Meet the Faculty: Qi Lei
This entree is a part of our Meet the Faculty blog series, which introduces and highlights faculty who have recently joined CDS.
Meet CDS Faculty Qi Lei, who will join CDS this fall as an Assistant Professor of Mathematics and Data Science. Lei’s research interests concern machine learning, deep learning, and optimization. She is specifically focused on developing sample and computationally efficient algorithms for fundamental machine learning problems. “I aim to understand the success of modern machine learning algorithms and design samples as well as computationally efficient algorithms that are grounded in mathematical principles,” said Lei.
Lei currently works as an associate research scholar at the Department of Electrical and Computer Engineering at Princeton University where Professor Jason Lee serves as her research mentor. She previously earned her PhD from the Oden Institute for Computational Engineering and Sciences at the University of Texas at Austin, advised by Alexandros G. Dimakis and Inderjit S. Dhillon. Her thesis titled “Provably effective algorithms for min-max optimization” received the 2021 Outstanding Dissertation Award.
While working on her PhD, Lei was a Research Fellow at the Simons Institute for the Theory of Computing at UC Berkeley for their program on the Foundations of Deep Learning. She has received a Simulation Graduate Research Fellowship, Computing Innovative Fellowship, and the Simons-Berkeley Research Fellowship.
Lei’s recently published papers have included ‘‘Optimal Gradient-based Algorithms for Non-concave Bandit Optimization” and “Predicting What You Already Know Helps: Provable Self-Supervised Learning.” Her work on handling distribution shifts won the best poster award at New Advances in Statistics and Data Science this May. In 2021, Lei was honored with a rising star in Machine Learning award by the University of Maryland and a rising star in EECS award at MIT.
To view all our current faculty, please visit the CDS Joint Faculty page on our website.
By Meryl Phair
