Explore professors working in reinforcement learning and related research areas.
Use YourScholar to discover research opportunities and identify
professors whose work aligns with your academic interests.
Professors in Reinforcement Learning
Showing page 3 of 3 —
59 professors available publicly
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...
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,...
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...
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...
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.
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...
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...
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...
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...
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...
Rodrigo Canaan
evolutionary computing
quality-diversity algorithms
reinforcement learning
Rodrigo Canaan is an Assistant Professor in the Computer Science and Software Engineering Department at California Polytechnic State University (Cal Poly). His research focuses on artificial intelligence, games, and co-creativity, with particular interests in evolutionary computi...
Ryan Shi
Societal Computing
Game Theory
Online Learning
Before joining SCI, Ryan Shi was a Ph.D. candidate of Societal Computing in the School of Computer Science at Carnegie Mellon University. He works with nonprofit organizations to address societal challenges in food security, environmental conservation, and public health using AI....
Fei Dou
Federated Learning
Reinforcement Learning
Self-Supervised Learning
Fei Dou is an Assistant Professor in the School of Computing at the University of Georgia. She obtained her Ph.D. in 2023 from the Department of Computer Science and Engineering at the University of Connecticut, where she worked in the Laboratory of Machine Learning & Health Info...
Ruiquan Huang
deep learning
reinforcement learning
trustworthiness of ML/AI systems
My research interests lie broadly in Machine Learning (ML) and Artificial Intelligence (AI), with a particular focus on deep learning, reinforcement learning, and the trustworthiness of ML/AI systems.
Qi Zhang
Cooperative Artificial Intelligence
Reinforcement Learning
Multi-Agent Systems
Qi Zhang is an Assistant Professor in the Computer Science Department and the Data Science & Artificial Intelligence program at Worcester Polytechnic Institute (WPI). He joined WPI in July 2025, having previously served as an Assistant Professor at the University of South Carolin...
Md Tamjid Hossain
Adversarial Machine Learning
Federated Learning
Reinforcement Learning
Md Tamjid Hossain is a privacy and security expert currently serving as an Assistant Professor (Tenure-track) of Computer Science and Cybersecurity and the director of CiPH3R-Lab (https://ciph3rlab.github.io/) at Texas A&M University-San Antonio (A&M-SA). His research interests i...
Duy Ho
AI-empowered Robotics
Augmented Reality
Virtual Reality
Dr. Duy Ho received his Ph.D. from the University of Missouri-Kansas City.
Topics of interest: AI-empowered Robotics, Web/Mobile Application Development, Augmented/Virtual/Mixed Reality, Reinforcement/Imitation/Curriculum Learning
Lokesh Das
Vehicle-to-Everything (V2X) Communication
Reinforcement Learning
Next-Generation Traffic Control Systems
Dr. Lokesh Das’s current research focuses on developing novel algorithms for the next-generation traffic control system for autonomous vehicles utilizing modern deep learning and vehicle-to-everything (V2X) communication technologies to reduce traffic congestion and enhance tra...
Mohammad Rahman
Cyber-Physical Systems (CPS)
Quantum Machine Learning (QML)
Blockchain Security
Mohammad Arafatur Rahman is assistant professor at Tuskegee University. His research interests include CPS, QML, Security, Reinforcement Learning, and Blockchain.