About Me

I am a CRCS postdoctoral fellow in the School of Enginnering and Applied Sciences at Harvard hosted by Milind Tambe.

I recently completed my PhD in the Computer and Information Science Department at University of Pennsylvania where I was fortunate to be advised by Michael Kearns.

I study the interactions between machine learning and a variety of contexts, ranging from crowdsourcing to game theory and algorithmic fairness.


Network Formation under Random Attack and Probabilistic Spread with Y. Chen, M. Kearns, S. Khanna and J. Morgenstern - IJCAI 2019

Equilibrium Characterization for Data Acquisition Games with J. Dong, H. Elzayn, M. Kearns and Z. Schutzman - IJCAI 2019

Fair Algorithms for Learning in Allocation Problems with H. Elzayn, C. Jung, M. Kearns, S. Neel, A. Roth and Z. Schutzman - ACM FAT* 2019

Fairness in Criminal Justice Risk Assessments: The State of the Art with R. Berk, H. Heidari, M. Kearns and A. Roth - Sociological Methods & Research 2018.

A Convex Framework for Fair Regression with R. Berk, H. Heidari, M. Joseph, M. Kearns, J. Morgenstern, S. Neel and A. Roth - FATML 2017.

Fairness in Reinforcement Learning with M. Joseph, M. Kearns, J. Morgenstern and A. Roth - ICML 2017.

Learning from Rational Behavior: Predicting Solutions to Unknown Linear Programs with R. Rogers, A. Roth and Z.S. Wu - NIPS 2016.

Strategic Network Formation with Attack and Immunization with S. Goyal, M. Kearns, S. Khanna and J. Morgenstern - WINE 2016

Online Assignment of Heterogeneous Tasks in Crowdsourcing Markets with S. Assadi and J. Hsu - HCOMP 2015.

Adaptive Task Assignment for Crowdsourced Classification with C-J. Ho and J. Wortman Vaughan - ICML 2013.

PAC-Learning with General Class Noise Models with R. Holte and S. Zilles (contributional order) - in KI 2012 (best paper award).


110 Maxwell-Dworkin
33 Oxford St
Cambridge, MA, 02138

Last update: Oct 9, 2019