Well, those are facts that only the suspect

443
00:28:41,640 --> 00:28:44,120
Speaker 1: is going to know. And you start putting out different

444
00:28:44,200 --> 00:28:47,520
Speaker 1: things into the public, and the bad guys starts seeing like,

445
00:28:47,600 --> 00:28:49,960
Speaker 1: oh my god, they know it's they know it's you know,

446
00:28:50,280 --> 00:28:51,920
Speaker 1: a black car I got to get rid of this car.

447
00:28:52,160 --> 00:28:55,440
Speaker 1: A lot of crimes happen and law enforcement releases information

448
00:28:55,520 --> 00:28:57,960
Speaker 1: that says we have absolutely no leads, we need help

449
00:28:58,040 --> 00:29:01,600
Speaker 1: from the public. These suspects sometimes get a false sense

450
00:29:01,680 --> 00:29:04,480
Speaker 1: of security. They keep driving the car. So there's a

451
00:29:04,560 --> 00:29:07,840
Speaker 1: reason that long ENFORFRONT releases certain things in a certain way.

452
00:29:08,080 --> 00:29:12,160
Speaker 1: They're not giving up. That to me tells me they

453
00:29:12,240 --> 00:29:15,520
Speaker 1: potentially have a suspect. They potentially have a car. They

454
00:29:15,560 --> 00:29:18,000
Speaker 1: could be doing active surveillance on a suspect right now.

455
00:29:18,520 --> 00:29:20,240
Speaker 1: They could be sitting on a car that's parked in

456
00:29:20,280 --> 00:29:22,640
Speaker 1: a parking lot in an apartment complex waiting for someone

457
00:29:22,680 --> 00:29:24,680
Speaker 1: to get into it. There's a host of things that's

458
00:29:24,720 --> 00:29:27,120
Speaker 1: going on, and they're not going to release what they've got.

459
00:29:27,400 --> 00:29:41,240
Speaker 1: They're giving you enough to get by Climb stories with

460
00:29:41,440 --> 00:29:46,800
Speaker 1: Nancy Grace. Guys, we were talking about the death Lieutenant

461
00:29:47,080 --> 00:29:51,280
Speaker 1: Kevin Jean. What happened? Why is this twenty six year

462
00:29:51,320 --> 00:29:54,080
Speaker 1: old man dad with his life in front of him?

463
00:29:54,480 --> 00:29:56,480
Speaker 1: Take a listen to our cut number four. This is

464
00:29:56,560 --> 00:30:01,240
Speaker 1: Tony Terzy at Box sixty one. Kevin Jian facebook page

465
00:30:01,320 --> 00:30:05,600
Speaker 1: biography was poignant. Life is a gift. I am so

466
00:30:05,960 --> 00:30:10,280
Speaker 1: thankful for so the community is grieving right now. This

467
00:30:10,520 --> 00:30:14,400
Speaker 1: is a loss of an extraordinary young man. At approximately

468
00:30:15,240 --> 00:30:20,240
Speaker 1: eight thirty pm on Saturday, officers responded after receiving numerous

469
00:30:20,360 --> 00:30:24,000
Speaker 1: nine one one palls of gunshots which occurred here in

470
00:30:24,080 --> 00:30:27,200
Speaker 1: the area of Lawrence and Nickel Streets in New Haven.

471
00:30:27,400 --> 00:30:32,120
Speaker 1: Kevin Jong pronounced dead on scene. His identity was confirmed

472
00:30:32,280 --> 00:30:35,400
Speaker 1: to be a resident of West Haven, twenty six years old,

473
00:30:35,880 --> 00:30:38,680
Speaker 1: and he was a graduate student attending the Yale School

474
00:30:38,920 --> 00:30:42,720
Speaker 1: of Environment. Police won't say much about the case, including

475
00:30:43,080 --> 00:30:47,400
Speaker 1: why Jiang, who had just proposed to his fiancee a

476
00:30:47,560 --> 00:30:51,560
Speaker 1: week before he was killed, was in the East Rock neighborhood.

