US UC BerkeleyElectrical Engineering and Computer Sciences Dec 1
Develops deep reinforcement learning algorithms for decision making and control in robots.
2026 Cliqueformer: Model-Based Optimization with Structured Transformers AAAI 2026 Decoupled Q-Chunking ICLR 151 T1164 papers23 members45 alumniSG NTUCollege of Computing and Data Science
Studies multi-agent systems, computational game theory and reinforcement learning, with applications to security and e-commerce.
2026 A tighter bound for reward learning in reinforcement learning from human feedback TMLR 2026 AdverMCTS: Combating pseudo-correctness in code generation via adversarial Monte Carlo tree search ICML 120 T1146 papersGroup size not listed US UIUCSchool of Information Sciences Dec 1
Studies heterogeneous machine learning, active learning, neural bandits and self-supervised learning, with applications in security, healthcare and agriculture.
2026 AdaFuse: Adaptive Ensemble Decoding for Large Language Models ACL 2026 Auto-regressive In-context Demonstration Selection ICML 114 T1141 papers26 members41 alumniCN PekingInstitute for Artificial Intelligence Jan 15
Researches reinforcement learning, multi-agent systems, AI alignment and embodied intelligence.
2026 A Game-Theoretic Negotiation Framework for Cross-Cultural Consensus * ACL 2026 AdaMAP: Learning Adaptive Multi-Action Prediction with Grounded Dreaming Guidance NeurIPS 105 T1137 papers6 membersGB CambridgeDepartment of Applied Mathematics and Theoretical Physics Dec 8
Mihaela van der Schaar John Humphrey Plummer Professor of Machine Learning, AI and Medicine Develops machine learning and AI methods for medicine, including synthetic data, time-series analysis and models of clinical decision-making.
2026 A Study of Posterior Stability in Time-Series Latent Diffusion ICLR 2026 Deep Hierarchical Learning with Nested Subspace Networks for Large Language Models ICLR 100 T1120 papersGroup size not listed US UC BerkeleyElectrical Engineering and Computer Sciences Dec 1
Develops deep reinforcement learning, imitation learning and unsupervised learning methods for robot learning.
2026 Cliqueformer: Model-Based Optimization with Structured Transformers AAAI 2026 Contact-Aware Neural Dynamics CVPR 96 T1105 papersGroup size not listed CH ETH ZurichComputer Science (D-INFK)
Leads the Learning & Adaptive Systems group, working on probabilistic machine learning, Bayesian optimization, safe reinforcement learning and uncertainty…
2026 A Theoretical Analysis of Test-Driven Code Generation NeurIPS 2026 A Unified Density Operator View of Flow Control and Merging ICML 90 T1102 papers14 members37 alumniUS UIUCSiebel School of Computing and Data Science Dec 1
Studies machine learning theory and algorithms, including optimization, reinforcement learning and alignment of large language models.
2026 "A Sharp KL-Convergence Analysis for Diffusion Models under Minimal Assumptions ICLR 2026 "Almost linear convergence under minimal score assumptions: Quantized transition diffusion COLT 89 T1104 papers13 members36 alumniGB UCLDepartment of Computer Science
Jun Wang Professor of Information and Data Science Researches multi-agent reinforcement learning, deep generative models and information retrieval.
2026 A Benchmark for Deep Information Synthesis ICLR 2026 Bottlenecked Transformers: Periodic KV Cache Consolidation for Generalised Reasoning ICLR 86 T1135 papersGroup size not listed US UC BerkeleyElectrical Engineering and Computer Sciences Dec 1
Jason Lee Associate Professor Studies the theory of deep learning, representation learning and reinforcement learning.
2026 Coverage Improvement and Fast Convergence of On-policy Preference Learning ICML 2026 Improved high-dimensional estimation with Langevin dynamics and stochastic weight averaging ICLR 75 T176 papers8 members12 alumniCN TsinghuaDepartment of Computer Science and Technology Feb 28
Hang Su Associate Professor Works on trustworthy and explainable AI, adversarial robustness, computer vision, and reinforcement learning.
