US UT AustinElectrical and Computer Engineering Dec 15
Leads the VITA Group, working on efficient and robust deep learning, sparse neural networks and large language models.
2026 A Physics-Grounded Benchmark for Multi-Agent Dynamics in World Models ECCV 2026 Beyond Test-Time Memory: State-Space Optimal Control for LLM Reasoning ICML 165 T1197 papers15 members45 alumniUS 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 CN ZhejiangCollege of Computer Science and Technology Feb 28
Studies data security and privacy, AI security, and security of IoT, smart devices and connected vehicles.
2026 A Causal Perspective for Enhancing Jailbreak Attack and Defense NDSS 2026 A Survey on Medical Large Language Models: Technology, Application, Trustworthiness, and Future Directions TKDE 120 T1295 papers16 members23 alumniUS UMDComputer Science
Develops machine learning, large-scale optimization and AI methods for biomedical data science and computational health.
2026 An Ensemble Framework for Unbiased Language ModelWatermarking ICLR 2026 Analyzing and Evaluating Unbiased Language Model Watermark ICLR 117 T1141 papersGroup size not listed CN ZhejiangSchool of Artificial Intelligence Feb 28
Kun Kuang Associate Professor Studies causal inference and its integration with machine learning, including causal AI for smart justice and domain-specific large models.
2026 "I Don’t Know What to Say": A Fact-Filling Questionnaire Method to Help Non-Experts Talk to LegalAI Assistant ACL 2026 Asynchronous Denoising Diffusion Models for Aligning Text-to-Image Generation ICLR 115 T1143 papersGroup size not listed CN PekingCenter for Machine Learning Research Jan 15
Researches data-centric machine learning, graph machine learning and ML systems.
2026 AD-MIR: Bridging the Gap from Perception to Persuasion in Advertising Video Understanding via Structured Reasoning ICML 2026 AgenticOCR: Parsing Only What You Need for Efficient Retrieval-Augmented Generation NeurIPS 115 T1184 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 membersSG NTUCollege of Computing and Data Science
Yu Cheng Nanyang Associate Professor (NRF) Works on efficient and sparse model architectures, model compression and multimodal learning.
2026 AdaReasoner: Dynamic Tool Orchestration for Iterative Visual Reasoning ICLR 2026 Characterizing, Evaluating, and Optimizing Complex Reasoning ICML 105 T1118 papers42 membersCH ETH ZurichComputer Science (D-INFK)
Researches machine learning and causal inference, including causal representation learning, kernel methods and applications in the sciences.
2026 Hyperbolic Busemann Neural Networks CVPR 2026 Learning Nonlinear Causal Reductions to Explain Reinforcement Learning Policies ICLR 98 T1141 papersGroup size not listed US StanfordComputer Science Dec 8
Stefano Ermon Associate Professor of Computer Science and Senior Fellow at the Woods Institute for the Environment Develops probabilistic and generative models such as diffusion models, with applications to sustainability.
2026 Adaptive Spectral Feature Forecasting for Diffusion Sampling Acceleration CVPR 2026 Align Your Structures: Generating Trajectories with Structure Pretraining for Molecular Dynamics ICLR 97 T1114 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 MITBrain and Cognitive Sciences Dec 1
Studies computational cognitive science and cognitive AI, building computational models of human cognition with machine learning.
2026 Evaluating Language Models' Evaluations of Games ICLR 2026 ExoPredicator: Learning Abstract Models of Dynamic Worlds for Robot Planning ICLR 90 T1158 papers16 membersUS CMUDepartment of Philosophy Dec 9
Develops methods for causal discovery and causal representation learning, aiming at explainable and controllable AI from a causal perspective.
2026 Ada-Diffuser: Latent-Aware Adaptive Diffusion for Decision-Making ICLR 2026 Beyond DAGs: A Latent Partial Causal Model for Multimodal Learning ICLR 90 T1143 papersGroup size not listed HK CUHKDepartment of Computer Science and Engineering Dec 1
Works on machine learning, graph neural networks, recommender systems, social computing and natural language processing.
2026 Advancing Multi-Agent RAG Systems with Minimalist Reinforcement Learning AAMAS 2026 Adversarial Encoding Perturbation and Synthesis for Set Representation Auxiliary Learning ICLR 89 T1141 papers27 members10 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 alumniCN PekingInstitute for Artificial Intelligence Jan 15
Researches machine learning, causal inference, trustworthy AI and large-model training and inference.
2026 A Relative Error-Based Evaluation Framework of Heterogeneous Treatment Effect Estimators ICLR 2026 Bayesian Causal Experimental Design for CATE Estimation under Noncompliance NeurIPS 88 T1123 papersGroup size not listed GB 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 SG NUSDepartment of Computer Science Dec 15
Works on probabilistic and data-efficient machine learning, including Bayesian optimisation, Gaussian processes and federated and collaborative learning.
2026 ActiveDPO: Active Direct Preference Optimization for Sample-Efficient Alignment ICLR 2026 Adalina: Adaptive Linear Approximation for the Shapley Value and Beyond ICML 79 T189 papers28 members40 alumni