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  • Student Interview | Linger Sun, Ph.D. Program in Data Science, SDS 2020 Cohort

Student Interview | Linger Sun, Ph.D. Program in Data Science, SDS 2020 Cohort

December 30, 2022 Student Interview

 

Linger Sun

Student Biography

Linger Sun is a third-year doctoral student at the School of Data Science, CUHK-Shenzhen. She graduated from CUHK-Shenzhen undergraduate program with a major in Applied Mathematics. Her research direction is operations management in medical scenarios, involving data analysis, simulation, optimization, online learning, reinforcement learning, among others. During her undergraduate studies, she won the second prize of the National Mathematical Contest in Modeling for Chinese College Students and the Honorable Mention of the Mathematical Contest in Modeling for American College Students. Linger Sun worked as an intern in the Data Management Department of China Construction Bank, and also served as a teaching assistant in many courses such as Calculus, Computer Fundamentals, Data Analysis, Probability Statistics, and Stochastic Processes. Upon graduation, Linger Sun ranked in the top 5% of the college and won the first-class honor.

 

Interview 

Q: Can you briefly describe your learning experience at the School of Data Science?

A: SDS's course offering are very rich, and most of them keep up with the forefront. In particular, the faculty is very strong. Most of the teachers have overseas teaching experience and come from multiple research fields. Teachers are very open to communicate with students, work diligently in class, and are willing to lead students to do scientific research. Many SDS teachers I know teach undergraduate students, and I joined the research team led by SDS teachers when I was an undergraduate student.

In addition, SDS arranges more than two seminars every week. The invited speakers come from many fields, and you can learn about the frontiers of development in various domains. And after the seminar, there will be a one-on-one session with the speaker, so that you can have more in-depth exchanges.

 

Q: Students are busy enough with their studies, and so it can be challenging to coordinate their studies and other aspects of life. How do you adapt and strike a balance?

A: This Work Life Balance question is also something I have been exploring. I feel like an atypical researcher. It may be because I had a smooth life, and my family raised me to live lightheartedly. For example, before going to college, my parents would take me on a trip basically once a week, which makes me accustomed to hang out on weekends.

I feel so revitalized after a little weekend hang out, which refreshes my mind. But it’s not just all about relaxation. I recently discovered that I actually feel a little anxious after these hang outs, as I spend a day for leisure, while everyone else is working hard. But be it relaxation or anxiety, these emotions can motivate or scourge me to devote myself more to my research.

Sometimes the college also organizes some activities for us, such as team building, sport games and mixer events, to help us relax and form a closer bond with our classmates and teachers.

 

Q: What do you think will benefit you the most from CUHK-Shenzhen/SDS?

A: I think both opportunities and challenges are presented here. CUHK-Shenzhen's strong faculty, laboratories and scientific research teams in various fields provide students with a variety of opportunities, but there are also many underlying challenges. Always having the courage to try new things, seize opportunities and embrace challenges are the most valuable lesson from CUHK-Shenzhen.

 


Q: What habits do you think are worth developing and helpful for self-cultivation during your study at CUHK-Shenzhen/ SDS?

A: In addition to good research habits, such as independent thinking, daring to question authority, embracing innovation, some life habits are equally important, such as fitness, which temporarily make you withdraw from the intense scientific research, and relax the brain while training the body.

However, it is not always easy to take great care of life while engaged in scientific research. For me, the work life balance is the ability to switch between work and life freely, to be more committed to work after having fun and relaxation, and to understand that work itself is a way to lead a better life. I think this habit of work life balance is also worth cultivating.

 

 Q: Was there anyone or anything that impressed you deeply in college?

A: The classrooms of many SDS teachers are full, and students from various colleges and majors will come to take the class, and even the windowsills are full of people.

 

Q: Do you have any hands-on practice in the four-year undergraduate program? Any experience and take-away about clubs and interships?

A: During the summer vacation of my sophomore year, I went to the Data Management Department of China Construction Bank for an internship. During the internship, I learned some practical problems and corresponding solutions. During this internship, I broadened my horizons and learned how to communicate more effectively with people from different backgrounds.

I was an Undergraduate Student Teaching Fellow at our school for a long time. This system was first started at Stanford University, which is to let undergraduates work as teaching assistants. Our school borrowed this system.

I have been teaching freshman classmates since my sophomore year. At that time, I taught calculus, computer science, and physics experiments. Later, during the Ph.D. program, I was assigned the role as TA (Teaching Assistant), and I have been working as a TA ever since. In all, I have accumulated four years of teaching experience. By teaching others, I can also understand each person's different thinking process, which is also very helpful for me to better understand the subject.

 

Q: Now that you have graduated and chosen to continue your studies, can you briefly share that experience with us?

A: My undergraduate degree is in mathematics. At that time, I chose this major because if I learn basic subjects at the undergraduate level, it would be easier to take a turn in the future. But even at that time, I decided that I would not always study mathematics. I am a more pragmatic person, and I favor application-oriented work in the future.

But only by laying a solid foundation at the beginning, can you deal with problems more easily in the future. After all, every problem boiled down to the root level becomes a mathematical one. Why is this algorithm the way it is? Its underlying logic is also of mathematical nature.

