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KP: All right. Today is the 30th of June, 2023. KP: My name is Karina Pan and I'm here with our interviewee, Dr. KP: Jesse Chan, on behalf of the Houston Asian American Archive. KP: Alright. So, our first question is where and when were you born?

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KP: I was born September the 1st, 1985 in Nederlands, Texas. KP: So, that's a little tiny town close to Port Arthur, Texas, for anyone who KP: knows that area. KP: And how would you describe the household that you grew up in?

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JC: The household I grew up in JC: was—so, my parents are JC: both–are both first generation American Chinese JC: immigrants. And, I think

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JC: we—it wasn't a particular—it was—there was Chinese culture JC: involved, there—I don't remember JC: it being like particularly, like, it seemed like JC: a fairly balanced household in terms of integrating both

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JC: American and Chinese culture growing up. JC: Yeah, we moved around a JC: fair bit and I think every single time we moved to a different place, JC: it—the household changed us a little bit.

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KP: Yeah, that's interesting. KP: Can you like des—I know you said you moved around a little bit, can you describe some KP: of the neighborhoods that you grew up in? JC: Yeah, sure.

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JC: So, I think we moved away from Port Arthur, Nederlands, when I was fairly young. JC: We arrived in Houston. JC: My brother was born in Houston as well. JC: And then from Houston, we actually moved to Wales in the

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JC: UK, and there it was a very, very different household, lived in sort of JC: this–this really old cottage for a few years and moved to JC: another old cottage. JC: And then when we moved back–we moved back into

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JC: the—Houston. And every single time, the household JC: just changed a little bit. I mean, we threw away some stuff, of course. JC: The culture, I think, shifts a little bit from the UK and back to the US, JC: and yeah.

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KP: Wow, that's so interesting to hear that you've moved around so much. KP: Do you have any childhood memories, any favorite childhood memories that you'd like KP: to share? JC: Sure. Yeah, I had—I

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JC: really, really loved Wales. JC: My dad got sent there for a job in a little town called JC: Tenby, working for Texaco. JC: And we got to live in this little small town called Saundersfoot

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JC: for, I think, about three years. JC: And I remember it was—moving from, say, Houston to a little tiny JC: town in Wales was really different, but JC: I loved the experience.

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JC: There was so much nature to explore everywhere. JC: And yeah, the U-U–the UK was just JC: a—it was really different and I enjoyed getting to JC: know UK culture and visiting London.

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JC: I mostly remember getting lost in the neighborhoods behind our—in the little—the JC: thickets behind our house. JC: And that was-that was a lot of fun. KP: That does sound like a lot of fun.

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KP: I know you mentioned like a little bit about what your dad did, but what exactly were your KP: parents' occupations? JC: Yeah. So I think before I was born,my mom was a instructor JC: in the computer science department at Lamar University.

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JC: And my dad has always been a chemical engineer with different JC: specializations. But I think he moved from—he started—I think JC: he very early on started with JC: Texaco and then more recently has worked at BP, GE,

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JC: and I think now Air Products. KP: Gotcha. So what are some of the values that your parents emphasized in your KP: upbringing? JC: Yeah, hard work.

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JC: Flexibility, I think, is one thing. JC: Sort of a belief that–that even if JC: you aren't good at something or if you don't like something, then you can learn to like it JC: and you can learn to excel at it.

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JC: And I think that was–that was helpful to—I saw this very much in my mom, JC: how she would be able to adapt to a whole host of different things that I think were JC: new to her. She always would—she would read along with us when we had reading JC: assignments, and I think we would pick apart the books

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JC: together. She would maybe ask JC: some—she would be learning some of the more advanced vocabulary along JC: with us if we didn't recognize some–some words, we'd find them out together. JC: And it was, I mean, of course she

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JC: outpaced us very rapidly, but it was nice to kind of see that okay, of JC: course you can learn, you can adapt, you can do different things. JC: She would pick up tons of different hobbies. JC: And I remember when she started gardening, becoming a

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JC: realtor, of course, there are different things, different JC: household hobbies, cooking and–and music and sports, and JC: all the things that she would just basically try out, JC: she didn't really—she might not have always gotten it at first, but she soon

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JC: excelled at them after a little bit of practice. JC: And I think that has been something that stuck with me, that we JC: can change and we can excel at what we put our minds JC: to.

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KP: Yeah, that's great to hear. KP: I know you mentioned that your parents were first gen immigrants, so when did they KP: move to the US and why? JC: Yeah. So I think both of them moved to the US, if I'm not mistaken, for

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JC: college. My dad, I think, went to college in Wisconsin. JC: My mom went to college in—at Lamar University, and I think they met JC: in in Texas after my dad had started work and my mom JC: had been an instructor for a little bit.

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JC: But I think that both of them moved to the US for a lot of the same reasons JC: that first generation Chinese immigrants do: to have a better life, JC: to–to sort of JC: pursue, I don't know, pursue the American dream,

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JC: to get a good education. JC: Yeah. KP: So do you think education was really emphasized as a result? JC: Yeah, most definitely.

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JC: I mean, both my parents—so they–they—I don't think that they JC: were—they weren't overly strict on grades, but they always JC: wanted to make sure that we were, I guess, trying our hardest, reaching our potential JC: and our—they'd always try and talk with us about how we're doing in

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JC: school and try to make sure that we were—yeah, JC: that we weren't falling behind. JC: Yeah, I think education has always been emphasized. JC: My mom would—my dad, of course, he—my dad did a

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JC: Master's and has always been very, JC: sort of, very invested in how we do in terms of math and science JC: and STEM and yeah, our sort of career success. JC: My mom—I always like to tell the story that apparently one of

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JC: our JC: —I think great, great, great great grandfather? JC: Somewhere back in the—in a while back, used to be a JC: tutor to the emperor. And so I think for her she was also really proud

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JC: of—well, we come from families that like–that really value JC: education. KP: That's really cool. KP: Yeah. I saw you earned your bachelor's in Computational and Applied Mathematics from

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KP: Rice. So how'd you decide to attend Rice for your undergrad? JC: I did not think that I would get into Rice and so it JC: was my reach school. I applied early decision and then I got in and I quit. JC: That was basically [laughs] it.

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JC: I—as soon as I heard back from Rice, I thought, oh, this is–this is JC: great. I've peaked. JC: And I just went with it. JC: My parents think in retrospect, they said, "You

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JC: could have probably applied to a few other schools to see if you got in elsewhere." And JC: I was just so happy to have gotten into Rice that I unfortunately JC: didn't–didn't heed that advice. KP: Okay. Can you describe your undergraduate experience at Rice or in some, like,

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KP: defining moments that you had? JC: Oh, absolutely. JC: I mean, Rice was—I think I started falling in love with Rice JC: before I even got here as an undergrad.

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JC: I visited during, I think, Owl Days and I stayed JC: with a–with an I think then-sophomore or then-freshman JC: Dennis Rhee. JC: He showed me around Rice and I had–I had the best time, got a chance to sit in on a class.

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JC: He took me around to like a couple of different social events. JC: And it just, it–it was wonderful. JC: When I got—I mean, O-week when I got here was–was–was a JC: fantastic experience.

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JC: I was so exhausted, lost my voice at the end, but it felt like there was JC: so much energy and and liveliness at Rice. JC: When I started, I actually started as an English major, and so there JC: was a little bit of trying to figure out what I was going to study, a

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JC: little bit indecision in terms of what I would like to study. JC: And—but I started with the applied math, the computational JC: applied math major by the end of my freshman year and after that, that became a really JC: big part of my time at Rice as well, getting to know that community and,

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JC: well, struggling through the problem sets and trying to figure out how to become an JC: applied mathematician as well. KP: Okay, that's–that's so interesting. KP: I think it's a pretty big, like, shift from English to, like,

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KP: this entire world of STEM. KP: So how did you decide to make that change? JC: There was—so I had always—I JC: had told myself that I was going to go into philosophy or English when I got to–to

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JC: Rice. But my–my dad said you should—I JC: think he said, "You should take some STEM classes just in case." And I JC: ended up taking this class CAAM 210, Introduction to, I JC: think, Computational Engineering or Scientific

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JC: Computing—I forget what it–what it used to be called. JC: We still teach it, but it was an introductory—introduction to computational JC: mathematics essentially. JC: One of my friends, Samuel Feng, was TAing it at the time and

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JC: I–I loved it. JC: I think that a lot about that class JC: shifted the way I thought about–about the field of mathematics. So, I loved English and I loved creative writing.

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There was a poetry class that was just the–the highlight of my–my freshman year that I—that was the most fun I've had. One of the most—some of the most fun I've had in college.

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But it became a little more difficult, I think, to gauge how I was doing in these English classes as I kind of proceeded to more advanced classes. And I remember–I remember an American lit class where I would write an essay, but I would just not really be sure

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if–if I liked what I write—I would shift—I would write an essay with one perspective, and then I'd shift that perspective, and I couldn't tell which one was–was the right one. I couldn't tell which one would get me the better grade. I felt a little bit unanchored in–in those courses,

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and I still have a lot of respect for the humanities and for–for English and the skills and the thinking it teaches. But I realized that it was–it was nice to have something to anchor myself to. And with applied math, computational mathematics in

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particular, it well—there's the mathematics you can anchor yourself to, but it also gave me the chance to–to see math from a different angle. Like in high school, you're not really taught to do mathematics with—you can use a calculator, but it doesn't become a core part of your of your learning

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or your mathematical process. A lot of it is–is based on more theory, on–on formulas or on trying to prove different things, and inserting computation into it, I suddenly was like, oh, I can–I can—This is—I have never

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felt so anchored to a–to a mathematical concept as when I'm implementing it because I can check literally every single step of the code, make sure that kind of—that is consistent with what I'm thinking, make sure that all of that is working right. It was concrete in a way that I hadn't experienced before.

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It gave me a chance to also help some other people. If I figured out something, then I really enjoyed learning how to explain it to some others. I was a student TA or a labbie for this class for, I think, the last seven semesters of my time at Rice.

