Episode Title: Professor Nikil Dutt of UC Irvine on Serendipity, Bright Students and Good Relationships.
Episode summary introduction: Professor Dutt believes exciting research comes from a combination of serendipity, bright students and good, collaborative relationships. There is more.
Professor Nikil Dutt is the Chancellor’s Professor of Computer Science, EECS and Cognitive Science at the University of California Irvine.
In particular, we discuss the following with him:
Topics discussed in this episode:
Our Guest: Professor Nikil Dutt is the Chancellor’s Professor at University of California Irvine with appointments in Computer Science, EECS and Cognitive Science Departments. Professor Dutt is a graduate of Birla Institute of Technology Pilani with a degree in Mechanical Engineering. He then received his MS in Computer Science from Penn State University and a PhD in Computer Science from the University of Illinois at Urbana-Champaign.
Memorable Quote: Prof Dutt: “Academia is not for the faint of heart”.
Episode Transcript: Please visit Episode’s Transcript.
Transcript of the episode’s audio.
Venkat Raman 0:06
Welcome to the podcast, college matters, Alma matters. We podcast, personal college stories, and all things college, check us out and subscribe at alma matters.io, forward slash podcasts.
<Start Snippet> Prof Dutt 0:21
If I were to put it in a nutshell, it's about being able to, it's like a small entrepreneur where you are expected to run your own, quote unquote, research business, you're, you're able to garner research funding to support number of students, to address questions that are interesting. And also, and not just raise funding, but use that as a mechanism, yeah, to deliver some outcomes in terms of new advances in terms of new discoveries.
And not only do that, but be able to communicate that with others. It's not enough that you do something but you'd have to be able to, you know, let people know, you know.
Professor Nikil Dutt is the Chancellor’s Professor of Computer Science at University of California Irvine.
Professor Dutt believes exciting research comes from a combination of serendipity, bright students and good, collaborative relationships.
This is not the whole story.
To take advantage of an opportunity requires preparation, academic rigor, perseverance and not just openness to, but the pursuit of ideas across disciplines.
Over the last 3 decades, Prof Dutt has done just that.
We caught up recently with him to hear his story.
Here’s Prof Dutt!
Prof Dutt 1:58
Venkat Raman 1:58
Hello, Professor Dutt. Welcome. Welcome to our podcast.
Prof Dutt 2:05
Fantastic. Yeah, thanks for making the time on the last day of 2020
Prof Dutt 2:09
Venkat Raman 2:10
And it's been quite a year. So very well.
So we are, you know, as we spoke, we're chronicling stories of alumni and faculty and admissions officers around their college experiences and about colleges and with the idea that this would be sort of a way to inform and inspire aspiring students world over. So. So thanks for making the time here. And I'm sure your story would be both inspiring and interesting to our audience. So thanks again.
Prof Dutt 2:52
Very well. So I think maybe the best place to start is, you know, maybe a brief background, professional background, and then we can talk about your journey to academia. And I think that would be quite interesting. And then we can spend some time on Irvine, UC Irvine to be specific.
Sure. So, I studied at BITS Pilani in India, I got my bachelor's in mechanical engineering in 1980. And although I was in mechanical engineering, I was always interested in computing. So I hung around the computer center that was even more interested in programming.
After I graduated, I joined TCS Tata consulting services for a year in between 80 and 81. And that was kind of interesting experience. I was ,I was not challenged, that was quite boring, frankly, I expected more. It was really boring work doing COBOL programming.
So I decided to apply for a graduate program for a master's in computer sciencein the US. And so 1981 I came to the US, and I was I got my master's at Penn State University in that during that process, you know, I initially thought I'd jump off and get a job, right at the end of my master's, but then I got I got very excited with some of the work I was doing during lectures. And so that led to think, Hey, why don't I explore, you know, a PhD? Sure, that led to joining University of Illinois at Urbana Champaign in 1983.
But all along, I was thinking I'd still go out and become, you know, a technical contributor in industry. That was the original goal I had when I started my PhD, but interestingly, as I started doing my PhD, I got more interested in doing research. Sure. Looking at options when I graduated at that time, you know, there were options where I could do, I could pursue research career in industry, you know, like IBM Research Labs. So there were a whole bunch of research labs then. So.
But I think I, I felt that I, you know, academia afforded me the opportunity to do what I wanted to pick the topics that I was excited in, to change directions and learn and grow. So that led me to an academic career.
