I'm a final-year Ph.D. candidate at Princeton University, advised by Prof. Prateek Mittal. I am also very fortunate to closely work with Prof. Ruoxi Jia at Virginia Tech. Before moving to Princeton, I received my master's degree from Harvard in 2021, where I worked with Prof. Salil Vadhan. Before that, I was an undergrad in Computer Science and Statistics from the University of Waterloo, where I closely worked with Prof. Florian Kerschbaum.
I'm interested in the broad area of machine learning and artificial intelligence (AI). During my Ph.D., I focus on developing principled data-centric methodologies to build trustworthy AI at scale. I use tools from statistics, optimization, and algorithmic game theory to understand the intricate interactions between data, optimizers, and architectures.
I am honored to be supported by Apple PhD Fellowship (awarded to 21 phd students worldwide in 2025), Princeton's Yan Huo *94 Graduate Fellowship (one of three recipients in the department), and Princeton's Gordon Y.S. Wu Fellowship. My work on scalable data attributon received ICLR'25 Outstanding Paper Honorable Mention (one of 6 papers recognized among 11,000+ submissions). In 2024, I was recognized as a Rising Star in Data Science.
I led the organization of ICLR 2025 workshop on Data Problems for Foundation Models (DATA-FM). I gave a tutorial at NeurIPS'24 with Ruoxi Jia and Ludwig Schmidt on Advancing Data Selection for Foundation Models: From Heuristics to Principled Methods. The slides are available here.
I am currently on the job market! Feel free to DM me for any opportunities or discussions. You can access my CV here.