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And it was—yeah, it was a very new experience for me that really catapulted me into computational mathematics. KP: Wow. It definitely sounds like you've got a passion for computational math. KP: And so, I see that you also earned your Master's and your PhD from UT

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KP: Austin's Institute for Computational Engineering and Sciences. KP: So what led you to decide to pursue higher education there? JC: Well, I graduated during the JC: first financial—first economic downturn in 2008,

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JC: or at least not–not the first. JC: But I graduated during the 2008 economic downturn, and so finding a JC: job was a little bit trickier. JC: But even before that, I–I felt like I had kind of just

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JC: started in applied mathematics—when I interviewed at a few companies, JC: and it seemed like we would JC: be doing interesting technical work, but that I wasn't really going to JC: be able to use most of the stuff that I learned and really loved

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JC: in the Applied—in the Computational Applied Mathematics major here at Rice. So I thought, "Okay, I'll apply for some jobs and if I don't get them, then I'll apply for grad school." And I ended up loving the grad school visits and really enjoying the–the culture that I saw.

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And I just thought this would be great to feel like I act—to–to do a little bit more of this, because I felt like even–even though I was a Computational Applied Math undergrad major, I felt like I didn't really understand it fully by the time I graduated.

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And then close to the end of your senior year in these majors, you often sit in on grad courses and I think they have the effect of just kind of showing you how large the world is in–in computational and applied math out there. So I thought it would—I felt like I'd just started and grad school gave me another four

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years—five years—five and a half to figure that out. KP: Okay, that's–that's great. KP: Sounds like you really got a chance to pursue what you loved in grad school. KP: Can you describe your graduate experience at the Oden Institute and some defining moments

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KP: that you had? JC: Sure. JC: I really enjoyed the Oden Institute. JC: It was—it felt very familiar and

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JC: yet very different at the same time. JC: So it was–it was a nice way to find out that—how JC: culture influences mathematics. JC: So, Rice, for example, I think, was a very computationally

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JC: and mathematically oriented department, whereas the Oden Institute JC: injected a whole lot of engineering into it as well. JC: And this was informed by—I mean a lot of the faculty there. JC: My own advisor, Leszek Demkowicz, was from the Aerospace and Civil—had a background in

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JC: aerospace and civil engineering, and I'd never really worked with those–those people JC: or, sort of, those areas before. JC: So I got to know a lot more about kind of the mathematical models that I was JC: trying to work with, got a lot to know—I got to know a lot more about the ways in which

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JC: engineers speak of computational concepts in a–in a different way. JC: And it was nice to see things differently and to see JC: how, I guess, different concerns for different communities between, say, JC: a mathematical—more mathematically-minded community and a more engineering-based

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JC: community changed the way in which they approach certain topics. So, it was–it was really eye opening in terms of the field. And Austin was just [laughs] Austin was–was amazing.

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My parents were a huge help. They helped me find—they actually helped me find—buy a place, a condo while I was there. And I think that made it a lot easier to–to—it

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made it very easy to focus on–on graduate school at that time. And I don't think I would have succeeded in grad school quite as much without their help. But from—I–I loved living in Austin. It was—it felt like a small town compared—it felt like a small town compared

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with Houston, but had so much vibrant culture. It was such a cool city at that time. I played, I think in two bands while I was there, and it was–it was some of the most

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fun I have ever had in a city. It was a lot of work and a lot of play. KP: That's great to hear. KP: You mentioned playing in bands.

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KP: What instrument did you play and how long had you been playing them? JC: I think—so I played guitar and and bass all through JC: college and all through high school or—through some of high school, JC: most—all of college.

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JC: And then, when I got to Austin, I started getting more interested JC: in the folk and indie music scene. JC: And it was there that they—that I got involved with a JC: couple of folks at my church and then the church music group, and

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JC: I would be playing, depending on the day, either drums, JC: bass, banjo, or guitar. JC: And it was, yeah, it was a good place to–to learn JC: how to play all these as well.

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KP: Wow, That is really impressive. JC: It's all—it's all fret stuff. JC: Fret—[laughs] I have respect for anyone who plays–who plays violin or anything JC: fretless because I cannot.

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JC: Frets make it easy. KP: How did you decide to pursue a career in academia and teaching? JC: To be honest, I don't know if I really consciously decided it. JC: I think it—so when I was in grad school,

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JC: I don't think I ever envisioned myself becoming a professor. JC: I think I might have envisioned a career in research, but maybe at the JC: national labs or maybe at the research arm of some company. JC: I think after grad school, I ended up coming back to

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JC: Rice for a postdoc and that gave me a chance to teach, gave me a chance to do JC: research. It really pushed me, I think, in a very JC: different direction to see how much I could do JC: independently, and I think throughout all this, I

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JC: was—before actually getting any—before actually JC: applying for an assistant professor position, I just thought, "Well, it'd be nice JC: to see how far I can go." I think becoming a faculty member always seemed like such a risky, far off goal

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that I thought, "Okay, well I can apply and then I'll apply to other stuff because I probably won't get it." And so when I got the postdoc, I thought, "Okay, we'll see how far this goes." When I eventually finished the postdoc and actually got a few offers, I thought, "Wow, I guess–I guess I'll kind of end up

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here." So, I–I don't think it was as conscious a choice as I first–as I–as–as it is for some people. Honestly, I just kind of like what I do. There's—there were some research experiences for

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undergraduates and some internships that I did during–during undergraduate and grad school where there was just a sense of discovery. Like you notice something slightly different mathematically–mathematically that you can exploit to either make an algorithm

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faster or to make it more accurate. And it was that sense of discovery that I kept getting little, like, bits of throughout grad school and throughout my postdoc. And I loved that so much that I felt like I–I kind of

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want to try and see if I can get more of those. And those have really been the–the moments that have sustained me as a-as a faculty member as well, just discovering these things and discovering them with my students. It is still the most–the most fun part of the job.

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KP: Wow, that's great. KP: Do you ever think you had, like, a calling to teach or like, did you ever first, like, KP: discover your passion and talent for teaching? JC: I'm not so sure I'm a talented teacher, to be honest.

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JC: I–I'm not—I am admittedly not the best lecturer. JC: I think I have to make a lot of mistakes before I get comfortable enough with the JC: material to really teach it, to lecture on it smoothly. JC: But, I don't think I ever felt called

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JC: to be–be a–be a lecturer or teacher, but I do think I really enjoyed– JC: I really enjoyed being able to meet other people JC: where they were at in terms of their experience. JC: I feel like—so I never did, math competitions or UIL,

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JC: or any–anything really mathematically related in high school. JC: And so I always felt like a—like not that—just JC: not that good at mathematics. JC: And, I think if you come from that perspective,

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JC: you—I think you often appreciate that there are simpler JC: ways to look at certain things. JC: And if I can bring those simpler ways to someone else, then JC: I'm—that–that is really satisfying to me.

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So a lot of what—my postdoc advisor really drove this home—that a lot of complex mathematics is really hidden behind this veil of like, notation and–and–and terminology. And when you strip it down, it's really a lot of very

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concrete mathematical ideas. You can–you can view them much more simply, much more intuitively. I think it's very similar to what–what some YouTube mathematicians or—mathematicians on YouTube will do nowadays, where they, like

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3Blue1Brown, for example, makes these great videos where they break down very, very complex ideas and just show you the basic intuition and try to convince you that this–this is easy if you look at it the right way. So I think if

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I–if I—any–any part of a calling to teach is, I think, rooted in that–that I'd like people to see that, to—I'd like to convince myself, first of all, that most of the times this is easy if you look at it the right way, or if you find the right way

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for yourself to look at it. Beyond that, I–I've learned to love it, but I–I don't think I ever expected to–to be doing it for a–for a living. KP: Wow, that's great.

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KP: Moving back a little bit, what were your first jobs like? KP: Especially, I know you mentioned working as a waiter at Dumpling King. KP: It doesn't sound easy working for $1 and tips. JC: [laughs] That was–that was honestly a fantastic experience.

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JC: I–I still–I still go there actually. JC: We really—they, in my opinion, they still have some of the better—the best JC: steamed dumplings in Houston, and yeah, I will always JC: get their green onion pancakes.

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JC: It was–it was good–it was JC: —I like–I like being front of house wait staff. JC: I really enjoyed interacting with the customers. JC: It—I don't know.

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JC: I think there's–there's—at least working in a restaurant, there's always feels like JC: there's something to do. JC: So when you're not bringing stuff–stuff—there are some dead times, of JC: course. But it was fun to try and keep up with the–with the

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JC: dinner rush or the lunch rush whenever I was there. JC: It was nice to feel like, "Okay, I have some responsibility. JC: It's—this is–this is kind of–this is kind of new as a high school JC: student." And it was–it

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JC: was somewhat—it was–it was nice to feel useful. JC: I—when I was working there, there weren't—the other JC: servers often were first generation immigrants, and JC: so many didn't speak English quite as fluently.

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JC: And so it was nice to be able to—if we got a letter or if we got a JC: phone call, then I could answer it and kind of translate—badly translate things JC: into Chinese for the owners and the other waitstaff, JC: and yeah,

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JC: I–I really enjoyed it. KP: That's great. Can you describe like how the roles that you've assumed have KP: kind of evolved with your career and like teaching and doing research and as well as KP: like the challenges and rewards that came along with that?

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JC: Yeah, that's an interesting question. JC: I think—so I think this is JC: probably true for a lot of faculty members that JC: they—their

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JC: connection to their research shifts and becomes JC: maybe a little—it becomes a little more distant as they JC: as they proceed onward in their career. JC: I think when I—so as a grad student, I think you just

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JC: are trying to figure out—just trying to get to know your field, get to know JC: yourself as a researcher, kind of what ways work best for JC: you, and you're, of course, trying to JC: build your skill base as well.

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JC: I don't think—I think during that time I really–I really don't think I JC: understood things very well. JC: I didn't really see the world for how large it was either. JC: As a postdoc, I think at around that time I started

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JC: to become comfortable enough with the tools that I was using JC: to—use them to explore a little bit, to kind of see JC: conceptually what I could do in certain areas. JC: And that was–that was really nice.

