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 alumniCN PekingSchool of Computer Science Jan 15
Leads research on database systems and large-scale machine learning systems, including distributed training and data management for AI.
2026 ChartVerse: Scaling Chart Reasoning via Reliable Programmatic Synthesis from Scratch ACL 2026 DARTS: Distribution-Aware Active Rollout Trajectory Shaping for Accelerating LLM Reinforcement Learning ICML 118 T1187 papers36 members64 alumniCN 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 SG 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 CN 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 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 alumniCN SJTUSchool of Computer Science May 31
Works on parallel and cloud computing and compilers, with recent work on accelerating LLMs through hardware-friendly quantization (OliVe) and deep learning…
2026 Accelerating MoE with Dynamic In-Switch Computing on Multi-GPUs ISCA 2026 Arena: Efficiently Training Large Models via Dynamic Scheduling and Adaptive Parallelism Co-Design EuroSys 74 T1217 papersGroup size not listed CN SJTUSchool of Artificial Intelligence May 31
Works on compression and acceleration of AI models and data, including self-distillation.
2026 Accelerating Diffusion Large Language Models with SlowFast Sampling: The Three Golden Principles ICLR 2026 Accelerating Diffusion Transformers with Gaussian Process Rectified Feature Cache ECCV 71 T189 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 alumniSG NUSDepartment of Computer Science Dec 15
Yang You NUS Presidential Young Professor Leads the HPC-AI Lab on scaling deep neural network training on distributed systems, including the LAMB optimiser.
2026 ASCIIEval: Benchmarking Models' Visual Perception in Text Strings via ASCII Art ICLR 2026 DyDiT++: Diffusion Transformers With Timestep and Spatial Dynamics for Efficient Visual Generation TPAMI 64 T185 papers15 members29 alumniCN PekingInstitute for Artificial Intelligence Jan 15
Researches graph machine learning, graph neural networks and graph foundation models, and efficient LLM architectures and reasoning.
2026 CanvasMAR: Improving Masked Autoregressive Video Prediction With Canvas NeurIPS 2026 Coevolutionary Continuous Discrete Diffusion: Make Your Diffusion Language Model a Latent Reasoner ICML 61 T177 papers9 members4 alumniCH 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 ZhejiangCollege of Computer Science and Technology Feb 28
Huan Li ZJU 100-talent Program Professor Researches data-centric, resource-efficient and scalable AI, building on earlier work in data management.
2026 AdaCTSi: Adaptive Correlated Time Series Imputation for Changing Environments TKDE 2026 AgentTailor: Dual-Gate LLM-Assisted Re-ranking for Personalized Long-Tail Recommendation NeurIPS 55 T178 papers25 members7 alumniUS NYUComputer Science (Courant) Dec 12
Andrew Gordon Wilson Professor of Computer Science and Data Science Works on Bayesian deep learning, Gaussian processes and generalization in neural networks, with numerical linear algebra for scalable inference.
2026 A Unification of Discrete, Gaussian, and Simplicial Diffusion ICLR 2026 Diverse Dictionary Learning ICLR 53 T158 papers7 members11 alumniUS CMULanguage Technologies Institute Dec 9
Lei Li Associate Professor Studies large language models, machine translation and AI for science, including efficient LLM inference.
2026 AdaSplash-2: Faster Differentiable Sparse Attention ICML 2026 CodeEvo: Interaction-Driven Synthesis of Code-centric Data through Hybrid and Iterative Feedback ACL 52 T177 papers19 members16 alumniUS CMUElectrical and Computer Engineering Dec 9
Designs efficient algorithms and systems for training and serving large language models, including sparsity and long-context inference.
2026 AstraFlow: Dataflow-Oriented Reinforcement Learning for Agentic LLMs ↗ NeurIPS 2026 CamoDocs: A Poisoning Attack Against Retrieval-Augmented Language Models Using Camouflaged Documents ↗ EMNLP 51 T154 papers5 members13 alumniUS Georgia TechSchool of Computational Science and Engineering Dec 15
Chao Zhang Edenfield Early-Career Associate Professor Researches label-efficient text mining, knowledge extraction and natural language processing with large language models.
2026 MLE-Smith: Scaling MLE Tasks with Automated Multi-agent Pipeline ICLR 2026 Towards Diverse Scientific Hypothesis Search with Large Language Models ICML 51 T166 papers9 members9 alumniUS UCLAComputer Science Dec 15
Studies scalable optimization, adversarial robustness and verification of neural networks, and efficient training of large models.
2025 Don't Think Longer, Think Wisely: Optimizing Thinking Dynamics for Large Reasoning Models NeurIPS 2025 Is Your Multimodal Language Model Oversensitive to Safe Queries? ICLR 50 T161 papers13 members18 alumniUS StanfordComputer Science Dec 8
Christopher Ré Professor of Computer Science Leads Hazy Research on efficient foundation model architectures, data-centric AI and ML systems.
2026 An Information Theoretic Perspective on Agentic System Design ICLR 2026 Cartridges: Lightweight and general-purpose long context representations via self-study ICLR 49 T157 papers11 members29 alumni