Biography

I am an Integrated Master’s–Ph.D. student in the Department of Biomedical Sciences at Seoul National University, studying the intersection of probabilistic generative modeling and AI for scientific discovery. My research focuses on density estimation with stochastic interpolants and molecular generation for drug design, aiming to bridge rigorous mathematical theory with applications in biomedicine.

Before joining the graduate program, I completed dual Bachelor’s degrees in Mathematical Sciences and Computer Science & Engineering at SNU, graduating Summa Cum Laude. My research experience spans probabilistic modeling, black-box optimization, subgraph algorithms, and mathematical physics, reflecting my long-term interest in unifying mathematical structure and empirical discovery.

Beyond research, I value teaching and mentorship as integral parts of scientific growth. I have served as a Teaching Assistant for data science and calculus courses, and as a mentor for underprivileged students in mathematics and programming, guided by the belief that meaning and happiness arise through service.

I am motivated by the pursuit of interpretable and principled AI for science—models that not only perform but also explain and discover.

Feel free to reach out if you’d like to discuss generative modeling, AI for science, or interdisciplinary research collaborations.