00:28:55.370 - 00:29:09.310

JC: The first couple of years of my–of my time at Rice as an assistant JC: professor, those, I think were JC: the—I–I felt the closest to my research because it was mostly JC: just me.

00:29:09.310 - 00:29:21.690

JC: I didn't–I didn't have a student until my second year. JC: And then—even then, they worked on a JC: kind of separate project that I had sectioned off for–for–for JC: them.

00:29:21.810 - 00:29:41.220

But I think during those times I felt very free to just explore everything on my own and try to–try to find the right fit in terms of what I wanted to–to focus on. And I think that was when I was most tightly integrated with–with the

00:29:41.220 - 00:29:55.320

research as well. I sort of—I knew the codes inside and out. They were all mine. I knew all the technical details of everything, and then as I kind of pursued—as I've gotten older and maybe a little more tired and as I've

00:29:55.350 - 00:30:12.480

taken on more students, I think I've–I've tried to maintain a very strong connection to the technical aspects of their work, but I have also tried to–to, I guess, give more of that

00:30:12.480 - 00:30:25.500

to the students so they can explore the technical aspects themselves. They can learn things so they can get an intuitive sense. I don't want it to just be me telling them "this is the technical way in which they–they do things," because a lot of the times my students will figure out far better ways than

00:30:25.500 - 00:30:42.020

I–than I came up with to-to do things. So at this point now, as I'm kind of reaching the end of my time as an assistant professor, I feel like I am–I feel like I understand my field a little bit better.

00:30:42.260 - 00:30:57.140

I don't necessarily need to—I don't spend quite as much time in the technical parts as I used to. I used to spend, I think, almost every day coding, implementing, getting something to

00:30:57.140 - 00:31:15.200

work, and now I might spend like 2 or 3 out of the days really heavily focused on that. But often it'll be with my students or with some collaborators. And so I think I'm a little bit further removed from the nuts and bolts of it. I think this–this gives you—this gives most faculty a chance to, well,

00:31:15.200 - 00:31:30.710

try to explore the larger issues. Such as, well, what are the–what are the kind of issues—what are the problems that that are facing your little subfield? What are the problems that are facing your field of—your broader field,

00:31:30.740 - 00:31:42.620

say, just computational physics based simulations in general? It also gives you a chance to see, well, what are the problems that are facing, say, the department, the more human problems? And it gives you a chance to explore those areas

00:31:43.160 - 00:31:59.690

and–and not just focus completely on your little section of research. That said, I think I would feel really disconnected from this field if I didn't have a chance to just explore, tinker, and code on my own

00:31:59.690 - 00:32:14.490

as well. I think that's—that part keeps me feeling grounded and connected to, well, what my students are doing and what everyone else is doing. So, yeah, I'm hoping that balance will kind of stay as I continue onward.

00:32:15.870 - 00:32:30.630

KP: That's interesting. Can you share a little bit about like what you enjoy most about your KP: work? I know you've mentioned things here and there. JC: Sure. By far it's the JC: sense of discovery.

00:32:30.660 - 00:32:49.290

JC: So I can think of—I can think of almost every–every JC: single student, PhD project, JC: Master's project, and even some undergraduate projects. JC: There's just a—they usually start with, "Hm, this

00:32:49.290 - 00:33:06.510

JC: would be cool if we could do this," or,"I think we can do this." And JC: there's a kind of very broad, intuitive idea, "this is probably possible based on JC: what I've seen in the past." But when you drill down to the nuts and bolts, I JC: feel like–I feel like then it becomes trickier.

00:33:06.960 - 00:33:23.920

JC: Then you're like—then you see, these are the technical issues, why this hasn't been done JC: previously, or if we try and account for this and suddenly we have to give up some JC: other nice properties, mathematical properties of different methods we've JC: analyzed and overcoming that has always been the

00:33:24.310 - 00:33:37.270

JC: most fun part of a project. It's like—it feels like we go—I go from a very broad sense of "this is–this is what I'd like to do. This is probably possible." Narrowing it down to "these are the challenges

00:33:37.270 - 00:33:56.710

that–that are in between getting this between where we are and getting this to work." And that one moment when I think we figure out a key trick or a key way to look at something that makes the project suddenly a lot more tractable, a lot more feasible, that is

00:33:56.710 - 00:34:10.590

always the part that I enjoy the most by far. It's a little bit like—so, I like doing puzzles with my partner. And often what what I find myself doing is taking a little

00:34:10.590 - 00:34:24.930

piece and just kind of staring at it and then looking at the reference picture. And then eventually if I look hard enough, then I can see, okay, it—this looks like it probably belongs here. And then immediately, it all becomes clear that I can just put this piece right there,

00:34:24.930 - 00:34:40.500

and maybe a couple other pieces fall into place. But it feels very much the same way in terms of mathematics—that there's–there always is the feeling of a puzzle piece sliding perfectly into place after trying to figure out how it

00:34:40.500 - 00:34:55.870

goes—how it fits in for–for weeks or months. And that is the most satisfying part, by far, for every single project I've worked on. And more recently with my students, I think, seeing

00:34:56.680 - 00:35:09.520

that sense of discovery from their perspective. If they—like my—some of my–some of my students have been discovering things that I didn't realize were possible. They were solving problems that I–that I didn't know how to solve.

00:35:09.520 - 00:35:27.730

And seeing the way in which they approach things, it similarly feels like a puzzle piece kind of sliding into place, and-and suddenly like, "Oh, I can like—it feels like I've opened up a view into this world." Like when you're playing a video game and suddenly you reveal a giant part of the map because you–you–you

00:35:27.730 - 00:35:40.750

finally got through one little section that–that's–that's a lot of what–what I love the most about this–this field of work. KP: That's great to hear. KP: In your opinion, what do you think are like the most important traits of like being a

00:35:40.750 - 00:35:59.720

KP: good teacher and a mentor for college students or like leading your research group KP: and like, what guidance is most needed for your students and team members? JC: I think, so I'll go with what my undergraduate JC: mentor-mentor told me.

00:36:00.260 - 00:36:17.020

JC: He said—I think JC: you–I think he said you have to start with caring JC: . And from there you can kind of build from—you can build onward. JC: I think I would agree with that.

00:36:17.020 - 00:36:35.310

JC: There's—one of the most remarkable things about this department is that JC: I—everyone has different ways of JC: approaching it, but I think they all fundamentally care a lot JC: about–about being a good mentor or teacher or an

00:36:35.310 - 00:36:54.270

JC: instructor. Everyone that I've seen come through here is JC: really passionate about the areas that they–they work in, and that reflects in the JC: courses they teach and in terms of the way in which they approach students. JC: Now, some people will be–will—that will lead them to be more strict with their

00:36:54.270 - 00:37:09.660

JC: students because they want to push them and maybe–maybe JC: help them exceed their boundaries. JC: For me, I think it just—it shows up in just wanting to be available. JC: Like if someone has a question or if someone–someone is confused, and

00:37:09.660 - 00:37:29.340

JC: I–I really—that's something I'd really like to rectify. JC: I—because I believe that everything is—should JC: be clear or easy if we kind of look at it in the—or JC: it can be clarified or made easier if we look at it from the right perspective.

00:37:29.370 - 00:37:45.510

So I try to be really available. I try to answer questions fairly quickly on Slack or other online forums, and I think that's the way in which—the way I care about my area comes out. But I think at the core, as long as you care, I think

00:37:45.510 - 00:38:04.140

that–that really–that really centers things because that–that's the–that'll be the driving force behind all the different adjustments you make. If you try to make yourself more effective as a teacher or if you try to improve your lecture style, then all this, I think, is best

00:38:04.140 - 00:38:20.980

motivated from caring about the area and about the students. Apart from just that core aspect, I think–I think there are–there are sort of technical skills that are also helpful, just

00:38:20.980 - 00:38:39.480

being—learning to organize things in a way that's–that's easy for you. That's really helpful. Learning to—I guess , be a little bit flexible in terms of how you structure the course

00:38:39.480 - 00:38:55.770

and how you adapt it. As to each class, every class is a little bit different. I remember one time a grad student came in and just said, "Why aren't you doing it this way? This is—it's a whole lot easier if you–if you view this one thing with this other formulation." I thought, "That–that is fantastic." And so immediately

00:38:55.770 - 00:39:15.120

the next day, I–I took that and redid the lecture, and it was so much better. Yeah, I think these are all helpful. One practical skill that I really appreciate is public speaking and being

00:39:15.120 - 00:39:33.030

comfortable with public speaking or kind of being on stage does help a little bit. I know there was–there was a faculty member at Rice who's now at Northeastern, I believe he actually took some improv classes to become more comfortable with

00:39:33.030 - 00:39:52.560

this. There are definitely instructors of improv and–and theater that are also focused on–on, well, academics—on how to improve your stage presence, how to better communicate things. Because there is a–there is a communicative aspect of teaching as

00:39:52.560 - 00:40:14.470

well. I'm not the best at it, but I do think like spending time in these bands in Austin, playing music , kind of being on stage for those things—that definitely helped make me feel less uncomfortable in terms of this–this lecturing as well.

00:40:15.920 - 00:40:27.860

KP: Okay, that's interesting. KP: Do forgive me if I pronounce this wrong, but I noticed that you're interested in KP: researching high order, discontinuous Galerkin methods and high KP: performance computing.

00:40:27.860 - 00:40:39.680

KP: [JC: Yeah.] So explaining kind of like, what that is in layman terms and like, how you KP: first became involved in such research? JC: Yeah, most definitely. JC: So broadly, the area that I'm interested in is

00:40:39.980 - 00:40:57.500

JC: computationally—computational physics based simulations. JC: So, I often use the the example—if you ever see JC: like these computer generated images of a car moving and then it JC: gets–it crashes and it gets crumpled, and you see all these bright colors show up.

00:40:57.500 - 00:41:12.300

JC: Or if you see like a Formula–Formula One race car, and you see like visualizations of JC: flow going over it. JC: These are the types of simulations that I'm–I'm interested in, especially the flow JC: based simulations, because most of my work nowadays is in fluid dynamics.

