Vishal Raman

Vishal Raman

Fun fact: I didn’t own a plate in my entire life until this semester (Spring 2022).
Interviewed by Chelsea Leung

What’s your year, pronouns, and major?

I’m a 3rd year, I use he/him/his pronouns, and I’m a Math and CS double major.

Where are you from?

I’m from Princeton, New Jersey.

What committees have you been in?

Last semester I was in Data Consulting, and this semester I’m a Data Consulting Project Manager.

What hobbies and interests do you have?

I like to play the piano, and I like to play games like chess, poker–all kinds of strategy games.

What are your professional interests?

I’m interested in quantitative finance. That’s what I worked on last summer. Aside from that, in terms of academics, I would like to go to grad school in some field between the intersection of math and deep learning.

How do you use statistics in this field?

Anything related to machine learning involves a lot of statistics because all of it is based on statistics methods from a long time ago. But, they’ve been developed over time and became a lot more complicated over the years. Everything in machine learning comes from the backbone of statistics.

What internship experience do you have?

Last summer I was an intern at IMC Trading. There, I got to learn a lot more about financial models, terminology, and techniques that people use in this industry. This summer, I’ll be a research intern at Cornell focusing on problems related to optimal control. So, problems in game theory with a numerical focus on finding solutions to different types of games. Here’s an example: one problem they’re working on is cancer research through the lens of game theory. In your body, when you’re treating someone for cancer, there could be lots of different types of cancer cells, and there are different treatments that target different types of cells. But, there’s the problem of when to apply the right treatment at the right time, how to apply the treatment to minimize cost, and how to maximize the likelihood of survival. That’s one example of a game that has a lot of importance in everyone’s lives.

How did you find out about SAAS and why did you join?

I found out about SAAS from one of my friends who’s in the club now, named Ashley. Last year when I was moving in, a lot of my roommates were already in the club. So, I thought it would be a fun way to make new friends and have some social experiences aside from day-to-day work.

What did you learn in Data Consulting?

Last semester, we worked on something related to A/B testing, and we used techniques for multi armed bandit algorithms, which are pretty new and currently being researched a lot as a subfield of reinforcement learning, so it’s very exciting to learn about. This semester, I’m working on a project that involves computer vision, which is also a very hot and exciting field. It’s exciting because essentially computers are really, really dumb. Like, they’re babies in terms of vision-related tasks. There’s a breadth of problems in computer vision because there’s so many things we can do in an instant that a computer can still struggle with.

Why did you decide to stay in SAAS for another semester?

I enjoyed the social atmosphere of SAAS. It’s the reason I joined and why I decided to stay. I’m learning a lot in the projects that go on and it’s very fun to work with really smart people.

What’s your favorite SAAS memory?

My favorite SAAS memory was going to the B&G social last semester, and I got a little bit drunk for the first time and apparently I was saying a lot of math to people, which was a weird and unforgettable experience and that was a lot of fun.

What has been your favorite class so far?

I hate all of them… No, that’s not the answer. This semester, I’m taking a class on dynamical systems. I enjoy that a lot because it takes a lot of different areas in math–from geometry, from probability, from analysis–and it combines them all together to study these types of systems called dynamical systems. They’re highly, highly relevant in lots and lots of fields that people really care about. One very important example from computer vision is the Generative Adversarial Network (GAN). It’s an example of a closed-loop autoencoding scheme. And whenever you have these closed-loop processes going on that are constantly repeating and you want to study the long term behavior of that kind of system, that’s what dynamical systems are all about. It’s a lot of fun learning about this math theory background that leads to a lot of important work in computer science and a lot of other fields.

Who’s your favorite professor?

My favorite professor is Maciej Zworski. I’m currently a grader for one of his classes. I’ve taken three different classes with him. He’s always a little bit wild. When he’s at the blackboard, he’s always kind of baffled, but he just huge brains it and figures everything out. But it’s a lot of fun to be in his classes and to speak to him because he loves talking to undergrads.

What does he teach?

He’s an analysis professor, so he focuses primarily on Partial Differential Equations (PDEs) and he’s also involved with a lot of problems in Geometry related to PDEs. And problems in physics related to studying dynamical systems.

What’s a spot on campus more people should know about?

Doe Library. It’s a quiet spot with a lot of students working, and it’s also aesthetically pleasing so it’s a lot of fun to work there.

What’s a place that you think is not fun to work at?

Doe Library. It’s a quiet spot with a lot of students working, and it’s also aesthetically pleasing so it’s a lot of fun to work there.

What’s your favorite place to eat in Berkeley?

My favorite place to eat is The Noodle, and my favorite thing to get there is Mango Sticky Rice.

Why?

I didn’t try it before going there, and I really enjoyed it. And my favorite fruit is the mango.

What’s your favorite boba shop?

It’s split between Yifang and TP Tea.

What’s your go-to order?

Brown Sugar Pear Black Tea Latte.

The website version of this interview was mildly edited for length and clarity.