Manish Raghavan

I'm a final-year PhD candidate in the Computer Science department at Cornell University, where I have the great fortune of being advised by Jon Kleinberg. I'm supported by an NSF GRFP award and a Microsoft Research PhD Fellowship. I received my B.S. in Electrical Engineering and Computer Science from UC Berkeley in May 2016. My primary interests lie in the application of computational techniques to domains of social concern, including algorithmic fairness and behavioral economics, with a particular focus on the use of algorithmic tools in the hiring pipeline. I'm also a member of Cornell's Artificial Intelligence, Policy, and Practice initiative and the Mechanism Design for Social Good working group on Bias, Discrimination, and Fairness. In my spare time, I play for Cornell's Mundial FC club soccer team.

Research

How Do Classifiers Induce Agents To Invest Effort Strategically?

Jon Kleinberg and Manish Raghavan

The 20th ACM Conference on Economics and Computation (EC 2019) [video]

Also appeared as:
Designing Evaluation Rules that are Robust to Strategic Behavior at the AAAI-20 Sister Conference Track.
How Do Classifiers Induce Agents to Invest Effort Strategically? in ACM Transactions on Economics and Computation, October 2020.
Algorithmic Classification and Strategic Effort in SIGecom Exchanges, November 2020.

On Fairness and Calibration

Geoff Pleiss, Manish Raghavan, Felix Wu, Jon Kleinberg, and Kilian Q. Weinberger

The Thirty-First Annual Conference on Neural Information Processing Systems (NIPS 2017)

Other Writing

Talks and Workshops

Teaching

CS 170: Efficient Algorithms and Intractable Problems

taught by Umesh Vazirani and Alessandro Chiesa, Spring 2016

CS 170: Efficient Algorithms and Intractable Problems

taught by Prasad Raghavendra and Sanjam Garg, Fall 2015

CS 70: Discrete Mathematics and Probability Theory

taught by Umesh Vazirani, Spring 2015

CS 61B: Data Structures

taught by Jonathan Shewchuk, Spring 2014