00:41:12.300 - 00:41:29.700

JC: With all of these methods, I think almost all of JC: them tend to basically do the same thing. JC: They take the area in which—they take the space in which you're JC: trying to figure out how something works, say, how fast this fluid is going, what the

00:41:29.700 - 00:41:45.330

JC: pressure of this fluid is at certain points, how it's kind of JC: generating vorticular flow. JC: All of this stuff can be boiled down into–into JC: values for, say, the velocity or the pressure or,

00:41:45.750 - 00:42:00.570

JC: say, the density or different physical quantities that you can–you can JC: track. So, what most simulation methods will do, they'll take a domain, and they'll break it up into little small pieces, and then over each individual piece, they'll try

00:42:00.570 - 00:42:16.890

to approximate what these values are. So, what the velocity is on this little tiny subsection, what the pressure is, etc, etc. This is true for most methods and the ways in which different methods are

00:42:16.890 - 00:42:33.030

different—sorry—well, what they'll do is they'll approximate the—these physical quantities over each of these subsections, which I'll call an element, and then they'll evolve those in time or just try and solve for them if it's a–if it's a time independent equation.

00:42:33.270 - 00:42:51.990

But often the differences between different methods just come down to how you break up these and construct these little elements. So discontinuous Galerkin methods they have—they are a type of finite element method which fall under Galerkin methods.

00:42:51.990 - 00:43:09.720

And this is a very, very old engineering approach to modeling and simulation where you just take a domain, you break it up into a whole bunch of tiny triangles, and then over each little triangle or square or cube or tetrahedron in 3D, you try and approximate the solution

00:43:09.720 - 00:43:27.960

using some either a linear function, a constant function, or maybe a high order polynomial function, and discontinuous Galerkin methods basically do this third option where over each little individual element, the solution is approximated using a polynomial, and it's then evolved.

00:43:28.080 - 00:43:46.990

So, the reason why these—I use these methods, why I'm interested in them, is, on the technical side, they–they have some nice mathematical properties which make things easier in certain contexts, especially in fluids, but more so they just make for a very

00:43:46.990 - 00:44:02.050

convenient implementation. It was the area that I learned with my postdoc advisor, Tim Warburton.He is a expert on discontinuous Galerkin methods, and I think through his—through working

00:44:03.250 - 00:44:22.550

with him, it was—he showed me ways in which you could view a discontinuous Galerkin method as a very simple, minimal set of operations, which I think helps in teaching it. So these discontinuous Galerkin methods, just to

00:44:22.550 - 00:44:35.000

finish off the description, the main idea is you have these small elements and the solution can be discontinuous on each one. That's the main thing. So you have on each element a polynomial representation, but

00:44:35.000 - 00:44:46.670

they're not necessarily continuous. And so you have to transfer some information between each of these elements, which leads to extra costs, but also makes the implementation, I'd say, significantly easier for certain setups.

00:44:47.700 - 00:45:05.820

A lot of the reason I keep using these methods is just because I have some expertise in them. And there's, of course, inertia, but they do make it—they–they do provide some mathematical properties that have allowed me to develop some of the new schemes that the new numerical simulation

00:45:05.820 - 00:45:23.310

techniques that I've been working on for the past, I guess, five years now, which are related to this structure of these discontinuous Galerkin methods. That said, I do also dabble in other types of discretizations . Other people may work on finite element methods.

00:45:23.700 - 00:45:36.360

I've dabbled a little bit in those. I've dabbled a little bit in finite difference type methods as well. And all of these I think, once you have enough experience in them, in–in computational simulations, all of these look like

00:45:36.360 - 00:45:51.370

slightly—slight variations on each other. They have–they have different analyses, different mathematics behind them. But in the end, when you implement them, I think you can kind of see very

00:45:51.370 - 00:46:06.680

similar features that are shared between all of them. KP: Wow, that's so interesting. KP: I think you explained that really, really well. KP: I'm not sure how often you work with other people in your work, but how difficult or

00:46:06.680 - 00:46:19.760

KP: easy would you say it is to, like, recruit qualified team members and what KP: qualities do you value most in that? JC: That is an excellent question. JC: And I–I will say at this—just to start

00:46:19.760 - 00:46:34.810

JC: off, I do not know about the second JC: part. That, I JC: think, has changed a lot over the years. JC: It depends a little bit in terms of what I'm working on.

00:46:35.380 - 00:46:54.830

JC: So I—so, in terms of recruiting JC: qualified people, I've often had the issue that I think I JC: want to work with more people than I–than I can, that there JC: are phenomenal students at–at Rice that I've had to turn down working with

00:46:54.830 - 00:47:10.490

JC: just because I didn't necessarily have the funding or the space in my group at that JC: time. And I–I think they would have done excellently in my JC: group, but they're of course doing excellently in other people's groups as well JC: at the moment. I think in terms of

00:47:10.490 - 00:47:26.370

JC: skills, I—for JC: me, a–a strong mathematical and computational JC: foundation are really helpful. JC: So it's helpful for me if my students know how to code and they know how to do

00:47:26.400 - 00:47:44.040

JC: mathematics, but also to be able to combine the two. JC: Synthesizing two fields or combining two fields together is always a JC: little bit different than being an expert in each field separately. JC: So, what I mean by that is I—it really helps for me when a

00:47:44.040 - 00:47:59.160

JC: student knows how to see the mathematics in the computation and see the JC: computation in the mathematics. So, to be able to look at some mathematical formulation and think, "Okay, I can implement this really efficiently computationally or this is really

00:47:59.160 - 00:48:16.920

convenient to put into existing frameworks." That is a–that is something I'm really interested in. Similarly, if you can look at your code and if we spend a lot of time debugging code, trying to figure out what went wrong and often the bugs are not really computational bugs so much as mathematical

00:48:17.020 - 00:48:31.990

bugs, thinking from a mathematical perspective, being able to see an overarching mathematical theme in the code and being able to pick that apart bit by bit, that also ends up being really useful. And I think the most successful students in my group have essentially this skill

00:48:31.990 - 00:48:47.800

to be able to—there's a–there is a technical word for this: co-design, I think, to be able to co-design things that involve both mathematics and computation.

00:48:47.950 - 00:49:03.670

I'm sure if I was a better engineer or physicist, then being able to interact with that field as well would open up even more avenues. But for myself, these are the two that I focus on. KP: Interesting. Throughout your career in academia, have you ever faced

00:49:03.670 - 00:49:19.770

KP: discrimination as an Asian American, or has your minority experience shaped your work KP: experience at all? JC: That is a good question. JC: I–I am not sure.

00:49:19.770 - 00:49:38.960

JC: And this is not be—I–I'm not sure I think because I JC: often am not entirely aware until afterwards. JC: So there are a couple mentors that I've talked with at Rice JC: who I think are much more active in the Asian American Pacific Islander

00:49:39.410 - 00:49:55.820

JC: communities and are a lot more, I think, cognizant JC: of, say, issues like discrimination or JC: or microaggressions or any–any–any way in which JC: anti-Asian bias can show up.

00:49:56.270 - 00:50:12.700

JC: I am not so aware of this. JC: And I think often, I can think of–of places where I've encountered this JC: outside of academics. JC: It's often a little bit more blatant in those situations, but

00:50:12.700 - 00:50:28.300

JC: to be honest, I can't think of that many at the moment JC: that have happened while I—in–in the academic settings I'm thinking JC: of. That definitely does not mean that they don't happen. JC: I don't want to dismiss anyone's experience of this.

00:50:28.480 - 00:50:44.640

JC: I just think that I have a remarkably low awareness JC: of when this does happen. JC: Some of my—some of the—I JC: also have a remarkably bad memory of when—of recalling when these events happened.

00:50:44.660 - 00:51:01.760

JC: I remember having a conversation with some of the other Asian American faculty at Rice JC: and remarking on something that felt a little strange. And they said, "That's–that's definitely evidence of bias." But even now, and this was not too long ago, I–I actually don't remember

00:51:02.270 - 00:51:18.920

what exactly we talked about. And I'm not sure if this is just [laughs] weird coping mechanism or me just–just losing—just not remembering enough as I–as I get older. But yeah,

00:51:20.030 - 00:51:36.180

I can't think of specific examples right now. I will also say that at least in my particular field, my field tends—so, the field that I work in, the subset of these high order discontinuous

00:51:36.180 - 00:51:54.720

Galerkin methods that I focus on, it's a relatively small and, I think, close community, and at least as far as I can tell, it's really healthy community, really welcoming, really supportive of, say, young researchers and–and new

00:51:54.720 - 00:52:08.880

people coming in. And I think for that reason as well, I–I think it can be harder—it's harder to find these—I haven't experienced as many issues, I think because this was

00:52:08.880 - 00:52:23.970

a healthy community. But I do know a lot of—several colleagues who work in communities that are, I think, less well adjusted where they have faced a little bit more—they have faced more challenging

00:52:24.480 - 00:52:41.530

circumstances due to their ethnicity and background. KP: Alright, and picking back—or piggybacking off of that, so what do you think is your view KP: of, like, Asian American representation in general in your field? JC: I think that there's not a lot of Asian Americans in applied math, believe it or not.

00:52:42.220 - 00:53:00.100

JC: There JC: is—we have a member of our department, Richard Tapia, who focuses a lot JC: on–on issues facing underrepresented minorities in STEM. JC: And I think it was kind of an eye opening experience to me when one time he just during

00:53:00.100 - 00:53:17.790

JC: a talk, I think he–he pointed at me and said, "Asian Americans are underrepresented," JC: and I thought, "Huh, that's...kind of odd." But there's a little bit of truth to JC: that in that I—you do see JC: a–you do see a decent representation among East

00:53:18.150 - 00:53:35.010

JC: Asian academics at the–at universities and in JC: research positions, but I think especially among faculty, there JC: aren't as many Asian Americans that I know. I can think of—I think at Rice, I know that there's,

00:53:37.180 - 00:53:54.250

I believe, two others that I'm aware of, but they're older than I am, they're full professors. A lot of the–the–the Asian colleagues that I have are first generation, I'm not entirely sure—So for

00:53:54.250 - 00:54:12.120

me, it's–it's a little bit of a strange thing being an Asian American in academics, I think we run into a lot of Asian American students, but we don't necessarily have a lot of them go into academia and I'm-I'm not sure why.