477
00:30:52,040 --> 00:30:55,280
Speaker 1: We have developed information suggesting that this incident may not

478
00:30:55,400 --> 00:30:58,640
Speaker 1: have been an actual random act, that he in fact

479
00:30:58,800 --> 00:31:02,760
Speaker 1: was targeted. What do they mean by not a random act?

480
00:31:03,880 --> 00:31:07,360
Speaker 1: Does that have to do with his just announced engagement.

481
00:31:07,920 --> 00:31:10,520
Speaker 1: Does it have to do with road rage? That he

482
00:31:10,720 --> 00:31:14,320
Speaker 1: was hunted down because of road rage and shot dead

483
00:31:14,400 --> 00:31:15,920
Speaker 1: in the street when he was a lured out of

484
00:31:15,960 --> 00:31:22,000
Speaker 1: his car? What happened? The mystery only mounts as the

485
00:31:22,080 --> 00:31:24,480
Speaker 1: days go by. But I have another idea and I

486
00:31:24,560 --> 00:31:27,640
Speaker 1: want to throw this out there to you. First of all,

487
00:31:27,840 --> 00:31:30,280
Speaker 1: doctor Daniel Bober. I want to circle back to you,

488
00:31:30,840 --> 00:31:36,840
Speaker 1: doctor Bober, assistant professor at Yale who also studied there.

489
00:31:37,520 --> 00:31:40,920
Speaker 1: I know that that was more of a rhetorical question.

490
00:31:41,040 --> 00:31:44,479
Speaker 1: I know why people sacrifice all their money, all their

491
00:31:44,560 --> 00:31:47,640
Speaker 1: savings to help their children or themselves get through an

492
00:31:47,640 --> 00:31:52,760
Speaker 1: Ivy League school because it is believed that those are

493
00:31:52,800 --> 00:31:56,520
Speaker 1: the very best schools in the world and that if

494
00:31:56,560 --> 00:32:01,920
Speaker 1: you can get through, you'll be set. I mean, you

495
00:32:02,000 --> 00:32:04,840
Speaker 1: think your children will be set for life if they

496
00:32:04,920 --> 00:32:09,880
Speaker 1: get that golden ticket that Yale University, Harvard University, University

497
00:32:09,920 --> 00:32:16,000
Speaker 1: of Pennsylvania, you know, Brown, that golden ticket that will

498
00:32:16,040 --> 00:32:19,920
Speaker 1: take them through the rest of their lives. That's why

499
00:32:20,040 --> 00:32:24,080
Speaker 1: people do it. It's the mecca of learning. Doctor Bober.

500
00:32:24,160 --> 00:32:28,000
Speaker 1: You're absolutely right. Yeah, I agree. Um, I think like

501
00:32:28,120 --> 00:32:29,880
Speaker 1: in the case of your sister, you said she got

502
00:32:29,920 --> 00:32:32,560
Speaker 1: into Warden. You know, Warden is probably the best business

503
00:32:32,600 --> 00:32:35,280
Speaker 1: school that there is. So, I mean, these are things

504
00:32:35,360 --> 00:32:38,360
Speaker 1: that parents do to give their kids every possible advantage

505
00:32:38,480 --> 00:32:42,959
Speaker 1: in life. And you know, crime is something that's going

506
00:32:43,040 --> 00:32:45,600
Speaker 1: to happen anywhere. In some areas have more crime than others.

507
00:32:46,720 --> 00:32:48,920
Speaker 1: But you know, you want the best for your kids,

508
00:32:48,960 --> 00:32:51,200
Speaker 1: and sometimes you're willing to make these sacrifices to make

509
00:32:51,280 --> 00:32:55,800
Speaker 1: that happen to you, Robert Crispin, And let me try

510
00:32:55,840 --> 00:33:00,520
Speaker 1: with you too, Wendy. This is a new Haven West Haven, Annecticut.

511
00:33:00,680 --> 00:33:03,440
Speaker 1: That is a coastal town. They're going to be a

512
00:33:03,600 --> 00:33:10,440
Speaker 1: lot of tolls, and throughout the northeast there are tolls, tolls, tolls, bridges,

513
00:33:10,480 --> 00:33:14,560
Speaker 1: and tolls with surveillance cameras. That's what I'm working up to.

