Hi! I'm a third-year undergraduate at the Georgia Institute of Technology studying Mathematics. I am fortunate to work with Prof. Yongxin Chen and Prof. Amirali Aghazadeh on the mathematical foundations of machine learning. Outside of research, I enjoy photography, writing, reading, listening to music, and bouldering. In Summer 2025, I participated in a REU at Williams College; this summer I'll be a Quantitative Trading Intern at Susquehanna International Group (SIG). I also serve as the lead of quantitative research for Trading @ Georgia Tech.
Research
My research centers on reasoning about machine learning from mathematical first principles, with a particular focus on high-dimensional probability, optimal transport, and geometric deep learning. Previously, I have worked on structure-preserving generative models, including diffusion on Riemannian manifolds, normalizing flows, geometric flow matching, sampling acceleration for discrete processes, and finite-sample convergence for Sequential Monte Carlo on non-log-concave targets.
My current focus is on sequential minimax games and their connections to martingale optimal transport. I also work on uncertainty quantification for neural surrogates of Wasserstein gradient flows. My recent work on entropic martingale optimal transport appeared at ICLR 2026.
I am also interested in differential geometry, options pricing, and algorithmic game theory.
Publications
- E. Chen. "Entropically Regularized Martingale Optimal Transport with L1 Relaxation". International Conference on Learning Representations (ICLR) Workshop on Advances in Financial AI, 2026. paper
Contact
ec [at] gatech [dot] edu / linkedin