About
Han is an Assistant Professor in the Department of Computer Science at the University of Maryland. Her research interests span machine learning theory, economics and computation, and algorithmic game theory. During her PhD, she focused on fundamental questions arising from human social and adversarial behaviors in the learning process, examining how these behaviors impact machine learning systems and developing methods to enhance accuracy and robustness. She also explored the theory of adversarial robustness based on empirical observations
Research Performance Summary
First Recorded Paper
Almost optimal algorithms for linear stochastic bandits with heavy-tailed payoffs
Year: 2018
Citations: 67
Venue: Advances in Neural Information Processing Systems 31
Latest Recorded Paper
A Machine Learning Theory Perspective on Strategic Litigation
Year: 2025
Citations: 0
Venue: arXiv preprint arXiv:2506.03411
Last 10 Years Publication Activity
This timeline shows the professor's yearly publication activity.