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PROFESSORS IN REINFORCEMENT LEARNING

Showing page 2 of 3 — 50 professors available publicly

Mark Nelson

procedural content generation automated game design reinforcement learning

I'm a computer scientist with a background in artificial intelligence (AI). My research focuses mostly on AI & games, especially procedural content generation and automated game design. I've also done some work in reinforcement learning, evolutionary computation, creativity suppo...

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Luis Ortiz

Artificial Intelligence (AI) Machine Learning Reinforcement Learning

I am an Associate Professor at the Department of Computer and Information Science at the University of Michigan - Dearborn, a position I have held since September 2018. I was an Assistant Professor from September 2015 until August 2018. From August 2008 through August 2015, I ...

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Byung-Cheol Min

human-robot interaction reinforcement learning learning from demonstration

Dr. Byung-Cheol (“B.C.”) Min is a Professor with a joint appointment in the Department of Computer Science and the Department of Intelligent Systems Engineering at the Luddy School of Informatics, Computing, and Engineering, Indiana University Bloomington. He joined the unive...

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Adam White

Reinforcement Learning Continual Learning Intrinsic Motivation

Adam White, PhD is an Associate Professor in the Department of Computing Science at the University of Alberta, a Canada CIFAR AI Chair, and Director of the Alberta Machine Intelligence Institute (Amii). His research focuses on reinforcement learning, continual learning, robotics,...

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Mahdi Khodayar

Deep Learning Spatiotemporal Pattern Recognition Reinforcement Learning

Mahdi Khodayar, Ph.D., received his B.Sc. degree in computer engineering and the M.Sc. degree in artificial intelligence from K.N. Toosi University of Technology, Tehran, Iran, in 2013 and 2015, respectively, and a Ph.D. degree in electrical engineering from Southern Methodist Un...

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Nghia Hoang

Federated Learning Bayesian Methods for Big Data Neural Networks

Education: B.Sc. in University of Science (Vietnam), 2009 Ph.D. in Computer Science, National University of Singapore (Singapore), 2015 – PhD Thesis Work Experience: 2015 - 2017: Research Fellow, National University of Singapore (NUS), Singapore 2017 - 2018: Postdoctoral...

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Xiangnan Zhong

Adaptive Dynamic Programming (ADP) Reinforcement Learning Computational Intelligence

Xiangnan Zhong is currently an Associate Professor with the Department of Electrical Engineering and Computer Science, Florida Atlantic University (FAU), Boca Raton, FL, USA. She received the Ph.D. degree in Electrical, Computer, and Biomedical Engineering from University of Rhod...

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Josiah Hanna

Reinforcement Learning Data-Efficient Reinforcement Learning Autonomous Agents Learning

Josiah Hanna is an assistant professor in the Computer Sciences Department at the University of Wisconsin -- Madison. He received his Ph.D. in the Computer Science Department at the University of Texas at Austin. Prior to attending UT Austin, he completed his B.S. in computer sci...

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Dean Hougen

Artificial Neural Networks Deep Learning Interpretable Machine Learning

Dr. Dean F. Hougen is a professor in the School of Computer Science at the University of Oklahoma. Dr. Hougen has a PhD in Computer Science and Engineering from the University of Minnesota, with a graduate minor in Cognitive Science, and a BS in Computer Science from Iowa State U...

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Samira Sadaoui

Adaptive Machine Learning Incremental/Decremental Learning Concept Drift Learning

Obtained MSc and PhD in Computer Science from the University of Nancy I, France Currently Professor of Computer Science at the University of Regina, Regina, Canada Current research interests are in Artificial Intelligence, including: Adaptive Machine Learning, Incremental/Decre...

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Minwoo Jake Lee

reinforcement learning interpretational learning transfer learning

I am an associate professor in the Department of Computer Science and School of Data Science, University of North Carolina at Charlotte (Charlotte). I am working on machine learning algorithms for reinforcement learning. My interests focus on various topics in machine learning, w...

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Shangtong Zhang

reinforcement learning theoretical reinforcement learning empirical reinforcement learning

Shangtong Zhang is an Alf Weaver Assistant Professor in the Department of Computer Science at the University of Virginia, directing the Sequential Intelligence Lab (SIL). His research focuses on both theoretical and empirical aspects of reinforcement learning, resulting in multip...

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Tyler Bonnell

Agent-Based Modeling (ABM) Reinforcement Learning Geospatial Statistical Tools

Dr. Tyler Ronald Bonnell is an Assistant Professor in the Department of Computer Science and the Department of Psychology (Adjunct) at the University of Calgary, where he also serves as the Co-Director of the Data Science and Analytics program. He leads the Behavioural Ecology an...

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Genya Ishigaki

Network Slicing Network Caching Combinatorial Optimization

Genya Ishigaki is an Assistant Professor at San Jose State University. He received his Ph.D. and M.S. in Computer Science from The University of Texas at Dallas in 2021, and his B.S. and M.S. in Engineering from Soka University, Japan. His research interests include network slici...

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Zoran Tiganj

Natural Language Processing (NLP) Reinforcement Learning Spatial Navigation

Zoran Tiganj received his Ph.D. in computer science from INRIA in 2011 and his M.S. degree in electrical engineering from University of Zagreb in 2008. He worked as a postdoctoral associate at University of Versailles 2011-2012, and as a postdoctoral associate and research scient...

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Kianté Brantley

Natural Language Processing (NLP) reinforcement learning imitation learning

I am an Assistant Professor of Computer Science at Kempner Institute and School of Engineering and Applied Sciences (SEAS), Harvard University. My research focuses on problems at the intersection of machine learning and interactive decision-making, with the goal of improving the ...

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Haipeng Chen

Use-Inspired AI Reinforcement Learning Generative AI

Haipeng Chen is an assistant professor and graduate program director of the Data Science Department at William & Mary. He directs the W&M Data-Driven Decision Intelligence (D3i) Lab. Externally, he serves as the vice chair of the AI Blue Ribbon Collaborative at Center for Telehea...

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Dong Dai

parallel file systems metadata management graph storage

Dong Dai works on optimizing and designing intelligent infrastructure for high-performance, data-intensive systems, such as parallel file systems, metadata management, graph storage, and job scheduling. His recent work focuses on using various learning methods (e.g., deep learnin...

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Sen Lin

Continual Learning Reinforcement Learning Large Language Models

Sen Lin is an Assistant Professor in the CS department at University of Houston. Previously, he was a Postdoc in the NSF AI-EDGE Institute at The Ohio State University. His research interests broadly fall in the intersection of machine learning and wireless networking. Currently,...

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Banafsheh Rekabdar

Reinforcement Learning Variational Autoencoders (VAEs) Diffusion Models

I’m an Assistant Professor in the Department of Computer Science at Portland State University and Director of the Artificial Intelligence Lab. My research focuses on reinforcement learning and generative AI (e.g., VAEs, diffuison models), with an emphasis on robust and mult...

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