Hello! I am a first-year Ph.D. studying Operations Research at Stanford. Before my Ph.D., I graduated with High Honors from Princeton University in 2023, where I majored in Applied Mathematics (ORFE) and minored in Computer Science. Advised by Professor Jason Klusowski, my undergraduate thesis project built a computational model that leverages decision trees to perform transfer learning from deep neural networks, winning the Admiral W. Mack Angus Thesis Prize. I also conducted applied math research in the drug manufacturing division of Merck & Co., where I built a combinatorial optimization model to solve planning problems in pharmaceutical production and inventory control.

On the applied side, I am broadly interested in engineering modern ML methods to automate industrial operations and augment human productivity. More theoretically speaking, I am fascinated by the development of deep learning architectures like transformers and state space models (S4) whose performance defies the curse of dimensionality. Before college, I qualified for the US Physics Olympiad (USAPhO) and won the Silver Medal (top 120 nationally).

JFK's moonshot speech at Rice University has always inspired me, and I find it even more relevant today as our society enters a new moonshot era with the AI revolution. As Kennedy put it, "we choose to go to the Moon in this decade and do the other things, not because they are easy, but because they are hard." Feel free to contact me if you are interested in any of these topics or potential collaboration. I'm all ears!