514
00:33:15,960 --> 00:33:20,360
Speaker 1: Not only surveillance cameras on tolls basically any direction the

515
00:33:20,400 --> 00:33:27,800
Speaker 1: Purple would have gone, but residential surveillance cameras, public transportation

516
00:33:28,320 --> 00:33:34,680
Speaker 1: surveillance cameras, ring doorbell, you name it. There's a way

517
00:33:34,880 --> 00:33:38,560
Speaker 1: to try to piece together where this black car, this

518
00:33:38,760 --> 00:33:42,360
Speaker 1: shiny new black car went. I mean, Wendy Patrick, you

519
00:33:42,440 --> 00:33:47,080
Speaker 1: saw what the neu Canan police did in the case

520
00:33:47,160 --> 00:33:52,920
Speaker 1: of Jennifer Dulos, right, they pieced together a video timeline

521
00:33:53,000 --> 00:33:57,520
Speaker 1: based on everything from home surveillance video to bus doors

522
00:33:57,640 --> 00:34:01,960
Speaker 1: opening and closing and seeing the drive by. Now that's

523
00:34:02,000 --> 00:34:04,640
Speaker 1: exactly right. So well, we have thus far we have

524
00:34:05,040 --> 00:34:08,640
Speaker 1: earwitnesses and eyewitnesses. We have the people that heard the

525
00:34:08,880 --> 00:34:12,600
Speaker 1: distinct sound of gunfire as it was explained numerous nine

526
00:34:12,640 --> 00:34:14,279
Speaker 1: one one calls that, let you know, there are lots

527
00:34:14,320 --> 00:34:17,160
Speaker 1: of people that actually heard this. But if the eyewitnesses

528
00:34:17,239 --> 00:34:19,040
Speaker 1: that are going to be able to link up what

529
00:34:19,320 --> 00:34:24,360
Speaker 1: surveillance cameras may have captured regarding suspect vehicles with a

530
00:34:24,480 --> 00:34:27,680
Speaker 1: vehicle the shiny black cars that was described that was

531
00:34:27,719 --> 00:34:31,320
Speaker 1: actually at the scene. And one of the challenges there, Nancy,

532
00:34:31,360 --> 00:34:32,719
Speaker 1: as you and I and actually as all of our

533
00:34:32,760 --> 00:34:36,719
Speaker 1: deaths know, is you tend to recognize things you're familiar with.

534
00:34:37,280 --> 00:34:39,759
Speaker 1: So wouldn't it be great if you'd actually did have

535
00:34:39,920 --> 00:34:42,680
Speaker 1: somebody with a working knowledge of cars or some sort

536
00:34:42,719 --> 00:34:46,279
Speaker 1: of a mechanical background that would have been able to say,

537
00:34:46,800 --> 00:34:50,880
Speaker 1: those distinctive markings on that suspect vehicle matches what we

538
00:34:51,000 --> 00:34:54,319
Speaker 1: have on those surveillance videos, because it is the timeline

539
00:34:54,440 --> 00:34:57,320
Speaker 1: that eventually, hopefully is going to be putting this together

540
00:34:57,480 --> 00:35:00,360
Speaker 1: as a case gets prepared for a jury, not just

541
00:35:00,640 --> 00:35:04,719
Speaker 1: any black car, this black car. To Alexis Terre's Chuck

542
00:35:05,320 --> 00:35:08,200
Speaker 1: joining me Crime Online dot com investigative reporter as well

543
00:35:08,320 --> 00:35:14,000
Speaker 1: as with lead Stories dot Com, Alexis Molly tibbets remember

544
00:35:14,719 --> 00:35:19,160
Speaker 1: no leads What happened to Molly couldn't find her. Long

545
00:35:19,239 --> 00:35:23,200
Speaker 1: story short, I believe it was residential home surveillance camera

546
00:35:23,560 --> 00:35:28,480
Speaker 1: catches a vehicle that is going back, and then it

547
00:35:28,560 --> 00:35:32,840
Speaker 1: comes back, and then back and then back. Where in

548
00:35:32,960 --> 00:35:36,560
Speaker 1: the area where she was jogging. What did it have?