00:54:12.130 - 00:54:29.530

So whenever I meet another Asian American in applied mathematics or just in—just at an acad-academic function, it always strikes me that's that's a little bit more rare. So. I would-I would like that-I would like that to change but I think to do so,

00:54:29.560 - 00:54:40.900

I'd first have to understand exactly why that is the case. KP: Right. That's interesting. KP: You wouldn't have expected that at all either. KP: I noticed that you've written a lot of journals and publications.

00:54:40.900 - 00:54:59.630

KP: Which–which of them do you think you're most proud of and have—or have impacted your KP: career the most? JC: There are a couple that I—so a lot of them that JC: I've—a lot of the publications that I think have stuck with me the most were the ones

00:54:59.630 - 00:55:17.890

JC: that—where-where they change the direction I was JC: going or they-they-they marked personal milestones for me. JC: So there's a 2017 paper on Bernstein Bezier, discontinuous Galerkin JC: methods, and I just remember that as being the first paper I got back where the reviews

00:55:17.890 - 00:55:33.790

JC: were just like, "This is amazing." And I-I—usually the reviewers are like,"This is JC: technically what he has done and here are the mistakes or the-the grammar mistakes and JC: the errors and the notational mistakes, and it's fine. JC: Publish it after some revisions." And this one review–this one paper actually

00:55:33.790 - 00:55:49.840

JC: had one reviewer that just thought, "This is exactly what we need to see," and it was a JC: really big confidence boost. JC: I'm not sure–I think–I'm-I'm not sure how true JC: this is for every academic, but at least for me, I–no one is immune from-from

00:55:49.840 - 00:56:03.800

JC: low confidence. And in-in your career at times, I think. JC: So hearing things like this are really helpful, they're a real big JC: morale booster. There was another paper that I published at the very end of my postdoc

00:56:03.800 - 00:56:18.780

where I think it was the first time I discovered an idea–did the analysis and kind of followed through on the idea completely by myself. And the first time someone does that, it's–it's a

00:56:18.780 - 00:56:36.670

real–I think that's a real formative experience. So there are times during a graduate project when you'll do a key part yourself, but often your advisor works very closely with you on trying to formulate the project and trying to guide it through and show what–show you what's going on

00:56:36.850 - 00:56:53.770

. But the parts that you–or indispensable and fundamentally associated or–that you really took ownership of, I think those are the parts that stick with you. But when you take an idea and just follow through it completely from start to

00:56:53.770 - 00:57:09.590

finish, I think that was a moment when I thought, "Okay, maybe I can— maybe I can do this for a living. Maybe I can do this by myself without—on my own, without an advisor or a collaborator or some other supervisor."

00:57:11.270 - 00:57:26.630

That one really changed my trajectory as well and–and influenced what I did for the next three years. And finally the 2018 paper that I–my first–so I think it's the paper with the most citations on my Google Scholar at the moment.

00:57:26.630 - 00:57:41.150

But there's a 2018 paper on something on entropy state conservative and entropy, stable, high order, discontinuous Galerkin methods, some technical name. But it was—the paper that changed my

00:57:41.150 - 00:57:55.880

career trajectory completely. It was—so there's–there's a really cool book called—actually, I'm going to grab it [laughter]. There's a really cool book called "The Structure

00:57:56.480 - 00:58:14.310

of Scientific Revolutions." This one by Thomas Kuhn. He's a philosopher of science, and I was reading it around the same time that I did this, and it just talks about the idea of a paradigm shift of what is possible. And I think that paper marked for me a paradigm shift in terms

00:58:14.310 - 00:58:31.950

of what I considered possible with these numerical methods, I always assume—so just for context, the challenge was that when we use these high order methods, they ended up being much more accurate than existing methods, which are—tend to be lower

00:58:31.950 - 00:58:48.510

order. So you have this much improved accuracy, but at the cost of kind of sensitivity. Sometimes your simulation would run and then they blow up unexpectedly and then you're out several hours or you're trying to figure out if that crash was from a bug or from some mathematical issue.

00:58:48.510 - 00:59:07.450

There was—it was hard to make these methods reliable, and I think it was just assumed since people had been trying to make these methods reliable for 20, 30 odd years since the mid 80s, it was just assumed at this point that, well, this is an issue you're going to have to deal with

00:59:07.480 - 00:59:21.820

until these methods came along. So I wasn't the one who developed the-these. There was some work by Mark Carpenter and collaborators at NASA, and then there was some work by some other faculty members, Gregor Gassner

00:59:21.820 - 00:59:35.440

and a few others in Cologne, Germany, and then some other folks also at Brown, Chi-Wang Shu. A whole bunch of people were involved in setting the framework for this, but they essentially all figured out somewhat independently that there is

00:59:35.440 - 00:59:52.900

a nice trick to making these methods not bulletproof, but much more reliable and stable from the get go. And I—my paper basically did a—I think, a technical extension of this to a broader class of—of discontinuous

00:59:53.380 - 01:00:11.020

Galerkin methods. But for me, it was basically a paradigm shift. This changes completely the way in which I try to—in which I was approaching these methods. It made it possible to be a lot more precise in terms of figuring out why my code crashes,

01:00:11.020 - 01:00:26.440

which is always really helpful. If something doesn't work, it's so hard to figure out why something broke if you don't have a rigorous mathematical theory behind it, and it really changed my opinion in terms of what

01:00:27.520 - 01:00:43.510

what we could do with these simulation methods going forward. And—it since 2018, I basically have been focusing completely on this class of methods: they've been the focus of my last two grants. All of my students have been–been working on this for the past, I think 3 or 4

01:00:43.510 - 01:01:00.970

students and they have—it's— yeah, it has been a world of a difference in terms of what I was working on. So what I worked on previously was a rather—I-I worked on wave propagation simulations which still have their own challenges, but a lot of the

01:01:00.970 - 01:01:18.170

issues that I was trying to solve were, I think, maybe more niche issues that people who used a specific numerical method for simulating things would face. But most—the broad range of people that were doing wave propagation simulations would

01:01:18.170 - 01:01:38.290

never run into these—for these—for this recent paper or—for this 2018 paper, I think it—it allowed me to make an impact in a field where there were many more open problems, like, stability and reliability of your simulations is a

01:01:38.290 - 01:01:55.970

much more significant issue, I think, in high speed fluid flows and conservation laws and fluid dynamics and it felt like a—it felt like a research area that had a lot more to work on for the next couple of years.

01:01:57.020 - 01:02:14.810

It didn't hurt—it didn't hurt that–that—so when I wrote that paper originally, I tried to formulate it in a way that was a little bit different from–from every other paper that had come before, and it nearly got rejected the first time around because I don't think anyone understood—I don't think I communicated very well what I

01:02:14.810 - 01:02:29.750

was doing. So after one very substantial rewrite, I went—the—the reviewers, I've never seen such a big change in the reviewer responses. Both reviewers at first were like, "I don't understand any of this, but it looks like you have some interesting results.

01:02:30.050 - 01:02:46.000

So maybe clean it up and tell us what's actually going on." And then after the revision, they were both saying, "This is a significant advance in the field." And I thought, "This is—it was nice to have kind of everything—every— all the things I felt with those previous

01:02:46.000 - 01:03:05.470

papers. The idea coming together really nicely by—with formulating the idea, having it come together, being able to take it from start to finish, and the confidence boost of having a good review." All of those were really present in this last paper in this 2018

01:03:05.470 - 01:03:15.280

paper on entropy, stable, discontinuous Galerkin methods. So those were probably the three most impactful in my mind [KP: Wow.] For me personally. KP: Yeah, that's great to hear.

01:03:15.700 - 01:03:32.790

KP: On a different wavelength with the rise of ChatGPT and other tools, KP: what kind of a role do you think could be contributed by AI in your field? JC: Man that is a—it's a really good question. JC: So I think AI in our field is

01:03:34.280 - 01:03:49.310

JC: ... It—it shows so much promise. JC: So I think AI JC: will—it—I think it's probably here to stay. JC: I don't work as much on that in my own group, but I do work with some other folks

01:03:49.310 - 01:04:05.060

JC: who work on machine learning-based approaches to simulations. JC: They call these data-driven methods for physics-based simulations, JC: and they are often so much easier to use and so much easier JC: to implement and require much less technical background.

01:04:06.140 - 01:04:21.420

JC: The thing I really like about AI is that it—I think it JC: lowers—it lowers the–the learning curve and the JC: bar for accessibility to a much broader audience JC: in terms of these computational simulations.

01:04:21.430 - 01:04:39.150

JC: This is an issue with my field that I–I–I think has kind of been an JC: issue for as long as we've existed, just that—the JC: most advanced state-of-the-art methods require—they require a JC: significant amount of background to really sink your teeth into them.

01:04:39.790 - 01:04:57.720

JC: So I think AI is fundamentally changing things, I JC: think the community as a whole is also finding that with JC: how easy AI is to use, they also have to balance this JC: with—it's still a little bit mysterious, so AI is a little

01:04:57.720 - 01:05:13.830

JC: bit of magic. JC: They have—the–the structure of neural networks that underlie AI JC: provide a much better approximation than all the JC: traditional approaches that we've tried, but because it's a little bit like

01:05:13.830 - 01:05:31.600

JC: magic, when it breaks, I think it's also hard to tell exactly why it breaks. So at least from what I can tell of the AI community, there's a lot of—there's a lot of observation going on right now where people are seeing just interesting patterns.

