Sridhar Mahadevan



School of  Computer Science

AAAI Fellow

Co-Director, Autonomous Learning Laboratory

Editorial Board, Journal of Machine Learning Research

Research Interests

Artificial Intelligence

Machine Learning

Reinforcement Learning

Representation Discovery

Variational Inequalities


On sabbatical leave, Fall/Spring 2014-2015.


mahadeva AT

140 Governor’s Drive

Department of Computer Science

University of Massachusetts

Amherst MA 01003


Administrative Assistant: Susan Overstreet


My research spans across many areas of artificial intelligence (AI) and machine learning (ML). Most recently, my students and I are investigating a new framework "rethinking" AI and ML based on the concept of equilibration, which unifies a broad class of problems, including (convex) optimization, game theory, complementarity problems, networked equilibrium problems, and nonlinear equations. The approach uses the mathematical framework of variational inequalities.

We are exploring many applications of this framework, including economic models of the next-generation of Internet architectures, new safe, scalable, and reliable reinforcement learning algorithms for solving sequential decision problems, and new methods for learning low-dimensional representations of high-dimensional scientific datasets, such as spectroscopic measurements of rocks on Mars from Curiosity, the rover currently on Mars, and materials from near-Earth asteroids.