About Me

I am a PhD student in the Computer and Information Science Department at University of Pennsylvania. I am 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.


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).




Shahin Jabbari
3401 Walnut St, Room 409B
Computer and Information Science
University of Pennsylvania
Philadelphia, PA, 19104