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Nika Haghtalab is an Assistant Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. She broadly works on the theoretical aspects of machine learning and algorithmic economics. Her research considers the impact of learning algorithms within the context of social and economic structures, particularly as organizations increasingly interact through learning systems. Prof. Haghtalab's work aims to build theoretical foundations that ensure the performance of learning algorithms in the presence of everyday societal and economic forces. She completed her Ph.D. in Computer Science at Carnegie Mellon University, where she was supervised by Avrim Blum and Ariel Procaccia. Her thesis, titled 'Foundations of Machine Learning,' received the CMU School of Computer Science Dissertation Award in 2018 and an Honorable Mention from SIGecom in 2019. Prior to UC Berkeley, she served as an Assistant Professor in the Department of Computer Science at Cornell University from 2019 to 2020 and worked as a postdoctoral researcher at Microsoft Research New England from 2018 to 2019.
University of California, Berkeley • Berkeley, CA
Assistant Professor in the Department of Electrical Engineering and Computer Sciences.
Cornell University • Ithaca, NY
Assistant Professor in the Department of Computer Science.
Microsoft Research New England • Cambridge, MA
Conducted research in machine learning.
The Mathematics Subject GRE is required for the Fall 2026 admissions cycle. General GRE is optional.