01:05:31.940 - 01:05:49.210

The first—I think the first wave of—of AI papers was basically showing like, what is possible. The next wave I thought was maybe showing "Well, it's not always realistic to expect the best case scenario," and this—the most recent

01:05:49.210 - 01:06:06.970

set of AI papers that I-I've been going over has, I think, been trying to tease out exactly why it is, or at least observe patterns. So when AI fails and when it doesn't, and if we figure that out and if there's a solid computational—or sorry, solid theoretical foundation

01:06:06.970 - 01:06:23.020

as explaining why this is the case, then I think it would—oh man, I don't know, it's—it would be utterly transformative for the field. I think—so I'm working with a group that is doing AI based

01:06:23.020 - 01:06:42.490

simulations of—of some complex reactive fluid, complex fluid flows, let's say, and they still do need numerical simulations like my field to exist, to provide data to—in which they can train and in which this neural network can learn.

01:06:42.490 - 01:06:59.480

But I think if—if you have a reliable AI approach to physics-based simulation, I think that really opens up the possibility of many more people using this. And this—you already see this at some–some industry—some

01:07:01.550 - 01:07:19.010

companies like Exxon, for example, they're shifting much more to an AI-driven approach. I think this is true for a lot of the energy companies in Houston. And I know—I mean, tech companies everywhere are basically investing in this. So, I'm sorry, I know that's a long way off from ChatGPT.

01:07:20.090 - 01:07:36.190

That's more general machine learning and AI in my field. In terms of ChatGPT itself, that—I think it's—it remains to be seen. I think it's—it's—I've

01:07:36.520 - 01:07:53.140

seen it transform the way in which we already write papers. So we'll use—well, we can–we can generate a pretty decent paper just by inputting in a couple of bullet points and asking ChatGPT to fill in the rest. It helps in writing, I mean, it can spit out a conclusion or an or—an

01:07:53.140 - 01:08:03.370

introduction fairly easily. It can even generate code. But I think the more technical things get, the harder it is for at least the current version of ChatGPT to really pick up on things.

01:08:03.910 - 01:08:23.800

So my students have experimented with it to just see, well, "Can you write a code that will do a numerical simulation of this or this or this," and often it'll spit out a code that does something, but not exactly what they ask for. It's really, I-I don't know, it's—it's hard to say because it changes so

01:08:23.800 - 01:08:39.790

quickly. My hope is that it becomes a tool. I'm teaching a programming class in the fall, and my hope is that I'll be able to discuss ChatGPT and encourage students to try to use it, but also try to illustrate some of the pitfalls.

01:08:39.790 - 01:08:58.690

If you generate, for example, programming—sorry, if you generate code with ChatGPT, maybe it doesn't—maybe it works like 90% of the time and then 10% of the time it generates like some small thing that's not entirely to spec. That's a very long way of saying I'm not entirely sure.

01:08:58.690 - 01:09:11.490

[KP: laughs] I'm excited to see. KP: No. Yeah, that's really interesting. KP: What advice would you give to Asian Americans of the younger generation that KP: think they're interested in pursuing a career in either STEM-based research or in

01:09:11.490 - 01:09:31.060

KP: teaching? JC: I think my JC: biggest suggestion would be figure out what works for JC: you. So, as Asian Americans, I think a lot of our

01:09:31.060 - 01:09:45.550

JC: families tend to—they—they want us to live up to JC: our potential. JC: They want us to be able to do the best that we can do. JC: Not everyone's going to, of course, be an amazing pro athlete or a

01:09:45.550 - 01:10:01.750

JC: successful doctor or a lawyer. JC: But I think most Asian American—most families JC: want their kids to do the best that they can. JC: And I think I would—I would say that really does—that really has helped in

01:10:01.750 - 01:10:16.840

JC: my career as well. JC: So I learn far better JC: from sort of simple, illustrative examples where you cut out most of the JC: mathematics to be honest, and you just try and get the main idea behind something.

01:10:16.840 - 01:10:35.650

JC: I work really well with codes that are often slower but easier to pick apart JC: that I can—that I can kind of go in and experiment and tinker with JC: and I think at a younger age I would have thought, JC: "Well, these are weaknesses, these are things I can't do without." And now that I'm

01:10:35.650 - 01:10:54.490

JC: a little more mature, I—I think it strikes me as, "No, these are just—this is JC: just the way in which I think." And I think it really is important JC: to—I didn't spend enough a lot of time learning about JC: myself until maybe the end of grad school and sometimes in

01:10:54.490 - 01:11:07.180

JC: my post-doc. JC: But learning about yourself, knowing yourself well also means that you JC: kind of know how you work best. JC: It means you can be kind to yourself when you are facing issues and struggling

01:11:07.180 - 01:11:26.560

JC: because maybe–maybe you're not an auditory or visual learner, maybe you're a JC: tactile or experiential learner, and that's okay. You can, of course, try to—I think as an undergrad while you're young, I think you can, of course, try to change yourself to see if you can

01:11:26.560 - 01:11:44.890

expand the ways in which you can be—you can learn and which expand your skill set. But I think it's also important to balance that with knowing there are just some things that you more naturally gravitate towards and if you can accept that part of—accept basically who you are.

01:11:44.920 - 01:12:00.190

So, first it requires figuring out, I think, who exactly you are, what–what you tend towards. And if you can accept all that, then I think it really is a very freeing way to—it really makes you feel much more free as you go into your career.

01:12:01.030 - 01:12:16.270

So, I wouldn't have spent as much time trying to become an amazing functional analyst in terms of my mathematical background, I know I'm not that great—so my advisor had a great story.

01:12:16.270 - 01:12:34.690

When I was applying for a postdoc, he wrote me a recommendation letter and said, in the letter, I—he-he told me what he wrote: he said, "He's not the best mathematician and he's not the best programmer"—and—but then he qualified that with, "He sees connections

01:12:34.690 - 01:12:51.310

between things." And it's really like I think back to that a lot because it's—it really does seem to be the thing that has helped me the most in my career, recognizing that, yeah, I'm not that great at the technical aspect of either the computation or the mathematics, but I am halfway decent

01:12:51.310 - 01:13:07.060

at making broad, intuitive connections and conspiracy theories between numerical methods, and that has served me remarkably well in my career. That's my main—main advice to future generations.

01:13:08.740 - 01:13:23.710

KP: Thank you for that. I noticed that you're involved in both the Society for KP: Industrial and Applied Math and the US Association for Computational Mechanics. KP: So can you share a little bit more about your role in both these organizations and how KP: you first got involved?

01:13:23.710 - 01:13:37.610

JC: Yeah, definitely. JC: So both of these are organizations that I was basically introduced to during either JC: grad school or my postdoc. JC: So my graduate advisor was more in the computational

01:13:38.090 - 01:13:56.390

JC: mechanics engineering community and that's much more USAC—USACM. JC: So, I will often go to their conferences—they have a US National Congress JC: on computational mechanics—and then I'll often also go to the Siam conferences JC: like Siam Computational Science and Engineering, which was introduced to me by my

01:13:56.390 - 01:14:10.250

JC: postdoc advisor. JC: So I mostly just attend conferences for USACM. JC: I haven't been quite as involved in the organization, but for Siam because a lot of JC: the department is also involved heavily—I recently

01:14:11.060 - 01:14:26.510

JC: took an officer position in our local Siam Texas-Louisiana chapter JC: where I'm just secretary. JC: So, this just involves going to the meetings, helping with the planning of our JC: annual conference, trying to take down minutes and sending out the—sending out

01:14:26.540 - 01:14:44.450

JC: emails, but it's nice to be able to–to give back and JC: see all the work that's involved with this annual meeting. JC: And it—,yeah Siam has really done—it's really been a JC: place that I felt like has been my academic conference home.

01:14:44.480 - 01:14:58.850

JC: It's always the conference that I'm looking forward to the most every two years when it JC: shows up. And so, being able to give back a little bit to JC: it as has felt great. KP: That's great to hear.

01:14:59.720 - 01:15:15.400

KP: What do you think about the state of math education in the US? KP: Because I do hear that, you know, compared to other countries, especially in Asia, we KP: often lag behind. JC: So I'm—not entirely convinced

01:15:15.430 - 01:15:32.000

JC: of of this, I-I–I JC: think—I JC: think...so I'm not a math JC: educator, first of all. I-I should probably specify that most of what I know is

01:15:32.030 - 01:15:49.520

JC: hearsay and my own—my own guesses as to what's JC: going on. But my experience JC: with–my experience has been that JC: we might lag behind in terms of some metrics, like definitely there

01:15:49.520 - 01:16:06.030

JC: are students in East Asian countries or even European countries that do JC: score much better than we do. JC: And there are, of course, issues of inequality and access JC: in our education system that are definitely seen very strongly in

01:16:06.030 - 01:16:23.820

JC: mathematics. But I think the—I JC: think our math education system, when it works, I think it's JC: a—it–it's a long term payoff. JC: So I don't–for example–I don't know Common Core that well and

01:16:23.820 - 01:16:40.170

JC: I–I don't know well enough to really debate about the intricacies, but JC: —from what I understand, it's aimed at trying to introduce JC: —the "why" into mathematics. JC: When I learned algebra, I learned essentially a set of rules.

01:16:40.770 - 01:16:55.920

JC: I think for the most part, if those—those seem to work JC: for me, but there were concepts in, in high school and middle school that I thought JC: it would have been nice if we had gone a little bit more into the process of JC: mathematical thinking.

01:16:57.110 - 01:17:13.660

JC: My experience in higher education has been that JC: people who are really good at mathematics in high school are not JC: necessarily that enamored with mathematics in college, I think JC: because it's a very different beast.

01:17:13.810 - 01:17:30.570

JC: Mathematics in college is—I mean, sometimes you don't even see numbers in a JC: class, but it's—it becomes so much more of a conceptual beast and JC: an intuitive way of thinking, that it almost strikes me JC: as being closer to philosophy or art, at times.

01:17:31.620 - 01:17:50.720

And I think Common Core, from what I can tell, is trying to introduce some of that same intuitive, conceptual thinking into lower-level mathematics. I'm not sure if this is the best way to do it. I—from what I can tell with myself, I often do better learning the

01:17:50.720 - 01:18:04.040

rules and then building an intuition around them. But I appreciate that this is—kind of—this is, I think, some of the strength of American education when it works.

