Story | Lily Chen (she/her), Contributing Reporter
Photo | Provided by Prof Michael Choi (he/him)
Date of interview: Sep. 1, 2021
Interviewer: Lily Yunrong Chen
Interviewee: Prof Michael Choi
Department: Science (Data Science, Mathematical Stochastics)
Q: I know that a lot of professors have had the experience of living in different countries. Would you like to share with me about where you have lived?
A: I guess it would be good to have a bit of self-introduction. I grew up in Hong Kong, and I got my undergrad degree at the University of Hong Kong. After that I moved to the States to Cornell University to do my PhD in operations research. That was from 2014 to 2017, so I stayed at Cornell which is in upstate New York. [Then] I moved back to my home in Hong Kong to do a postdoc for a year. After that I moved to the Chinese University of Hong Kong (Shenzhen) from 2018 to 2021. I joined Yale-NUS in July 2021, so I’m now in Singapore. But then, even back in my PhD days I have visited Singapore for research purposes. So, Singapore is not really a brand new place to be.
Q: So do you consider Hong Kong as your home?
A: Yeah, I do consider Hong Kong as my home, but then there’s an old saying—I don’t know whether it is in English or Cantonese—that “home is where your heart belongs.” So, I mean physically, I consider Hong Kong to be my physical home in the sense that I have many friends and family still there, like my parents and my sister. But then after my relocation to Singapore, I consider Singapore to be my new home, in the sense that I also brought a lot of my family, like my wife and my dog, to Singapore. My family is now living in Singapore, so I consider Singapore to be my new home.
Q: You mentioned that you went to university in both Hong Kong and also in the States. How was your university experience? Do you have any life advice to give to Yale-NUS students?
A: My advice to any college student is to try to explore an area that matches with your interests. In that way, if you pursue a career in industry, or if you pursue an academic career like me, you will not regret it. I think for college students, my advice is to find and develop your own interests while you’re at college. It can be something academic, but it can also be something non-academic as well; that’s totally fine.
Enjoy your college time, because no matter what you do after you graduate from college, things will become very hectic. When working in industry, you definitely have much less time than you have as a student. On the other hand, if you pursue an academic career like me, you will have more and more academic pressure. So in some sense, college is like the last few years that you have complete freedom to pursue your own interests. Just treasure your time while you’re in college, enjoy, and learn the best out of it.
Q: That’s very fair advice. Your research interest is related to statistics, physics, and probability theories, would you like to elaborate more on that?
A: My research is about the study of stochastic processes, basically trying to develop theories to describe random phenomena. This kind of random phenomenon can happen in our day-to-day life. For example, people will use stochastic processes to model the random fluctuations in the stock market. And there are various random phenomena that happen in the real world. So, one of my research areas is to create and better understand stochastic processes.
It turns out that I’m interested in a really special class of stochastic processes that we call the Markov chain, or Markov process. So if any of the students here decide to do a major in Mathematical, Computational, and Statistical Sciences, they may take some more advanced courses in probability and stochastic processes. In these courses you would learn about the first special kind of stochastic process called the Markov chain and Markov processes, which play a fundamental role in our understanding of random phenomena.
One of my research programs is to develop the theory of Markov chains and processes, as well as to study their applications in statistics and data science. So in statistics and data science, it turns out that a lot of algorithms that people use in data science or in machine learning are closely related to Markov chains and Markov processes.
More broadly speaking, I’m interested in statistical physics, applied probability, stochastic optimization and information theory, but all these topics are kind of connected by Markov chains and Markov processes, which have become my primary focus in my research.
Markov chains and Markov processes are just everywhere. Perhaps one of the simplest examples is card shuffling. Let’s say when you go to a casino, you have to shuffle a deck of cards. You may ask yourself, how many shuffles do I need for the deck of cards to be considered fully random. It turns out that this question boils down to the analysis of a specific Markov chain, and it turns out that the answer to that question is that it only takes seven shuffles, what we call the riffle shuffle, to mix a deck of cards. That’s one example of a real life application of Markov chain theory. And this principle has then been applied to the design of the shuffling machine at the casino. It turns out that the principle behind the operation of this random shuffling machine is exactly related to this card shuffling problem that I just described. So, this is just a very layman’s introduction to the Markov chain, and I hope everyone can appreciate the beauty of it.
Q: Would you like to give me the story of travelling to Singapore? Was the process of getting entry approval smooth?
A: That was a headache. I consider myself lucky in the sense that I could physically arrive in Singapore on time before the semester started, and I do know quite a few of my faculty colleagues who failed to arrive on time to Singapore because of the pandemic. For me, I departed from Hong Kong, and Hong Kong is considered to be one of the safe regions from Singapore government’s perspective. So, the process has been pretty smooth for me and my family. And we had to do seven days of Stay-Home Notice (SHN); that’s about it. But one thing that troubled me is, apart from bringing along my wife, I also brought along my dog from Hong Kong, and that turned out to be pretty troublesome, and obviously I didn’t want my dog to serve quarantine by herself. I wanted my dog to serve quarantine with my wife and myself, because we three are like a family. That was a bit of a headache, but luckily, it got resolved at the end, and we managed to find an apartment that allowed all three of us to serve our SHN together.