549
00:35:36,760 --> 00:35:40,440
Speaker 1: It had distinctive markings on the side of it. I

550
00:35:40,680 --> 00:35:43,640
Speaker 1: think it's gonna end up being scratches along the side

551
00:35:43,640 --> 00:35:47,040
Speaker 1: of that car. That's how they found the killer. And

552
00:35:47,560 --> 00:35:52,279
Speaker 1: I remember Michelle Parker of the so called People's Court Mom.

553
00:35:52,880 --> 00:35:56,239
Speaker 1: She had all of those stickers were glow tin or

554
00:35:56,320 --> 00:36:00,880
Speaker 1: something that she was advertising her home business on her hummer.

555
00:36:01,239 --> 00:36:06,239
Speaker 1: When her hummer was found, those individual peculiar to her

556
00:36:06,360 --> 00:36:11,200
Speaker 1: car only stickers have been scratched off. It's very significant

557
00:36:11,239 --> 00:36:13,799
Speaker 1: if they can get video of this car to see

558
00:36:14,040 --> 00:36:16,880
Speaker 1: what if any markings are on it. But hey, the

559
00:36:17,080 --> 00:36:20,400
Speaker 1: big one, I'm burying the lead here. There's gonna be damage,

560
00:36:20,480 --> 00:36:23,759
Speaker 1: most likely on the front. I'm gonna I can't say

561
00:36:23,800 --> 00:36:26,480
Speaker 1: which in because I don't know where where Kevin's car

562
00:36:26,600 --> 00:36:28,880
Speaker 1: was damaged in the back, but there's gonna be damage

563
00:36:28,920 --> 00:36:31,440
Speaker 1: on the front of that black car. Alexis and the

564
00:36:31,560 --> 00:36:34,560
Speaker 1: police are gonna go to as you said, They're gonna

565
00:36:34,600 --> 00:36:38,640
Speaker 1: go to the repair shops. They know which ones probably are,

566
00:36:38,800 --> 00:36:41,560
Speaker 1: you know, the the ones that are going to handle

567
00:36:41,719 --> 00:36:43,960
Speaker 1: quick fixes like this, and they're gonna go and they're

568
00:36:43,960 --> 00:36:46,319
Speaker 1: gonna say, look, you, if you have this car, if

569
00:36:46,360 --> 00:36:49,200
Speaker 1: somebody comes in, you better let us know because it's

570
00:36:49,239 --> 00:36:51,880
Speaker 1: part of a crime scene. It's not just oh, I

571
00:36:52,000 --> 00:36:53,759
Speaker 1: bumped into the wall as I was backing out of

572
00:36:53,800 --> 00:36:55,719
Speaker 1: my driveway, like this is the police. They're going to

573
00:36:55,800 --> 00:36:58,000
Speaker 1: go to each of these places around town that they

574
00:36:58,120 --> 00:37:01,040
Speaker 1: know and they're gonna do it. And also it doesn't

575
00:37:01,040 --> 00:37:03,360
Speaker 1: even have to be like the four houses on the

576
00:37:03,440 --> 00:37:07,560
Speaker 1: corner where Kevin was murdered. It can be two blocks down.

577
00:37:08,040 --> 00:37:10,520
Speaker 1: They can get the image if they see a black

578
00:37:10,560 --> 00:37:13,400
Speaker 1: car there either in any direction. It doesn't have to

579
00:37:13,440 --> 00:37:16,520
Speaker 1: be right around there, but they can get images further

580
00:37:16,600 --> 00:37:19,000
Speaker 1: away from the scene of the crime. And there's also,

581
00:37:19,239 --> 00:37:23,600
Speaker 1: to you, Robert Crispin, private investigator, Christens Special Investigations dot Com,