My current research direction was determined during the summer vacation of my junior year. At first, I was very interested in the Stochastic Process class by Prof. Dai Jiangang (Dean of the School of Data Science). At that time, an opportunity came knocking at my door. Two teachers came to visit Prof. Dai. It happened that the project they wanted to carry out was also related to Prof. Dai's course, and they were looking for undergraduates to join, so I went for an interview. After the interview, we carried out a project related to operations management. It is also in this project that I have determined the direction of my future studies.

I graduated in 2020. Originally, my plan was to go abroad to study for a master's degree in OR (Operations Research), and I had completed the application at that time and received my favorite offer. There are OR programs from UCB, Cornell and Cornell Tech, but when I was about to make the final decision, the pandemic broke out. My family is not very supportive of me going abroad to study for a master's degree. So should I go for a master's or a Ph.D.? At that time, a professor encouraged me to go for my Ph.D., and CUHK-Shenzhen also gave me this offer. In the end, after weighing various pros and cons, I decided to directly go for Ph.D. 


Q: What are your current major and and why did you choose it?

A: OM (operations management) is my research field now. From a macro perspective, it is an interdisciplinary subject that intersects mathematics, data science, statistics, computers and so on. Generally speaking, OM deals with some practical problems, such as Pricing, Inventory, Supply Chain, Scheduling, etc. OM has a sister discipline called Operations Research, which deals with more theoretical problems.

OM basically starts from real problems, makes some assumptions, constructs a mathematical model, and then seeks a suitable algorithm to solve it. We also need to carry out a theoretical analysis of these algorithms, such as to verify whether the algorithm can theoretically reach its optimal solution, or how far it is from the optimal solution. Under appropriate circumstances, we can even apply this algorithm directly to the industry to solve some real-world problems. This way of combining abstract mathematics with real-world problems appeals to me and is why I chose this major.

 

Q:Can you share your research experience?

A: I had two research experiences during my undergraduate years.

The first part of scientific research is about the pricing of options and futures. Most of our math classes at that time were taught by Prof. Li Yutian, so I had a good connection with him. Then during the summer vacation of my sophomore year, I took the initiative to send an email to Prof. Li, asking if there were any opportunities for scientific research. In fact, I didn’t have too many ideas at the time. I just wanted to experience what it’s like to do scientific research. But that project was particularly difficult for me because the professor is from the mathematics department and used the PDE (Partial Differential Equation) method. I still remember that I read the books for a week in a row, with but little gain. Later, I gradually discovered that I didn’t particularly like that direction, and I felt that it was too esoteric and beyond my cognitive level. The project was continued on and off for about a year, and there has been no particularly significant progress. It was not until the summer vacation before I turn senior that I encountered new opportunities, and I found that I still prefer application-oriented subject, and I was happier in the process of doing it.

The second part of my scientific research is what I mentioned before, which is about OM. At that time, I saw the recruitment notice in the school group chat. At that time, about 40 people were interviewed, and finally 4 were recruited. I think it's especially important during the interview process to highlight why others should choose you, and why you choose the program. Of course, the CV should also be well written in advance, highlighting personal advantages and unique experiences.

Specifically, this project is a question about hospital scheduling. When we usually go to the hospital, we find that the doorway of the doctor's consultation room is always full of people. Every patient in the line seems very anxious, and the doctor is too busy, resulting in a very poor order in the entire hospital. The problem is that, among these patients, in addition to the patients who come to see the doctor for the first time, there are also patients who return after the examination. For these returning patients, they don't know when they should come back, they only know that they need to come back to see the doctor after the examination. As there is no take-a-number system when they return, they can only be inserted into the queue of patients who come to see the doctor for the first time, which triggers anxiety of the returning patients, dissatisfaction of the patients who are cut in the queue, and even creates tension between doctors and patients.

By analyzing this problem, we decided to design a method to solve the scheduling of waiting patients who have made appointment and the returning patients at the same time, so that the order of the entire hospital can be improved. We started from the real situation at hand, established a mathematical model for it, and then use a Data-Driven Algorithm to solve it, and finally prove that this method is close to optimal, or, when compared to no scheduling, this method can optimize the existing order of the hospital to the greatest extent.


Q:What are your plans for you future?

A: In the future, I will still focus on data science, aspiring to be a practitioner in the industry and tackle with practical problems.

 

Q:In view of the possible confusion and bewilderment of many freshmen, do you have any lessons to tell your younger fellows?

A: I think it is a cost-effective thing to get more exposure to some fields, or to get more exposure to things that interest you when you are in the lower grades of the undergraduate program.

There could be two situations. One, you like a subject very much, but after studying for a period of time, you find that you don’t like it so much after all, or you find that you like something else; second, you have learned about one subject, and at the same time, you want to know more about it, and in the process, you find yourself like it more and more.

At the beginning of the program, if you find yourself in the first situation, the price of trial and error is actually very low. The cost is much lower when you figure out now that you don't like it, than coming to the epiphany spending years on it. If you are in the second situation, and want to go deeper into this field later, the early exposure can lend you hand to win at the starting line.

You need to try many things before knowing you like it or not, and you never know what could interest you until you give it a go. So no matter what major you choose, you need to start by trying and knowing.

Picking up interest should be the starting point of any endeavor. If your interest in the subject seems lackluster at best, it will be painstaking to dig deeper. But if you're interested in the subject, the entire deep dive can be fun and enthralling.

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