01:18:05.500 - 01:18:20.440

I think I should probably stop here and say that I just don't know the area well enough to really make more comments. But from my experience, at least at the higher education level, we have good students from all sorts of backgrounds.

01:18:20.440 - 01:18:34.090

From East—from people who went— students who went to college in East Asian countries and have a very different background. They often have different strengths. And students who went to coll—went to school in the US, they have

01:18:34.360 - 01:18:45.160

a whole different set of strengths. I think one of the things you learn very quickly with mathematics is that there's not exactly a right way. There's not a unique right way to do something.

01:18:45.520 - 01:18:59.680

There are many right ways. And I would say for math education, I would–I would conjecture the same is probably true, that there's a lot of different ways to become good at math.

01:19:00.560 - 01:19:14.670

It just depends on what you exactly mean by good at math. KP: That's an interesting way to look at it. KP: So do you think, like, people can be, like, born naturally good at math or coding or KP: other STEM-related subjects?

01:19:18.590 - 01:19:34.830

JC: I'm going to say yes just because I think I've met some people JC: who, if they weren't born good at math, then they—they got on board really, really JC: quick. But I—did you ever watch Ratatouille? KP: Yeah, it's one of my favorite movies [laughter].

01:19:35.510 - 01:19:52.290

JC: Same. But it's I think—the—I think the the end, the–the main JC: theme, like, "Anyone can cook," and what that means, like JC: a—not necessarily anyone can cook but a great cook can come from JC: anywhere—kind of applies to mathematics too.

01:19:52.310 - 01:20:08.980

JC: So you have people who are super talented from a young age, but you also have really JC: late bloomers. The mathematician who proved the twin JC: primes conjecture, I think he was, JC: well into his 40s, if I'm not mistaken, and essentially

01:20:09.790 - 01:20:27.310

JC: working as an instructor at a smaller school and JC: accounting for Subway on the side, if I remember correctly. JC: There's a Korean mathematician whose name is–is—I'm JC: missing right now—but if I'm not mistaken, he won the Fields medal, the–I think the

01:20:27.310 - 01:20:40.360

JC: Nobel Prize of mathematics. JC: But, essentially took some time off during college and was–was a JC: real late bloomer. JC: I think—yeah, I think there are

01:20:40.360 - 01:20:58.960

JC: people who—for whom certain types of mathematics just come very JC: naturally to them. But I'm a firm believer that anyone can be good at math. JC: Sorry—I should say, I'm a firm believer that if anyone wants to become good at JC: mathematics then they can, it's just a matter of w

01:20:59.860 - 01:21:14.530

JC: hat you consider mathematics. Mathematics can be highly technical. It can be numbers and formulas and and kind of a more rigid structure thing. It can also be really loose and flowing, and even the mathematics in

01:21:14.530 - 01:21:30.100

different countries kind of reflected this. So, there were some—there are some histories of mathematics and logic and philosophy that talk about like brawls or conflicts that would arise between like the French School of Mathematics and the

01:21:30.100 - 01:21:46.660

German School of Mathematics, where one is like, "No, you have to have everything postulated and rigorous," and the other one is like, "No, it should be flow—it should be, like, free-flowing and artistic and and—and beautiful." And I think both are possible, both are—both are true, both are mathematics.

01:21:46.780 - 01:22:04.680

So I'm going to weasel out of that question by saying I think it depends on how you define mathematics, I think—I think anyone –can be—can be good at it if they—if they are willing to

01:22:04.680 - 01:22:17.440

change how they—how they think of mathematics. KP: Wow, that's such an interesting way to think about it. KP: I think I'm going to shift to a couple of questions here that are more about, like, KP: building a portrait of you and who you are as a person.

01:22:17.470 - 01:22:28.030

KP: [JC: Sure.] So how would you identify yourself in terms of ethnicity and KP: nationality? JC: Yeah, I would say I'm Chinese American. JC: Asian American.

01:22:28.870 - 01:22:41.260

JC: My mom is from Taiwan. JC: My dad is from Hong Kong. JC: But I think I—I think I generally just—I-I generally JC: resonate with the Chinese American experience.

01:22:44.000 - 01:22:59.020

KP: How would you describe the Asian American community in Houston? JC: Oh, wow. JC: It is—it is more JC: closely connected than you might expect.

01:22:59.030 - 01:23:16.340

JC: So I think I grew up within a very specific subset JC: of the Asian American community, the Christian Asian-American community. JC: I always got the sense that, if there was another JC: Asian American kid who went to a church, that we

01:23:16.340 - 01:23:33.530

JC: were—we were separated by at most, like, one connection. JC: Like, there would always be like a friend-of-a-friend or like, "Oh, you went to JC: that camp or that that event or—or oh, yeah, I know, I know this—I know your JC: church." It always felt like it was not that hard to make one

01:23:33.530 - 01:23:48.310

JC: pers—to, to basically talk to a friend who knew someone else. JC: It it–felt like a very closely connected network. KP: Wow, that's so interesting. KP: Can you share about your current family life with us?

01:23:48.340 - 01:23:57.610

JC: Yeah, sure. JC: So–my brother and I—my brother and I JC: still live in Houston. JC: He moved back recently.

01:23:58.350 - 01:24:14.050

JC: My parents still—well, JC: they spend some time in Houston, some time in California, and it's always really nice JC: to—to see them when they're here, and I try to visit them in California whenever I JC: can as well.

01:24:14.590 - 01:24:30.400

JC: We still try to do family calls. JC: It's a—it's a tradition we started during the pandemic when we just JC: couldn't see each other, that we would just do these Zoom calls every—every JC: Sunday evening, and that's been a really nice—it's

01:24:32.640 - 01:24:47.880

JC: been a really nice tradition that we've kept–kept up. JC: It's—I still lean on my parents JC: for, I think, everything life related. JC: My mom is an amazing realtor.

01:24:47.880 - 01:25:06.570

JC: My dad knows I think all the technical stuff I could ever ask for about home JC: renovation or–or accounting or taxes, just the stuff JC: that—just the administrative stuff that you have to do in life. JC: And so I am so grateful for all their help in–in

01:25:08.100 - 01:25:24.020

JC: all of this. We—yeah, I JC: think we try our best to stay connected to each other JC: and, yeah JC: . I love my family.

01:25:24.950 - 01:25:39.770

KP: [Laughs]That's great to hear. KP: Can you tell us about some of your hobbies or interests outside of your career? JC: Sure. They change every couple of years. JC: So I—I still very

01:25:39.770 - 01:25:55.880

JC: much love music. I go to a wonderful church called Holy Family HTX JC: that's an Episcopal church downtown. JC: And I was lucky enough to—I'm lucky enough to play with them JC: whenever I can, so it gives me a chance to stay connected to that musical

01:25:55.880 - 01:26:14.420

JC: side, and they have such a wonderful set of musicians at that JC: church. I used to build bikes JC: and I don't as much anymore, but I still have several of the bikes that I've JC: built and it's been so much fun to—to ride them whenever it's

01:26:14.420 - 01:26:28.380

JC: possible to ride them in Houston. JC: So, it's a little hot right now but–but I've enjoyed getting to know, like the JC: bayou systems in Houston. JC: It always feels like, I mean, despite the fact that I think I've lived here for—oh

01:26:28.380 - 01:26:47.670

JC: gosh—way too long, it still feels like I'm discovering things about Houston. JC: We—I just—we just discovered the bayou trails maybe during the JC: pandemic. I didn't even know they existed before that and they are fantastic. JC: I—[laughter] my brother

01:26:47.670 - 01:27:04.700

JC: and I, of course, still, we just were both fans of the same JC: animes and same video games. JC: And it's—it's been good to—to JC: just—it's always good to just talk with him and catch up and see

01:27:04.700 - 01:27:21.470

JC: like, "Oh, did you see that last episode of this or that last—did you play the JC: most recent version of-of whatever?" So that's JC: always a great way for me to decompress. JC: I've—I've enjoyed animation and video games, I think,

01:27:21.650 - 01:27:40.820

JC: like most other Asian American boys, probably since I was very JC: small. And more recently I've actually gotten really into electric JC: scooters. I'm trying to—I actually commuted to JC: the office on an electric scooter and I try to do so whenever it's not raining or

01:27:40.820 - 01:27:57.620

JC: whenever I don't need to carry something. JC: Just saves on gas, a lot more flexible, better for the environment JC: and feels kind of nice to—it feels like JC: a much safer version of a motorcycle to me.

01:27:58.960 - 01:28:14.270

JC: [KP: That is super cool.] So yeah, these are a couple of the hobbies. KP: That's cool. How would you describe, like, the Asian American community in Houston? JC: I think we talked about that one JC: already.

01:28:14.290 - 01:28:22.720

KP: Right—Right. Sorry. KP: Do you want to expand a little bit on, like, maybe. KP: Like—how about—like broader—like in Texas in general? KP: Or how about, like, the whole of the US?

01:28:22.750 - 01:28:38.740

JC: Yeah, sure. JC: So I—again, I'm not really sure how JC: broadly this-this conclusion holds, but I get the sense that the Asian American JC: community in Texas is at least through the Chinese

01:28:39.100 - 01:28:56.060

JC: churches, fairly well connected. JC: So a lot of my friends from Dallas or Austin, they would JC: still be about one connection away through some random person in the Chinese church JC: and, yeah, I think it'll turn out often that if I meet

01:28:56.060 - 01:29:10.900

JC: someone who went to a Chinese church in one of those other cities, I'll realize that they JC: know a whole bunch of my friends as JC: well. I think JC: in terms of the—a broader Asian American community

01:29:11.440 - 01:29:29.840

JC: in America, I think it's—from what I can tell, it's kind of coming JC: into—it's-its—I think it's becoming more prevalent. JC: I think they're starting to—there is— there always has been a strong JC: activist and sort of self-aware movement among

01:29:31.040 - 01:29:44.690

JC: AAPI folks in Asian America. JC: But I think I feel like I've seen—it feels like I've seen more JC: discourse about it. JC: Nowadays, I feel like along with that discourse has come the space to maybe

01:29:44.690 - 01:30:01.550

JC: talk about individual or differences between different Asian JC: subgroups. So my partner and I, we really enjoy watching cooking JC: shows. Padma Lakshmi's Taste the Nation is, is JC: fantastic—and what we've noticed is

01:30:01.550 - 01:30:16.370

JC: just an increased emphasis in cooking shows like this and–and others, on not JC: just Chinese food, it's not just Yan Can Cook anymore, but it's JC: starting to become, like, individual parts of China, Fujian food, Chongqing JC: food.

