I work broadly on the theoretical aspects of machine learning and algorithmic economics. I especially care about developing a theory for machine learning that accounts for its interactions with people and organizations, and the wide range of social and economic limitations, aspiration, and behavior they demonstrate.
Prior to Cornell, I was a postdoctoral researcher at Microsoft Research, New England, in 2018-2019. I received my Ph.D. from the Computer Science Department of Carnegie Mellon University, where I was fortunate to be co-advised by Avrim Blum and Ariel Procaccia. My thesis titled Foundation of Machine Learning, by the People, for the People received the CMU School of Computer Science Dissertation Award (2018) and a SIGecom Dissertation Honorable Mention Award (2019).
My CV can be found here.