I am no longer actively advising PhD students, but I work with a large group of PhD interns at Adobe Research from many top CS PhD programs in the US, including from UMass, Amherst. Please see the web page https://research.adobe.com/careers/internships/ for more details.

Graduated PhD Students

Ian Gemp, PhD. Title: From Optimization to Equilibration: Understanding an Emerging Paradigm in Artificial Intelligence and Machine Learning. Currently Research Scientist, Deep Mind, London, UK.

Thomas Boucher, PhD. Title: Transfer Learning with Mixtures of Manifolds. Currently Senior Scientist, Gritsone Oncology, Cambridge, Boston.

Clemens Rosenbaum, PhD. Title: Dynamic Composition of Functions for Modular Learning. Currently Research Scientist, ASAPP, Manhattan, New York.

Clifton Carey, Ph.D. Title: Graph Construction for Manifold Discovery. Currently, Researcher, Google, New York.

Bo Liu, Ph.D. Title: First order optimization methods for reinforcement learning. Currently, Assistant Professor, Auburn University.

Chang Wang , Ph.D. Title: A Geometric Framework for Transfer Learning using Manifold Alignment. Currently, Research Staff Member, Bridgewater Associates, Westport, CT.

Jeff Johns , Ph.D. Title: Basis Construction and Utilization in Markov Decision Processes using Graphs. Currently, Researcher at Department of Defense, US.

Sarah Osentoski , Ph.D. Title: Action-based Representation Discovery in Markov Decision Processes. Currently, CTO at Mayfield Robotics, Palo Alto, CA.

Mohammad Ghavamzadeh , Ph.D. Title: Hierarchical Reinforcement Learning in Continuous State and Multiagent Environments. Researcher, Google Deep Mind, CA.

Khashayar Rohanimanesh, PhD. Title: Concurrent Decision Making in Markov Decision Processes. Currently Researcher, Osaro Labs, San Francisco.

Georgios Theocharous , PhD.  Title: Hierarchical Partially Observable Markov Decision Processes for Robot Navigation. Research Staff Member, Adobe Research.

Student Awards

Bo Liu, Ji Liu, Mohammad Ghamvamzadeh, Sridhar Mahadevan, and Marek Petrik, Finite-sample analysis of proximal gradient temporal difference learning, Proceedings of the Conference on Uncertainty in AI (UAI), July 12-16th, Amsterdam, Holland, 2015. Received Facebook Best (Student) Paper Award.

Rajbala Makar, Sridhar Mahadevan, and Mohammad Ghavamzadeh "Hierarchical Multi-Agent Reinforcement Learning", Fifth International Conference on Autonomous Agents, Montreal, 2001. Best Student Paper Award

Gang Wang, Sridhar Mahadevan "Hierarchical Optimization of Policy-Coupled Semi-Markov Decision Processes", Proceedings of the 16th International Conference on Machine Learning (ICML '99), Bled, Slovenia, June 27-30, 1999. (nominated for best paper award at ICML-99)

BS/MS Students

Suchi Saria, B.S. (Honors), Mount Holyoke, 2004. (PhD, Stanford, 2011, now Assistant Professor, Johns Hopkins.)

Natalia Hernandez-Gardiol , B.S. (honors). Postdoc, MIT CSAIL Lab .

Ilya Schweidwasser, BS (NSF REU student).

Rajbala Makar, M.S., 2000, Agilent, CA.

Silviu Minut, M.S., 2000.

Nikfar Khaleeli, M.S. 1997. Now at Windriver Systems, CA.

Nicholas Marchalleck, M.S., 1997. Now at Cybear Systems, FL.