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PROFESSORS IN REINFORCEMENT LEARNING

Showing page 1 of 3 — 50 professors available publicly

Tengyu Ma

deep learning theory non-convex optimization reinforcement learning

Tengyu Ma is an Assistant Professor of Computer Science at Stanford University. His research focuses on machine learning and algorithms, especially topics such as deep learning theory, non‑convex optimization, reinforcement learning, representation learning, distributed optimiz...

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Quanquan Gu

reinforcement learning computational genomics non-convex optimization

Quanquan Gu is an Associate Professor of Computer Science at the University of California, Los Angeles (UCLA) Samueli School of Engineering, where he conducts research in machine learning, data mining, and optimization algorithms with applications spanning deep learning, reinforc...

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Jason Lee

foundations of deep learning representation learning reinforcement learning

Jason Lee is an associate professor in EECS and Statistics at UC Berkeley. Prior to that, he was an associate professor at Princeton and a researcher at Google Deepmind. Jason received his PhD at Stanford University advised by Trevor Hastie and Jonathan Taylor, and was a postdoct...

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Daniel Yamins

computational neuroscience reinforcement learning applied mathematics

Dan joined Stanford in September 2016. He's an Associate Professor in the Departments of Psychology and Computer Science, the Wu Tsai Neurosciences Institute, and the Stanford Artificial Intelligence Laboratory. He is a recipient of the McDonnell Foundation Scholar, Sloan Resear...

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Simon Shaolei Du

deep learning representation learning reinforcement learning

Simon Shaolei Du is an assistant professor in the Paul G. Allen School of Computer Science & Engineering at University of Washington. His research interests are broadly in machine learning such as deep learning, representation learning, reinforcement learning and data selection. ...

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Chuck Anderson

reinforcement learning brain-computer interfaces high-dimensional data analysis

I am a professor in the Department of Computer Science, Colorado State University (CSU), working on machine learning algorithms and deep neural networks for reinforcement learning, brain-computer interfaces and high-dimensional data in general. My interests are in algorithms for ...

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Pavel Izmailov

Reinforcement Learning AI Alignment Interpretability of Deep Learning Models

I am an Assistant Professor in the NYU Tandon CSE department, and Courant CS department by courtesy. I am also a member of the NYU CILVR Group. I am also a Researcher at Anthropic. I am primarily interested in reinforcement learning, reasoning, AI for science and AI alignment. ...

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Ronald Parr

Approximate Dynamic Programming Markov Decision Processes Probabilistic Models for Robotics

Ronald “Ron” Parr is a Professor of Computer Science at Duke University, where he conducts research on machine learning, reinforcement learning, decision making under uncertainty, and planning algorithms. He earned his Ph.D. in Computer Science from the University of Californ...

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C. Karen Liu

Physics-Based Animation Character Animation Optimal Control

C. Karen Liu is a professor in the Computer Science Department at Stanford University. Prior to joining Stanford, Liu was a faculty member at the School of Interactive Computing at Georgia Tech. She received her Ph.D. degree in Computer Science from the University of Washington. ...

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Pascal Poupart

Natural Language Processing (NLP) Reinforcement Learning Bayesian Federated Learning

Pascal Poupart is a Professor in the David R. Cheriton School of Computer Science at the University of Waterloo, Waterloo (Canada). He is also a Canada CIFAR AI Chair at the Vector Institute and a member of the Waterloo AI Institute. He serves on the advisory board of the AI Inst...

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Sherry Yang

reinforcement learning generative modeling foundation models

I am an Assistant Professor at NYU Courant and a Staff Research Scientist at Google DeepMind. I research in machine learning with a focus on reinforcement learning and generative modeling. Recently, I am interested in problems at the intersection of foundation models and decis...

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Nan Jiang

reinforcement learning function approximation in reinforcement learning theoretical foundations of reinforcement learning

Hi, this is Nan Jiang (姜楠). I am a machine learning researcher. I work on building the theoretical foundation of reinforcement learning (RL), especially in the function-approximation setting.

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Chilukuri K. Mohan

Particle Swarm Optimization (PSO) Reinforcement Learning Anomaly Detection in Cybersecurity

Chilukuri K. Mohan is a Professor in the Department of Electrical Engineering and Computer Science at Syracuse University, where he specializes in computational intelligence and its applications to complex real-world problems. His research spans the breadth of artificial intellig...

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Milos Hauskrecht

Time Series Analysis Structured Active Learning Reinforcement Learning

Dr. Hauskrecht is Professor of Computer Science, University of Pittsburgh. He received his Ph.D. from the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology in 1997. He received his M.Sc. in Electrical Engineering from the Slova...

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Peyman Najafirad

AI Security Knowledge Representation Probabilistic Decision Making

Peyman Najafirad (Paul Rad), Ph.D. is an Associate Professor of Computer Science and Associate Dean for Research and Partnerships in the College of AI, Cyber and Computing at The University of Texas at San Antonio. He earned his Ph.D. in Electrical and Computer Engineering and al...

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Guni Sharon

Reinforcement Learning Combinatorial Search Multiagent Route Assignment

Assistant professor, Texas A&M University, Department of Computer Science & Engineering Research Interests: Artificial Intelligence, Intelligent transportation systems, Reinforcement learning, Combinatorial optimization Dr. Sharon has a strong theoretical basis in artificial ...

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Martha White

Reinforcement Learning Continual Learning Algorithms Sustainable Machine Learning Systems

Martha White is an Associate Professor of Computing Science at the University of Alberta and a Fellow of Amii, which is one of the top machine learning centres in the world. She holds a Canada CIFAR AI Chair, a Tier 2 Canada Research Chair in Reinforcement Learning, received IEEE...

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Michael Schomaker

deep learning reinforcement learning cognitive modeling

Prof. Dr. Michael Schomaker is a full professor of Artificial Intelligence & Machine Learning at the Ludwig‑Maximilians‑Universität München (LMU), where he leads research and teaching at the intersection of machine learning, cognitive systems, and AI applications. He studie...

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Sriraam Natarajan

Statistical Relational Learning Reinforcement Learning Graphical Models

Sriraam Natarajan, Ph.D. is a Professor of Computer Science at The University of Texas at Dallas and Director of the Center for Machine Learning. His research interests include artificial intelligence, machine learning, statistical relational learning, reinforcement learning, gra...

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Roy Fox

reinforcement learning control theory information theory

Roy Fox is an Assistant Professor and founder of the Intelligent Dynamics Lab (indylab) in the Department of Computer Science in the Donald Bren School of Information & Computer Science at the University of California, Irvine. He’s affiliated with the Center for Machine Learnin...

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