PROFESSORS IN REINFORCEMENT LEARNING

Showing page 3 of 3 — 50 professors available publicly

Dong Dai

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

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

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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Vignesh Narayanan

Vignesh Narayanan

Human-Centered Autonomy Reinforcement Learning Information Theory

Vignesh Narayanan is an Assistant Professor in the Department of Computer Science and Engineering and the Artificial Intelligence Institute (AIISC) at the University of South Carolina. His research is at the forefront of dynamical systems, control theory, and artificial intellige...

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Isabeau Prémont-Schwarz

Isabeau Prémont-Schwarz

brain-inspired artificial intelligence reinforcement learning combinatorial generalization

Isabeau Prémont-Schwarz is a professor of artificial intelligence. He is interested in brain-inspired AI, agent learning (including reinforcement learning), combinatorial generalization, and how to form "good" abstractions.

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Dr. Dongchul Kim

Dr. Dongchul Kim

reinforcement learning multi-agent reinforcement learning robotic control

I am an Associate Professor in the Department of Computer Science at The University of Texas Rio Grande Valley, where I also serve as the Graduate Program Coordinator. My research focuses on reinforcement learning, multi-agent reinforcement learning, robotic control, and drug dis...

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Kwanghee Won

Kwanghee Won

Intelligent Vision Systems Autonomous Vehicles Deep Convolutional Neural Networks

Dr. Kwanghee Won is an Associate Professor in the Department of Electrical Engineering and Computer Science at South Dakota State University, where he specializes in Intelligent Vision Systems and Autonomous Vehicles. He earned his B.S., M.S., and Ph.D. in Computer Engineering fr...

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Dr. Sihong He

Dr. Sihong He

Robust Multi-Agent Reinforcement Learning Robust Optimization Cyber-Physical Systems (CPS)

Dr. Sihong He is a Tenure-Track Assistant Professor at UTA, with a distinguished academic and research background in artificial intelligence, reinforcement learning, robust optimization, and robust learning. Dr. He earned her Ph.D. in Computer Science from the University of Conne...

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Srijita Das

Srijita Das

Active Learning Cost-Sensitive Learning Reinforcement Learning

I am currently a tenure-track Assistant Professor in the Computer & Information Sciences department at University of Michigan-Dearborn. Prior to that, I spent three wonderful years at University of Alberta working with Prof. Matt Taylor as part of the Intelligent Robot Learni...

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Dr. Mulong Luo

Dr. Mulong Luo

Large Language Models (LLMs) Reinforcement Learning AI for Security

Dr. Luo’s research spans the broad areas of computer security, computer systems, AI for security, and AI security. In particular, he is interested in how modern AI techniques—such as large language models (LLMs) and reinforcement learning—can help build more secure computer...

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