2026 A Survey on Autonomy-Induced Security Risks in Large Model-Based Agents TPAMI 2026 AEMIM: Adversarial Examples Meet Masked Image Modeling IJCV 73 T1103 papersGroup size not listed CH EPFLInstitute of Electrical and Micro Engineering (IEM, School of Engineering STI) Dec 1
Leads the Laboratory for Information and Inference Systems, working on optimization theory, reinforcement learning and robust deep learning.
2026 Diffusion-based Cumulative Adversarial Purification for Vision Language Models TMLR 2026 ESLM: Risk-Averse Selective Language Modeling with Hierarchical Batch Selection TMLR 71 T187 papers7 members25 alumniUS UT AustinComputer Science Dec 15
Peter Stone Professor, Truchard Foundation Chair in Computer Science Leads the Learning Agents Research Group, working on reinforcement learning, multiagent systems, robot soccer and autonomous agents.
2026 Coadaptive Value Alignment AAMAS 2026 Factored Latent Action World Models ICML 68 T1117 papers10 members48 alumniCN SJTUSchool of Computer Science May 31
Works on reinforcement learning, agentic AI and physical AI, focusing on foundation models for physical agents.
2025 Action First: Leveraging Preference-Aware Actions for More Effective Decision-Making in Interactive Recommender Systems SIGIR 2025 AgentNet: Decentralized Evolutionary Coordination for LLM-based Multi-Agent Systems NeurIPS 58 T171 papersGroup size not listed CN TsinghuaInstitute for Interdisciplinary Information Sciences (IIIS) Feb 28
Huazhe Xu Assistant Professor Works on deep reinforcement learning, robotics, computer vision, and tactile sensing.
2025 A Forget-and-Grow Strategy for Deep Reinforcement Learning Scaling in Continuous Control ICML 2025 Catch It! Learning to Catch in Flight with Mobile Dexterous Hands ICRA 57 T158 papers12 membersCH ETH ZurichComputer Science (D-INFK)
Niao He Associate Professor Leads the Optimization and Decision Intelligence group, studying large-scale stochastic and minimax optimization, reinforcement learning theory and…
2026 A Convex Framework for Confounding Robust Inference JMLR 2026 A Schrodinger Eigenfunction Method for Long-Horizon Stochastic Optimal Control ICLR 56 T168 papers11 members12 alumniCN TsinghuaInstitute for Interdisciplinary Information Sciences (IIIS) Feb 28
Yang Gao Assistant Professor Works on computer vision and reinforcement learning for robot learning.
2026 Best of Sim and Real: Decoupled Visuomotor Manipulation via Learning Control in Simulation and Perception in Real ICRA 2026 EasyInsert: A Data Efficient and Generalizable Insertion Policy IROS 53 T153 papers18 members6 alumniUS CMUMachine Learning Department Dec 9
Steven Wu Associate Professor Studies trustworthy machine learning, including privacy, AI safety, interactive learning and reinforcement learning.
2026 All Roads Lead to Likelihood: The Value of Reinforcement Learning in Fine-Tuning ICLR 2026 Back to Blackwell: Closing the Loop on Intransitivity in Multi-Objective Preference Fine-Tuning NeurIPS 52 T171 papers8 members16 alumniHK CUHKDepartment of Computer Science and Engineering Dec 1
John C. S. Lui Choh-Ming Li Professor of Computer Science and Engineering Works on online learning such as multi-armed bandits and reinforcement learning, network science and quantum networks.
2026 Constraint-Aware Combinatorial Bandits: Theoretical Foundations and Network Applications INFOCOM 2026 Faster, Smaller, and Smarter: Task-Aware Expert Merging for Online MoE Inference INFOCOM 51 T1155 papersGroup size not listed US UT AustinDepartment of Aerospace Engineering and Engineering Mechanics Dec 15
Ufuk Topcu Associate Professor Cockrell Family Dean's Chair for Engineering Excellence Designs and verifies autonomous systems, combining formal methods, control and learning for safe decision-making.
2026 Do LLMs Strategically Reveal, Conceal, and Infer Information? A Theoretical and Empirical Analysis in The Chameleon Game AAMAS 2026 IG-MCTS: Human-in-the-Loop Cooperative Navigation under Incomplete Information AAMAS 51 T1125 papers17 members24 alumni