So I started at Irvine at 1989, a bunch of interviews. And so I've been, you know, on the faculty at, in computer science at Irvine since 1989. So that's my journey, and I've sort of risen through the ranks.
And so and, you know, also the research that I've been doing has, has changed every five or so years, there are new things that I'm learning from students, from colleagues. And so it's been a very rewarding and enriching experience. So I am enjoying myself. And still, I hope to be active and continue to be active anyway.
So that's sort of a summary of, you know, where I am, and how I got here, I guess.
Venkat Raman 6:28
I think you mentioned a little bit about your decision to come to the US. So maybe a little bit about your experiences at both Penn State and Urbana Champaign, mainly from a transitioning point of view.
And, you know, and maybe, maybe we can sort of talk about that, and then let's dive into some of your current, I mean, not current, but how you kind of came to the various interests in research over the last couple of decades?
Sure, yeah. So I think, you know, the transition from, let's say, my education, undergraduate education at Pilani transition to masters probably wasn't that different, because we were still running semesters in Pilani. So the education systems in some sense, were similar in format. And similar in terms of evaluation. So I think that was not very different.
Of course, the main difference with graduate education is you're doing a lot more of thinking on your own to do you know, as we all know, it's not just, you know, reading a textbook or something. So it's a lot more open. So I think that was, that's something that doesn't matter where you come from, I think there's this big transition from doing your courses in an undergraduate environment to graduate work, where there's a fair amount of independence, and a fair amount of project work and research research in the sense of being able to assess what the state of the art is, and comparative analysis and identify trends, that sort of thing.
So I think that was interesting and different, I would say, rather than very self contained courses as an undergraduate, where you have a curriculum, and you have a course schedule, and you know, you, you can expect almost every week, what you're doing, you're quizzed on, on that content.
Of course, even in graduate education, some of the introductory courses are very similar. They are well defined, but as you, you know, as one moves through the program, you're getting to more advanced topics, then the topics are quite new. And so there's, you know, the courses themselves are a little more flexible in terms of content and the expectations in terms of what you expect it to do.
Venkat Raman 8:58
So any big differences, any big difference moving from Penn State to Urbana Champaign? I mean, was that a continuation, or did you feel like it was different?
Well, like, you know, the Masters again, you know, it's sort of gradations of how open the program is, I would say, so, okay. You know, the bachelors is very structured.
In the Masters, it's somewhat structured, but as you get to maybe doing a thesis, if you choose that option, then of course, there's some level of independence. And then the PhD is, you know, the funnel opens up and you're looking at a lot more openness in terms of expectations. And so I think there's definitely a transition academically in terms of what's expected and how one needs to move through the program.
And there's a fair amount of luck involved, frankly, of course, because, you know, especially for the PhD, yeah, you know, trying to identify Topic aligning with an advisor, finding funding, you know, all these things are, you know, experience varies tremendously, even in computer science or engineering, surely individual to individual from school to school.
So for, in my particular case, I think the transition from Penn State to Illinois is actually very good. I think Illinois had an extremely vibrant graduate program with a large PhD student body. So I think, I think was very active so that I benefited from that it was very large, as opposed to a small, sort of boutique PhD program.
So I think that was good for me. Of course, it can vary from student to student, some students might prefer sort of like the trade off between a small private college versus a large public school.
Venkat Raman 10:54
Prof Dutt 10:57
So for the PhD, I think the transition was not that different, in some sense, because I went from one large state university system to another large state university system. But in terms of the programs, the computer science program at Illinois, you know, is very large and very high quality. So I think I think I benefited from that.
Venkat Raman 11:22
So, so what, what captured your interest in terms of research? And what, what did you end up pursuing?
Yeah, I think, you know, the one word I would say is serendipity. All along, because it's always been the case that maybe as a child, I was quite curious. So I like to look at new things.
And so when I was at Penn State, I, this was in the early 80s, when the Mead-Conway revolution happened, there was this book that said, you know, that outline, a structured way in which you could design large scale electronic circuits. And so that was very inspirational to me.
So, and then the idea that, you know, we could, in essence, compile behaviors or abstract representations into circuits compiled into hardware, so hardware compilation, was something that, you know, in early 80s- 81, or so became very, very exciting topic. And so I think I got taken by that. And so that's what has swept me away.