01:30:16.700 - 01:30:33.780

It's—and you kind of see, like—I'm starting to see more history of Chinese—like, of Chinese people in America, like, the different waves of immigration and kind of how they've shown up in different places as well as increased emphasis on non-Chinese non-East Asian

01:30:36.300 - 01:30:53.130

—non East Asian, Asian American populations: Filipino, Vietnamese, Korean, like all these—all these little subcultures that have been kind of lumped together for a while. I'm starting to see increased emphasis on each of their unique individual characteristics and how they thrive in different parts of the

01:30:53.130 - 01:31:10.500

country. So that's been really encouraging. And seeing this representation, I mean, on TV, even in like some of the-the animated shows or, like, or random cartoons that we'll watch, it's it feels like things are, like, the representation is getting better and

01:31:10.500 - 01:31:27.270

better. I think one thing that I haven't really—I hadn't really appreciated as much is the role of—the way in which different Asian communities around the country might feel different.

01:31:27.270 - 01:31:44.820

So have several cousins in Canada, for example, and there's very strong immigrant Asian-American community up there that feels very different than the Asian-American community that I know in Houston, which again, in turn, feels very, very different from the Asian-American community that

01:31:44.820 - 01:32:00.600

I've-I've seen in LA. I feel like I'm-I'm always in awe in, kind of, the–the political awareness and the—the activism and the–the sort of intelligence of discourse that I see coming out of, like, of—of

01:32:02.250 - 01:32:19.910

western—the western US area. I feel like—I'm not sure if this is entirely true—but I feel like in Houston at least I see a lot more children of first generation immigrants, and so to me it seems like there's a kind of unique—a uniquely

01:32:21.220 - 01:32:39.980

large crowd of—I guess we're second generation Asian Americans—in Houston and in Texas—I don't know Canada well enough—they—I'm sure they have their own experience as well, but it feels—I guess to connect it to what I said

01:32:40.130 - 01:32:58.580

before—it feels like—it feels like being seen more and more, like—like it's not like we—I feel like it used to be–to be seen just meant someone recognizes, "Okay, Asian Americans are—or AAPI folks are important

01:32:58.580 - 01:33:13.260

in this aspect." And more and more it feels like it like—it feels like being seen beyond just the AAPI label, and that has been really cool. KP: Right. That's such a great way to put it. KP: I know a few times you've mentioned, like, Christianity.

01:33:14.280 - 01:33:27.270

KP: Was this something that you kind of grew up with or something that you kind of discovered KP: for yourself? JC: Yeah. I-I grew up with it. JC: I think—[laughs] I'm not entirely sure how true this is—but I think my mom s-sent us to

01:33:27.270 - 01:33:42.890

JC: church because that is where the "good kids" hung out. JC: But I was really involved a lot as JC: a–as a kid and all through college. JC: I think I—I—I grew up

01:33:42.890 - 01:34:02.120

JC: evangelical, I—I don't think I identify as that anymore—and JC: I think throughout—throughout graduate school, I spent a lot of time, time trying to JC: figure out, "Well, I have some questions about the JC: faith, what happens now if I no longer believe in certain

01:34:02.120 - 01:34:16.190

JC: aspects of–of the Christianity I grew up in? JC: What do I replace that with? JC: What—what how does that change the way in which I interact with my JC: faith?" And I think the churches that I've–I've been

01:34:16.190 - 01:34:36.120

JC: at since have–have reflected JC: that. So I went to a church in Austin called Vox JC: Beignet, which I think focused a lot on, well, JC: the role of art in in Christian life

01:34:36.120 - 01:34:54.420

JC: and was a lot more progressive. JC: It showed me a different Christianity than I think, the one that I grew up with JC: . The church we have here in Houston— Holy Family, HTX—I think is very similarly so, it JC: reminds me a lot of it and in a lot of ways I think I used to be a lot

01:34:54.420 - 01:35:12.110

JC: more certain about my faith—as—when I was growing JC: up. I think after—after college JC: and–and going to grad school, I had some questions JC: that–that made me much less certain.

01:35:12.110 - 01:35:29.180

And I don't think that uncertainty has really ever gone away, but I think it's been a little bit replaced by—by the faith traditions I'm—I try to be a part of, by—by them trying to see—trying to see beauty in–in the faith.

01:35:29.190 - 01:35:48.170

So I think a lot of what I grew up with was a faith that said that—a faith that—a faith that I interpreted as being valuable because it was correct. There was a lot of I was really interested in apologetics and–and just

01:35:48.170 - 01:36:04.750

proving that I was right. And after I didn't really know if I was right or not, then I think it—of these other churches showed me how you can try to seek, well, beauty in terms of—in

01:36:06.130 - 01:36:23.710

terms of art, in terms of the causes that you champion, in terms of the ways in which you try to reach out to other people and to to make a positive impact in their lives. I think—so I think my relationship with faith and Christianity has changed

01:36:23.920 - 01:36:41.670

a lot over the the past ten years, but it's felt more stable, like this is kind of—I think it's—it's—I feel like I'll probably—I feel like I

01:36:41.670 - 01:36:55.950

know a little bit more with the type of faith that I have now after spending time at Vox Beignet and at Holy Family. KP: That's great to hear. KP: Speaking of Holy Family, how did you first, like, get–get initially involved in them?

01:36:55.950 - 01:37:11.880

KP: And like, why did you decide to choose this particular, like, community KP: or congregation? JC: Yeah. Very simply put, Zachary McKenzie from—who moved to Houston from JC: Austin before us, went to Holy Family, and I thought, "Okay,

01:37:11.880 - 01:37:30.080

JC: well, we'll try it out." We had tried a couple different churches beforehand and not JC: none of them seemed to be a perfect fit, and the Holy Family just felt, I think, JC: immediately right. There—I mean—I—so apart from the art and everything, I think they

01:37:30.080 - 01:37:43.430

also had they—they had a lot of people, I think, who had been burned by the church before. And I think that creates a kind of unique community that centered a little bit around grief and–and sadness.

01:37:43.430 - 01:37:59.330

And I think there's a seriousness to that that is a little hard to replicate in some other churches. So thank you, Zach, for telling us about this place. And pretty much from the very first

01:38:00.620 - 01:38:16.640

time I visited, I thought, "This seems like a good place." I went and talked to the music leader afterwards, Luke, and said, "I love—I love what you're doing. Y'all sound great." He asked, "Do I play?" And I said, "Yeah." And he's like, "Do you want to play?" And starting from the second week I visited, I started playing with them.

01:38:16.640 - 01:38:26.840

So, they're a real welcoming place. KP: That's great to hear. KP: Like what is the extent of how you're involved in it? KP: Is it like—I know you mentioned you play with a music group, do you, like, attend

01:38:26.840 - 01:38:44.490

KP: services or any sort of, like, Bible studies or things like that? JC: Yeah. So I—I play with a music JC: group when I can, when I'm—when I'm free, I—I JC: attend one of their dinner groups, which are these just kind of informal get togethers

01:38:44.490 - 01:39:01.890

JC: with other couples or members of the church. JC: And I try—there are several events that I really like attending. JC: Like, they hold certain film screenings at times that I really enjoyed. JC: They—let's see, they had a pickleball event that I wish I had

01:39:01.890 - 01:39:18.200

JC: gone to. JC: I think—yeah, I-I'm not involved in—in JC: like the leadership or the sort of direction. JC: I think that's a—I probably don't have enough time to really sink my teeth into

01:39:18.200 - 01:39:30.470

JC: that, but it's definitely JC: an—it's—it's definitely a creative outlet for me. JC: And, yeah. KP: That's great to hear.

01:39:30.860 - 01:39:48.320

KP: Have you ever experienced like, a miracle or an answer to a prayer, or what are some other KP: defining moments that you think you've had in your journey of faith? JC: So, short answer, I don't think so. JC: I feel like I was even as—even as a much more—even

01:39:51.480 - 01:40:08.670

JC: as a much more evangelical kid, I don't think I ever really JC: felt, like, a direct answer. JC: It was always a little confusing to me when someone would say, "God spoke to me," because JC: I was like, "I don't know what that means." I don't think I've ever experienced this.

01:40:11.030 - 01:40:29.650

JC: So, not in that sense, I think. JC: I think more recently, I've—I've tried to understand JC: miracles and prayers as—in a different JC: way. Miracles as being mean—something that might seem

01:40:29.650 - 01:40:47.950

JC: ordinary. So I mean, some folks have—there are some JC: authors who I've heard who talk about miracles as just being, well, an extra few JC: months with, like, with a sick family member. JC: Nothing real special and nothing that is life changing, but it gives you time to spend

01:40:47.950 - 01:41:06.820

JC: with them. I think—I think there are ...probably JC: miracles I don't even notice. JC: Yeah. Unfortunately, no, JC: I don't—I don't think I really have experienced that as much myself.

01:41:08.170 - 01:41:30.640

KP: All right. Is there anything else you'd like to share with us before we wrap this up? JC: No, I think—well, thank you very much for–for doing this. JC: I've watched a couple of these and these are—and I'm really glad the Chao JC: Center is–is–is–is spearheading

01:41:30.640 - 01:41:40.360

JC: this. So, [KP: Right, yeah.] thank you for your time. KP: Again, thank you so much for interviewing with us. KP: It was such a great experience. KP: It was so wonderful to hear about your life and some of the things you've done.

01:41:40.900 - 01:41:48.670

KP: Have a wonderful day. KP: Please don't hesitate to reach out to me if you have any other questions. KP: And again, thank you so much. JC: Thank you, Karina. And thank you.

01:41:49.090 - 01:41:51.760

JC: Yeah, it's my pleasure. JC: Take care.