582
00:37:24,080 --> 00:37:27,680
Speaker 1: the issue of cell phone data or if Kevin's vehicle

583
00:37:27,800 --> 00:37:31,920
Speaker 1: had a nav navigational system, because we can look and

584
00:37:32,040 --> 00:37:35,400
Speaker 1: see where he was and for how long. For instance,

585
00:37:35,600 --> 00:37:37,759
Speaker 1: where was he right before the shooting. Hadn't he been

586
00:37:37,800 --> 00:37:40,560
Speaker 1: in a bar, Did he get an altercation, did he

587
00:37:41,160 --> 00:37:43,439
Speaker 1: get an argument with somebody in the grocery store parking

588
00:37:43,520 --> 00:37:46,200
Speaker 1: lot and they followed him. I mean, you can learn

589
00:37:46,320 --> 00:37:49,520
Speaker 1: so much from that navigation system in the car and

590
00:37:49,760 --> 00:37:53,000
Speaker 1: from his cell phone, right, Crispin. Absolutely, And as a

591
00:37:53,040 --> 00:37:55,359
Speaker 1: matter of fact, that knife cuts both ways, because once

592
00:37:55,400 --> 00:37:58,239
Speaker 1: I developed a suspect and I dropped a subpoena for

593
00:37:58,320 --> 00:38:01,160
Speaker 1: his cell site tower location, I can ping him right

594
00:38:01,200 --> 00:38:05,000
Speaker 1: to the scene. So if I catch a LPR, we

595
00:38:05,080 --> 00:38:07,520
Speaker 1: call them the license plate readers, and we do identify

596
00:38:07,600 --> 00:38:11,120
Speaker 1: a vehicle and we identify a suspect. It's just like

597
00:38:11,239 --> 00:38:13,560
Speaker 1: here in Florida, you can't go anywhere without getting caught

598
00:38:13,560 --> 00:38:16,640
Speaker 1: by a license plate reader. And you know, we do

599
00:38:16,800 --> 00:38:19,759
Speaker 1: talk about some of these places are more repressed and

600
00:38:19,840 --> 00:38:23,120
Speaker 1: there's more homicides, believe it or not, especially here in Miami.

601
00:38:23,280 --> 00:38:25,800
Speaker 1: There's more license plate readers in some of the requested

602
00:38:25,840 --> 00:38:28,560
Speaker 1: areas where our higher crime rate is. So I'm going

603
00:38:28,640 --> 00:38:32,040
Speaker 1: to probably venture to say that you know, they're they're

604
00:38:32,080 --> 00:38:35,360
Speaker 1: employing the LPR system and they're trying to identify something.

605
00:38:35,480 --> 00:38:38,400
Speaker 1: And to talk about the cell phones. Absolutely, you're carrying

606
00:38:38,400 --> 00:38:41,800
Speaker 1: an electronic device that is paying off hundreds and hundreds

607
00:38:41,840 --> 00:38:44,879
Speaker 1: of towers as you're driving. Every time you drive down

608
00:38:44,880 --> 00:38:47,360
Speaker 1: the road and you stand your phone for an hour talking,

609
00:38:47,560 --> 00:38:50,120
Speaker 1: driving up the turnplate, you're bouncing off the cell phone

610
00:38:50,160 --> 00:38:52,840
Speaker 1: towers and they're they're jumping your signal to tower to

611
00:38:52,920 --> 00:38:56,160
Speaker 1: tower to tower, and technology today to put you within

612
00:38:56,280 --> 00:38:59,800
Speaker 1: fifty feet of a crime scene. Guys, for those of

613
00:38:59,840 --> 00:39:04,520
Speaker 1: you don't know about lpr's license plate readers, we pass

614
00:39:04,600 --> 00:39:08,320
Speaker 1: them all the time, Robert. The ones that I'm familiar

615
00:39:08,360 --> 00:39:12,279
Speaker 1: with are just a straight metal rod sticking up let's

616
00:39:12,280 --> 00:39:16,000
Speaker 1: just say, inside the interstate and then horizontal to that,

617
00:39:16,520 --> 00:39:20,440
Speaker 1: or a series that looked like solar panels, you know,

618
00:39:20,719 --> 00:39:25,000
Speaker 1: maybe two feet tall, and those are actually license plate readers.