Because I was not an electronic engineer by training. Right, right. I mean, I had taken some courses, my undergrad, but there was not an expert in that area. But then I was more interested in software and compilers, runtime systems, and so on, but then the idea that you could use those tools to design complex hardware circuits was very exciting.
So that that probably is what piqued my interest when I was in Penn State. And that led to the transition to Illinois.
Venkat Raman 13:02
So now, you choose a career in academia, you mentioned that it seemed more research kind of grabbed your attention. And, so tell us a little bit about how that, you know, you balanced that with teaching? And how was, how was that sort of the overall equation of what you do?
Yeah, that's, that's a good question. I think, you know, there's the word on the street is, if you're not familiar with how research works, most people think, Oh, you know, these research, faculty are busy just doing research and teaching something, you know, there's that kind of perception.
But on the other hand, we've found over the years, and, you know, I'm probably an example of that, the folks who are passionate about the research are also passionate about sharing that, that education to new generations of students, right, and that actually makes them very good teachers and very compelling teachers.
And so I think so, in my opinion, I think I think it was not, I mean, I wasn't intent on just your teacher, I don't think that would have been a career choice for me. Right? You know, just being a lecturer at university or school that, that essentially was designed to just educate students at the undergraduate level, I think I, I wouldn't have chosen that path.
But, but having the ability to do research and also share that passion, with with students on topics related to that, is something that I enjoy and, you know, as part I'm in a public university, so we are not only required to teach but expected that the quality of what we do is high in terms of both teaching and research.
So you know, I do have a full load of teaching as with any other faculty member in computer science. I typically teach one or two undergrads, we run a quarter system. So yeah, teach one or two undergrad and one or two grad, depending on the mix, you know, every academic year.
That's, and the courses vary, you know, over the years, I think we tend to teach the courses that we are excited about, at least in our university. So.
Venkat Raman 15:31
So, you know, you mentioned earlier that you joined Irvine in ‘89, and you've risen through the ranks. So tell us a little bit about that journey. You know, what's it been a little over three decades now.
Yeah. You know, I mean, academia is certainly not for the faint of heart, I think. And it requires a certain level of engagement and commitment. As with any, you know, anything in life, there are ups and downs. But academia is particularly difficult in some ways, because there's that big tenure year step, right, you have to prove that you're independent, and you're valued and so forth. So that is an extremely stressful time, I think, for many young faculty, in terms of, you know, it's, it's a complicated process, because it's, there's no way to quantify it, right.
But, I mean, if I were to put it in a nutshell, it's about being able to, it's like a small entrepreneur, where you are expected to run your own, quote, unquote, research business, you're, you're able to garner research funding to support a number of students to address questions that are interesting. And also, not just raise funding, but use that as a mechanism, yeah, to deliver some outcomes, in terms of new advances in terms of new discoveries. And not only do that, but be able to communicate that with others, it's not enough that you do something, but you'd have to be able to, you know, let people know, you know, you know, so it's sort of microcosm of what you might look at in an entrepreneur is to start a business and market it and sustain it and nurture the team. So that's looking at it from that angle.
But coming back to your question, I think, for me, I think, you know, I have a very supportive family. So I was fortunate that, you know, you know, we have two, two kids, and, you know, raising a family at the same time, and also going through academia or any other job, it gets difficult. So for me, I was fortunate that the family support system was there.
But otherwise, you know, there were some, there's always been points in time in the career where it's probably difficult, but I'm an optimist at heart, and I enjoy what I do. So like, I didn't see, any looking back. I think it's been, it's been an enjoyable ride so far.
Venkat Raman 18:07
So maybe, maybe the thing to dwell on a little bit now would be the things that have kept you excited, right? I mean, first of all, I was sort of intrigued to see that you had gotten into cognitive science. So talk a little bit about that, how that, how that came in. And then we can go from there.
Yes, yep. So, you know, the, the. So let me answer the first question or topic that he said, you know, what excites me. So what really excites me is working, with, with bright students, and that I'm continually learning from, from my students and expanding the reach of what I do.
So in terms of cogsci, the interesting thing was I had this PC student who was working on essentially, he was working on some mixed signal circuits with another faculty. And then he took a course in introductory green sciences. And then he said he wanted to start working on trying to do some modeling. Mm hmm.
And I knew nothing about the topic. In fact, you know, the last time I had a biology class was in high school. So, for me, it was completely new. But through the student, we teamed up with another colleague, Jeff Krichmar, and we started building simulation infrastructure for modeling. You know, neural neural networks, spiking neural networks, it's a special kind of networks are representations of what happened to breed.
