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 UIUCSiebel School of Computing and Data Science Dec 1
Studies large-scale data mining and machine learning on graphs, including graph neural networks and network analysis.
2026 A Hands-on Tutorial for Diffusion Language Models with dLLM KDD 2026 Certified Defense on the Fairness of Graph Neural Networks KDD 92 T1123 papers14 members28 alumniHK 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 alumniCN TsinghuaDepartment of Computer Science and Technology Feb 28
Works on graph machine learning, network embedding, pre-trained graph and language models, and social network mining.
2026 ComputerRL: Scaling End-to-End Online Reinforcement Learning for Computer Use Agents ICLR 2026 GSPNet: Graph Spectral Projection Network Using Learnable Spectral Transformation TPAMI 70 T182 papers12 membersCN 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 alumniCN PekingSchool of Intelligence Science and Technology Jan 15
Researches machine learning and deep learning, including adversarial robustness, graph learning and weakly supervised learning.
2026 A Theoretical Framework for Masked Pretraining (MPT) JMLR 2026 Autoregressive Models Rival Diffusion Models at ANY-ORDER Generation ICLR 57 T160 papers14 members6 alumniGB CambridgeComputer Science and Technology Dec 8
Pietro Liò Professor of Computational Biology Develops AI and computational biology models, currently graph neural networks, to understand disease complexity for personalised and precision medicine.
2026 Autohformer: Efficient Hierarchical Autoregressive Transformer for Time Series Prediction ICDE 2026 Fast and Interpretable Protein Substructure Alignment via Optimal Transport ICLR 47 T1167 papersGroup size not listed · 43 alumniHK CUHKDepartment of Systems Engineering and Engineering Management Dec 1
Works on data mining, graph learning and knowledge management.
2026 A Unified Framework for Dense Subgraph Maintenance over Dynamic Bipartite Graphs SIGMOD 2026 Beyond Structure: Invariant Crystal Property Prediction with Pseudo-Particle Ray Diffraction ICLR 44 T154 papersGroup size not listed US UCLAComputer Science Dec 15
Develops graph neural networks, knowledge graph reasoning and network mining, with applications to science and chip design.
2026 ARLArena: A Unified Framework for Stable Agentic Reinforcement Learning ICML 2026 Beyond Length: Quantifying Long-Range Information for Long-Context LLM Pretraining Data ICLR 42 T1102 papers12 members18 alumniUS Georgia TechElectrical and Computer Engineering Dec 15
Pan Li Associate Professor Studies machine learning on graphs, including geometric deep learning for science and graph methods for trustworthy LLMs.
2026 ∇-Reasoner: LLM Reasoning via Test-Time Gradient Descent in Latent Space ICLR 2026 How Can State Space Models Enhance Machine Learning on Graphs? TPAMI 41 T160 papers7 members20 alumniCN SJTUSchool of Computer Science May 31
Works on big data processing and analytics, including temporal graph neural networks and learned models for stock trend forecasting (MASTER, DoubleAdapt).
2026 CoShap: A Scalable Coalition Growth Approach to Shapley Value Approximation SIGMOD 2026 DeMix: Debugging Training Data with Mixed Data Error Types by Investigating Influence Vectors KDD 39 T191 papersGroup size not listed SG NTUCollege of Computing and Data Science
Works on data management, data mining and machine learning, including graph learning and data-intensive algorithms.
2026 A Comprehensive Benchmark on Spectral GNNs: The lmpact on Efficiency, Memory, and Effectiveness. SIGMOD 2026 ArceKV: Towards Workload-driven LSM-compactions for Key-Value Store Under Dynamic Workloads. VLDB 36 T146 papers10 members7 alumniUS NYUComputer Science (NYU Shanghai) Dec 12
Studies graph machine learning, graph foundation models and multimodal learning, with applications in bioinformatics and healthcare.
2026 AgentGL: Towards Agentic Graph Learning with LLMs via Reinforcement Learning ACL 2026 ChronoClinQA: A Longitudinal Multi-Admission Benchmark for Clinical Reasoning over Electronic Health Records EMNLP 30 T140 papers9 members4 alumniGB ImperialDepartment of Computing Dec 1
Joey Bose Assistant Professor of Computing Leads the Bose Lab building generative models for science, including geometric deep learning and flow-based models for molecules and proteins.
2026 Aligning Flow Map Policies with Optimal Q-Guidance NeurIPS 2026 Autoregressive Boltzmann Generators ICML 24 T128 papers7 members2 alumniUS UCSDHalıcıoğlu Data Science Institute Dec 15
Develops geometric and topological data analysis methods and graph neural networks with theoretical guarantees.
2026 Beyond FlatWalks: Compositional Abstraction for Autoregressive Graph Generation NeurIPS 2026 Do Graph Neural Networks Learn Generalizable Algorithms for Clustering Graphs? NeurIPS 24 T135 papersGroup size not listed CN PekingSchool of Intelligence Science and Technology Jan 15
Researches machine learning, including Transformer and graph neural network architectures and ML for science such as molecular modeling.
2026 Diagnosing and Improving Diffusion Models by Estimating Optimal Loss Value ICLR 2026 Efficient Reasoning for Large Reasoning Language Models via Certainty-Guided Reflection Suppression AAAI 22 T130 papersGroup size not listed US UIUCSiebel School of Computing and Data Science Dec 1
Studies graph machine learning and LLM agents, including graph neural networks and multi-agent LLM systems.
2025 Beyond Facts: Evaluating Intent Hallucination in Large Language Models ACL 2025 ConsistencyChecker: Tree-based Evaluation of LLM Generalization Capabilities ACL 21 T123 papersGroup size not listed CH ETH ZurichComputer Science (D-INFK)
Leads the Interactive Geometry Lab, working on geometry processing, shape deformation and editing, discrete differential geometry and geometric deep learning.
2026 2D Gaussian Splatting for Bézier Spline Line Art Vectorization SIGGRAPH 2026 Fabricating 3D Shapes by Shrinking-Thread Embroidery SIGGRAPH Asia 18 T137 papers3 members29 alumniUS NYUComputer Science (Courant) Dec 12
Joan Bruna Professor of Computer Science and Data Science Studies the mathematical foundations of deep learning, including high-dimensional statistics, neural network optimization and geometric deep learning.
2025 Axial Neural Networks for Dimension-Free Foundation Models NeurIPS 2025 Benefits of Rank in Attention Layers ICLR 17 T119 papers3 members25 alumniUS UT AustinElectrical and Computer Engineering Dec 15
Develops ML methods for embedded and edge systems, including efficient vision transformers, graph neural networks and federated learning.
2026 Fuel Gauge: Estimating Chain-of-Thought Length Ahead of Time in Large Multimodal Models CVPR 2026 NeuS-QA: Grounding Long-Form Video Understanding in Temporal Logic and Neuro-Symbolic Reasoning AAAI 17 T156 papers5 members47 alumni