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.