619
00:39:25,080 --> 00:39:27,239
Speaker 1: Are those the ones you're talking about. So there's a

620
00:39:27,680 --> 00:39:30,560
Speaker 1: couple of different kinds. Obviously, there's the fixed ones that

621
00:39:30,640 --> 00:39:33,400
Speaker 1: are bridges or on long interstates, but there's also the

622
00:39:33,480 --> 00:39:36,640
Speaker 1: ones that are on police cars and those cameras. If

623
00:39:36,680 --> 00:39:38,719
Speaker 1: you look at the hood or you look at the

624
00:39:39,080 --> 00:39:41,640
Speaker 1: near the light bar or the back deck of the

625
00:39:41,680 --> 00:39:43,840
Speaker 1: police car, you see those cameras are angled down a

626
00:39:43,920 --> 00:39:48,200
Speaker 1: certain way, and as that officer's driving around, those tags

627
00:39:48,400 --> 00:39:51,200
Speaker 1: or those cameras are automatically running your tag. They're giving

628
00:39:51,280 --> 00:39:54,359
Speaker 1: up picture, they're giving a GPS coordinate location, and they're

629
00:39:54,400 --> 00:39:57,440
Speaker 1: running it to see if it's stolen. Automatically. The computer

630
00:39:57,719 --> 00:40:00,399
Speaker 1: is designed to do that, just as the cop down

631
00:40:00,400 --> 00:40:02,319
Speaker 1: the street. It's how we find a lot of people.

632
00:40:02,640 --> 00:40:04,759
Speaker 1: Once we get your tag, I can tell you where

633
00:40:04,800 --> 00:40:06,880
Speaker 1: you are, what time your car was parked there, and

634
00:40:06,880 --> 00:40:09,719
Speaker 1: I have an image of it. I can guarantee is

635
00:40:09,960 --> 00:40:11,919
Speaker 1: the LPR is going to come into this a little

636
00:40:11,960 --> 00:40:14,000
Speaker 1: bit if they can get a tag again. In the

637
00:40:14,080 --> 00:40:16,440
Speaker 1: last hours, the breaking news is that there is a

638
00:40:16,520 --> 00:40:22,359
Speaker 1: POI person of interest. Does what we know about this man,

639
00:40:22,520 --> 00:40:25,920
Speaker 1: Ken Sean Pon fit with the evidence that we know

640
00:40:26,120 --> 00:40:28,680
Speaker 1: to be true? Take a listen again to the New

641
00:40:28,760 --> 00:40:33,400
Speaker 1: Haven Police Chief. Mister Pon is wanted for questioning at

642
00:40:33,440 --> 00:40:36,840
Speaker 1: this time. We have a warrant for his arrest for

643
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Speaker 1: a stolen vehicle out of north Haven Correction for a

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00:40:42,160 --> 00:40:46,279
Speaker 1: stolen vehicle that he possessed in north Haven. The North

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Speaker 1: Haven Police Department came in contact with mister Pong soon

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Speaker 1: after our homiside. He is currently a person of interest

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Speaker 1: in our investigation. But I want to make sure you

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Speaker 1: know that he is currently now not wanted on that homicide. Again,

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Speaker 1: he should be considered armed and dangerous, and we asked

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Speaker 1: the public to continue their efforts to help us in

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Speaker 1: identifying any further witnesses. Any more information that you have

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Speaker 1: is critical to this investigation, but we just want to

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Speaker 1: make sure that the public knows that he has been identified.

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Speaker 1: If you're questioning what you just heard some of mine,

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Speaker 1: it's a lot of double talk. Bottom line, they're looking

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Speaker 1: for this guy, Keishawn Pan. They're not calling him a suspect.

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Speaker 1: They're saying he is armed and dangerous. That's enough for me.

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Speaker 1: The search is on Nancy Grace Crime Story. Signing off,

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Speaker 1: goodbye friend,