So that was what, you know, got me excited, got me started on that journey. And then that led to doing a lot more work together with my colleague, and a number of other students. So it's always been, you know, serendipity again, you know, in terms of being lucky that either a new option generally comes up with a colleague, or through a student, or through an engagement in hallway discussions with, with colleagues in terms of newer topics.
And these things blossom, oftentimes in, in trying to get work done with students, so it's always been student driven, I would say in terms of newer topics. So in cogsci, for example, that's how it started. And I had a very, you know, I've had a very productive sort of working relationship with Professor Jeff Krichmar, who's in cogsci. So that that's been, that's how it started. And continues.
And one ingredient in that is, personalities have to match you find the right people that, you know, you are very comfortable with that you can chat. And so I've been very lucky, I guess, in that I've had a large number of collaborators here to Irvine and elsewhere, with whom I've had very good working relationships and enjoyable ones.
Venkat Raman 21:09
Reflect on the types of students you've seen over the last few years, you've been there decades that you've been there. What do you find, as you know, different from maybe now 20 years ago to now or even 10 years ago to now? I mean, what is it that is changing? And what's interesting, and what's not that exciting?
Yeah, I think I'll talk primarily about the undergraduates. Yeah, that's the group that probably are listening to, or will be listening to these podcasts. Right, right.
So I think, you know, obviously, what we have seen is a big shift in, in our majors where computer science is an extremely hot field. So the number of applicants have gone through the roof recently.
And with that, also the quality not only the number of applicants, but the quality, if you look from multiple perspectives, in terms of their scores, the preparation is also rising. So it's become a lot more competitive, I think. And so, the overall quality of students is very high. And they're very engaging, I would say, compared to say, 20 years ago, or even 10 years ago.
Few of them have already done some amount of programming in in high school, they come in with some, so you know, they're already thinking computationally. Yeah. Which is quite different from maybe 15-20 years ago. Sure. So that's one.
And then the others, I think, you know, find a lot more engagement, I would say, in terms of the, the questions that they're asking. And, you know, they're not just there to take the classes and move on, which was sort of what I saw some time ago. I think that that's changed a lot. So they're a lot more engaged, I would say. That's one one thing I've noticed, at least in our program at US Irvine.
Venkat Raman 23:13
[If] Think back at some of the key research points, what would those be? I mean, just just from one of the things that I would, I guess you are really proud of in terms of research that you've been able to shape and make happen?
Yeah, I think students are probably, you know, and in terms of my graduate students, and also some of the undergrads that I've worked with who've moved on, you know, it's, it's been a real pleasure to work with them to work together on newer topics. Yeah.
And in terms of inflection points in terms of research, like I said, you know, there were these different periods of time I was working on silicon compilers was hardware components early on ..., then I did some work on hardware synthesis, which if someone's listening to this is sort of like taking a software description of a application and compiling that again, into hardware, synthesizing if you will.
And so there was a number of years where we were working on that, then we worked on compilation technology, advanced compilation technologies, where machines were getting more complicated. So how do you compile and generate code more efficiently, and then moved into a little bit of the CogSci related work, and then distributed systems in terms of how you can manage resources with energy efficiency in mind.
So you know, there have been different points in time with, with groups of students over the years where things have been moving forward. So and it's often been the case where, you know, the typical period for a PhD student is roughly about five to six years, so and I think with different cohorts, I find that you know, I can if I look back there are these different inflection points where as students graduate, they're new topics that arise, and then we move on.
Venkat Raman 25:15
What do you see over the next few years? There's some exciting areas that you're already working on, or what what sort of tickles your fancy right now?
Yeah, one, one topic that we've been working on is in looking at, again, inspired by biology, and cognitive sciences, trying to exploit notions of what we call as computational self awareness.
So this is the idea that, you know, if you look in terms of evolution of, of living things, we see that, you know, lower level, living creatures are aware of the environment, so you can shine a light on a worm, and it'll shrink or move away.
But we believe that higher level, organisms, like humans have executive capacity to do planning to do higher level functions, which are much more complicated than reactive processes that, you know, you feel something in the environment. And so, you know, I mean, the human body, if you look at public, sort of common literature, there's this whole lot, two systems that people talk about in the body, the fast, slow, fast is reactive, where if you touch something hot, then you have an autonomic nervous chance, and you jump to it. And then the slowest when you're deliberating over, you know, what I should have for lunch, or how I should navigate from point A to point B, or, you know, whatever.
