First Generation Grad Excels in Math and Law

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Although her parents didn’t receive a higher education, Carina Hong ’22 always knew she wanted to go to college. “I thought there’s such a big, exciting world out there, and I wanted to see how to get there,” she says. Mathematics opened the door.

Born in Guangzhou, China, she discovered her passion early and joined a free math Olympiad program that introduced her to “super fun problems” and to the thinking of mathematicians from every era and geography. “Intellectually, I got to travel around the world,” she says.

The program was extremely competitive, but Hong thrives on challenge. By high school the math Olympiad team had been whittled down from 1,000 kids to around 25. Hong was one of just four women still competing.

She set her sights on MIT early. “At 14 or 15, I was writing ‘MIT’ on the margins of scratch paper to motivate myself to keep going,” she says. Still, making the transition to the Institute was tough. “I didn’t know any other person going to MIT from my life before,” she says, noting that most of her classmates in the math department already knew each other from US Olympiads. “It was lonely at first.”

Fortunately, Hong found encouragement thanks to MIT’s “beaver spirit of just get your hands dirty—let’s get it done.” That helped her believe she could succeed even without the networks many people draw on to advance. “You can thrive if you try really hard; like be-ruthless-to-yourself hard,” she says.

Hong also found community through such organizations as the First Generation and/or Low-Income Student Executive Board at MIT, the Undergraduate Mathematics Association, and the International Student Association. (Hong served terms as president of the latter two groups.)

Rewards for Putting in the Work

Initially, Hong thought she might pursue a career in quantitative finance, but gradually at MIT she discovered that “math research is really fun.” In 2022, she won the Alice T. Schafer Prize from the Association for Women in Mathematics, awarded annually to one woman math major in the United States. “That was the moment when I felt like hard work really does pay off,” she says.

Hong also earned the 2023 Frank and Brennie Morgan Prize for Outstanding Research in Mathematics by an Undergraduate Student, a prize jointly awarded by the American Mathematical Society, the Mathematical Association of America, and the Society for Industrial and Applied Mathematics.

It took Hong just three years to finish her MIT degrees in math and physics. She was then accepted by Stanford University’s math PhD program, but before she could start it, she was offered an “amazing opportunity”—a Rhodes Scholarship to Oxford University, where she studied neuroscience. “I wanted to understand biology more,” she explains. “There is a really big world besides math and physics in science, and having an understanding of math in one axis and biomedicine in another axis, can kind of span the science space. That at least was my mental model.”

Hong is so driven to learn that she also sought to expand her thinking beyond the sciences, and for this she chose to study law. “I wanted to pursue law because I think there is something more than science in the real world—humanities, social sciences—and having law as the entrance place, then it’s like a three-dimensional vector, you will span the entire space.”

Math, Law, and AI

Hong applied to Stanford Law School while at Oxford and is now pursuing her math PhD and law degree simultaneously. “I knew very little about law school when I applied,” she says. However, she found law intellectually attractive and has enjoyed the process of discovery. “While I love subjects like contracts, corporations, and antitrust, which are quite math-flavored, I also love constitutional law and appellate litigation—something I didn’t even know existed,” she says.

Still, mathematics continues to be Hong’s primary passion. She has published research on such topics as pop-stack-sorting algorithms and she is particularly fond of her work on number theory. “I’m always a researcher at heart. I want to solve really difficult technical problems,” she says.

Currently, she is excited about an interdisciplinary pursuit that combines mathematics and deep learning. “There are exciting technical bottlenecks I want to be a part of solving,” she says. “What is the future of AI and mathematician interaction? And how will applied scientists interact with an AI mathematician? These are puzzles I hope to work on next.”

Photo courtesy of Carina Hong