Q: So far, based on your teaching experience, did you have any moments of “expectation vs. reality”?
A: Before I came to the college, I was told that the students here are pretty impressive and they are of high quality. And my experience so far has been pretty positive. There’s not really a huge gap or huge deviation between expectation and reality. My impression of the students here is that they are really smart, pretty hard-working, and so far everything has been in line with my expectations.
Q: What was your immediate reaction to the announcement of the school’s closure? Were you sad, angry, or upset?
A: I was just upset, for various reasons. I guess one of the reasons that I’m upset is because based on my limited time here at the college, I feel that the college is such a great liberal arts college in general. The people, the faculty, and the students here are awesome. It is a huge loss to Singapore and to NUS that this college cannot be sustained in the long run. So I feel sad.
The second reason that I feel sad is because I could also foresee the reactions from alumni, from our students, and from our faculty. Most of them must be very disappointed about this decision. I also feel sad for the junior faculties, especially faculties like me who just joined the college, or the freshmen who just joined the college. I mean, obviously we didn’t expect this at all. I do know some faculty and students that are kind of stuck somewhere else because of the pandemic and they cannot really make it to Singapore at this point. In general, I just feel sad for all parties involved.
Q: Is teaching at NUS appealing to you?
A: This is a good question, and in fact, I had worked at the Chinese University of Hong Kong in their Shenzhen campus for the past three years before going to [Yale-NUS] College [to teach]. And at that university, you can imagine, we need to teach big classes. One of the classes that I’ve taught in the past had like 500 to 600 students, which is similar to one of the biggest classes at NUS. So in that sense I do have experience in teaching such a big class, and I certainly do not mind. But on the other hand, I also do enjoy this liberal arts college setting, where you have such a small class size and wonderful class interaction during the lecture. If I go back to NUS to teach for them, one thing that I’m going to miss for sure is the small class size here and the interaction with the students.
Q: What does a liberal arts education mean to you?
A: To me, liberal arts education means freedom to explore students’ own interests. That’s why you have the common curriculum: you are exposed to a wide range of courses, unlike in a traditional university setting. In a traditional university setting, most of the time you pick your major in the first year or at the beginning of the second year, so you specialize right away. In a liberal arts college, you will have the privilege to first learn from a diverse range of perspectives and disciplines. Afterwards, you will specialize into the direction of your choice.
So a liberal arts education means that we are nurturing future leaders and future global citizens who have a wide range of perspectives, who are not limited to a particularly niche area. But at the same time, they are still capable of doing some very technical things. It is especially relevant in my own discipline, statistics and data science. So, for sure, if you want to find a job in the industry as a statistician or data scientist, you will need technical skills in data science, you will need to know the relevant statistics concepts, you will need to develop computer science skills to do your job, so for sure technical expertise is very relevant in the career of a data scientist or statistics related career.
But on the other hand, you will also need that global perspective to handle your day-to-day job in industry as a data scientist. Nowadays, one of the hot topics in data science is the data privacy issue. I mean, a lot of companies or governments are collecting our personal data. How are they going to protect it Organizations like tech companies or governments can use this data for their own purposes, so how can we protect our data privacy?
Apart from attacking it from a technical perspective, there are many papers and literature that attack this question from a more mathematical, statistical, computer science perspective. At the same time, you will also need to have knowledge and perspective from other disciplines, say from law, social science, arts, and humanities. You will need to have a very balanced perspective, in addition to technical expertise to address these pressing questions of data science and data privacy. So I think that the advantage of a liberal arts education is you have this balanced perspective, you’re broadly educated. Based on my encounter with liberal arts college graduates versus traditional university graduates, I do think that these two systems produce very different people.
Q: Now moving on to some fun questions: could you please give me your “top three list” of anything? It can be the top three foods, top three sports, etc.
A: I would say the top three fruits. So my top one is orange. Second one is mango. Third one is banana. The reason why I put orange first is because back in Hong Kong, I actually have a nickname from middle school, people call me “orange” in Cantonese in Hong Kong, because I used to have orange as part of my lunch in my lunchbox delivered by my family. So at that time my middle school friend called me “Orange,” instead of Michael or Michael Choi. That was a nickname from my middle school, but then after I moved on to high school and university, I still kind of self introduced myself, “Don’t call me Michael, call me Orange!”
Q: What is the weirdest food you have ever eaten?
A: I remember when I was young, I visited South Korea with my family. At one of the restaurants we had live seafood. So, like, live octopus. So that was pretty weird to me, because the octopus was kind of alive… I mean, it’s not alive, it’s already dead, but then, it’s kind of moving, so you put that moving octopus in your mouth. That was pretty weird to me, especially at that time when I was pretty young. I was only 10 or 11.
Q: What skill did you pick up during COVID?
A: That’s a good question. I guess I know how to use Zoom [now]. I mean before COVID, I knew Zoom was a very useful conference or meeting platform. Back in Cornell when I was a PhD student, in 2017 or 2018, the faculty and the professors there were already using Zoom sometimes for online meetings. Now, due to the pandemic, I have to use it on a regular basis.