So we want to take those ideas. And so coming back to that, the second form, the one that requires planning, inherently requires some amount of what we call a self awareness where you're aware of yourself and what you're going to be doing in the future. So we're trying to look at using these ideas in engineered systems to build more adaptive systems as we get to autonomy, and adaptive systems, where things are changing, and you don't know what might happen in the future.
So how can you use those types of ideas, to engineer systems to be more responsive, safe and efficient?
Venkat Raman 27:43
What do you have, any, any specific tips for these students who are applying? from your vantage point?
Oh, yeah. You know, I, I don't get involved in, in the admissions process, per se, but just looking at the profile of who we admit, yeah, I would think that if, if this student is considering applying for a program in computer science, or computer engineering or something in this space, yeah, I think they should have, they should try to make sure that they have some elementary programming skills in place, it doesn't matter what language per se, because, yeah, it's not so important. But in terms of thinking algorithmically, and being able to develop, you know, a completed program, and testing it, and so forth.
So I think that exercise and training, I think most most students have that, but it's possible that, especially if they're students applying from countries abroad, depending on the school system, they went to the knee or may not have had that level of training or experience, they may have done it a hobby, for example. Sure. So which is also okay. But I think having some more structured process in terms of not just hacking something together, what you know, what kind of algorithm you're using, or what the efficiency is, or, you know, thinking of these types of things, that that's important.
The other thing that's different, I think, is also, you know, this move, I think, even at the undergraduate level we're seeing now, which is in thinking a little more beyond just programming in terms of two dimensions, maybe, you know, applying it, typically programming is done in the service of some application. Right, right. programming for programs sake.
So typically, I think in high schools, you might see some interest in say robotics or things of that as a club where people are doing some gadgets, because now it's so cheap to get IoT devices. So sure, IOT gadgets, robots, so those are good, but increasingly, we're also seeing this idea that trying to do a little bit beyond just programming the processor but looking at distributing services. So looking at the networking aspects, looking at databases, how do you store it?
So obviously, a student's not able to do everything. But as they start doing projects, think maybe, think just beyond, you know, I can get this robot to work, but then it needs to communicate or it needs to, you need to store the, you know, capture the data, and where should I store the data.
So these types of things help them think a little broader. And that can show that they've thought through that. I think, you know, their statements, they have some expression of how they try to either self-learn some things, or they've had some training, and that I think that would not only help them, but also possibly give them an edge, I would think because it shows that prepared.
Two parts to my question, one is, what are you finding by way of research interests? You said that a) there are a lot more applicants, obviously, a lot more competitive? What, you know, what fraction, obviously, the market for computer science and engineering graduates is pretty hot, undergraduate graduates. So how much are you finding by way of research people who then move to doing a PhD are doing getting into deeper research?
And the second part of my question is, what are the kinds of things students need to be doing to to be good at research? I mean, is there anything that they should start early?
Prof Dutt 31:45
That's a good point, I think. So, you know, research is such a broad umbrella. So it's not about a PhD. So that that's probably the tip of the apex in terms of a triangle, right? You look at it, but I think, even as an undergraduate, depending on the schools that they apply to, most of them have undergraduate research opportunity programs that are managed by the campus, they're trying to engage students and in, engaging them with professors in the lab or doing some projects. And oftentimes, students don't think about that until maybe their junior year or getting into senior year.
But I think it's a good idea for students to start thinking about these things early on in their undergraduate career. These might be based on a course that they took, and they want to learn a little more, maybe they did something and doesn't have to be in programming, might be in, they did something in atmospheric sciences, and they said, Wow, this is cool. Maybe I can look at simulating the weather or something like, yeah, you're going to, then there's a lab on that campus where they're doing some really cool stuff in weather modeling. So getting involved in that sense, right.
So. So I think, and the research is, again, at that level is not about PhD, but it's trying to get better value for the education. Because as we discussed earlier, the courses are very well defined. There's just enough knowledge right and, and application of that knowledge is what they need, regardless of whether they pursue a job soon after they finish or the startup business or the think of grad school or whatever they do.
Yeah. So I think these undergraduate research experiences are extremely valuable educationally. And I think adds so much value to what a student does, as an undergrad.
