About

I am a 5th year Ph.D. student in the Computer Science Department at UT Austin, supervised by Peter Stone. I am primarily interested in how agents might learn to cooperate with unseen agents – a problem known as ad hoc teamwork. My other research interests include decentralized cooperative multi-agent reinforcement learning, leveraging demonstration knowledge to improve sample efficiency of reinforcement learning, and representation learning for reinforcement learning.

I received a B.S. in Mathematics and Computer Science from Duke University, where I researched interpretable machine learning methods for criminal recidivism prediction with Prof. Cynthia Rudin. We also analyzed the COMPAS recidivism prediction algorithm, showing that a nonlinear dependence on age was an alternative explanation for the previously observed racial bias of COMPAS. My work was recognized with a Goldwater Scholarship, a premier national undergraduate research award.