Doesn't matter. You know, whether they're going to grad school or not. I think I've seen this with hordes of undergrads who say that, because they're doing projects, it's hands on, they're forced to think they're building critical thinking skills, they have to present their work.
So all of these things that one has to do in real life, if you will. Yeah. They're forced to do that beyond just a rote learning of some, some topics from a course.
Venkat Raman 34:07
That's a very good point. That's a very good point.
Venkat Raman 34:14
So what are some, you know, what are some good ways to develop some research skills? Because I think it is quite different, like you pointed out. What might be good some things to tell students?
Yeah, you know, I think each person is different. Sort of. So, you know, for an undergraduate, for example, once they get involved, once they think something's interesting, they probably want to, you know, approach either a campus unit that has research programs or a lab in a professor.
And in some sense, it's an apprenticeship, where one is learning how things are done, in terms of how you think critically, yeah, how you analyze problems, how you able to present your work, how you're able to organize your thoughts in, in a manner so that it can be captured concisely.
Many of these things that, you know, students might do in a project course are similar, but probably in a slightly more open manner. So I think these are skills that, that will come out of engaging in research projects, oftentimes come out of doing a, maybe a capstone project in a senior year, programs in engineering and sciences we have been for student gets involved in doing this earlier on, I think that is a lot more valuable. Because it, it has that think about how to do things.
So I think it's really not so much doing the research itself, it's almost preparation for being able to think about problems, it's about how you think how you organize, how you develop ideas, things of that nature.
And it might not be rocket science, you know, it's, it might be something simple, it might be just helping someone, you know, reformat, Some, it may look like a mundane task to reformat data from one topic to another. You might think, oh, there's nothing in that. But that itself in itself requires. Sorry, I lost my headset, because to think about how you, you know, organize things, how you articulate it, how you capture it, how you record it, etc?
Venkat Raman 36:32
Absolutely, absolutely. I mean, you know, different views of the same data can be very revealing. So the exercise itself might be, might lead to greater things.
Venkat Raman 36:45
We are kind of nearing the end of our podcast.
I wanted to kind of give you a chance to talk about anything that we may not have touched upon, or anything that you think might be either beneficial, interesting, or inspiring for our audience.
Yeah, I think, you know, I mean, people say this all the time, but I think it's really true.
I think, oftentimes, especially students coming from developing countries are sometimes pushed by their parents to do X, Y, or Z. Right. Right.
And, and so I think it's very important in my mind that, that students really think about whether they're excited about what they're doing, right? Because if that passion and excitement is not there, I think it's it's really not worth the time and the effort, right.
I just wanted to add, yeah, in closing especially for students who are coming from India, and, you know, places like that, where one is so focused on academics, yeah, probably at the expense of almost everything else sometimes. Right.
So I think, you know, the undergraduate experience in the US can be very enriching. And so part of that is, is getting involved in other things beyond just classes and research, whatever they're doing.
You know, it's very important to, to, to participate in, in those things interested that one has in clubs or whatever else. And really, there's such a rich set of things that one can do and get involved in.
And that, that actually enhances the enjoyment of the experience and makes each individual more wholesome, I would say, because it really expands what, what one does. So I think that's just something again, people say this all the time, but sometimes freshmen are so you know, especially international freshmen school, about their academics that they might just focus on that.
So I think they should take time to, you know, do what you might call as extracurriculars, whatever that means.
Venkat Raman 38:51
Yeah. That's a great point. I'm glad you brought it up. Because it does. It does, like you said, make someone more holistic. And that I think, is a good, very good thing in life in general.
So, Professor Dutt, that thank you so much for, for your time, taking time during the holidays to do the sport guests with us. And I wish you all the best and Happy New Year and I'll be in touch. So take care. Be safe.
Prof Dutt 39:21
Okay. Happy New Year. Take care. Yeah. Bye. Bye.
Hope you enjoyed our podcast with Prof Nikil Dutt of the University of California Irvine.
Professor Dutt’s passion and excitement for academia and for his work comes through. Each new generation of students rejuvenates him and opens up new avenues of learning and research.
His current project on computational self-awareness is cool.
For those interested in exploring research, Prof Dutt’s tips and pointers are a good place to start.
For your questions or comments on this podcast, please email podcast at almamatters.io [firstname.lastname@example.org].
Thank you all so much for listening to our podcast today.
Transcripts for this podcast and previous podcasts are on almamatters.io forward slash podcasts [almamatters.io/podcasts].
Till we meet again, take care and be safe.
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