Studies machine learning theory and sequential decision making, with applications in chemistry and psychiatry.
Learning theory & optimization
Reinforcement learning
Proteins, drugs & materials
2026A characterization of list language identification in the limitCOLT
2026A semantic-based community model for high-fidelity tuning of olfactory mixture distancesPNAS
41 T1 · 67 papers · 10 members · 88 alumni
USMichiganComputer Science and Engineering
Danai KoutraAssociate Professor, EECS – Computer Science and Engineering
Studies data mining and graph learning, including graph summarization, network alignment and large-scale graph analysis.
Graph mining & networks
Data management & big data
Trustworthy & safe ML
2026AgentDR: Dynamic Recommendation with Implicit Item-Item Relations via LLM-based AgentsWWW
2026Beyond Unimodal Perspectives: Generative Retrieval with Multimodal SemanticsSIGIR
34 T1 · 43 papers · 8 members · 46 alumni
USMichiganComputer Science and Engineering
Joyce ChaiProfessor, EECS – Computer Science and Engineering
Studies natural language processing grounded in vision and robotics, including situated human-machine communication and interactive task learning.
Multimodal & grounded language
Signal processing & information theory
2026Fast Spatial Memory with Elastic Test-Time TrainingECCV
2026RoboMME: Benchmarking and Understanding Memory for Robotic Generalist PoliciesICML
34 T1 · 49 papers · 7 members · 88 alumni
USMichiganComputer Science and Engineering
Lu WangAssociate Professor, EECS – Computer Science and Engineering
Studies natural language processing, including text summarization, trustworthy and safe language models and AI evaluation.
Interpretability, evaluation & safety of LMs
Large language models
Trustworthy & safe ML
2026AdaMEM: Test-Time Adaptive Memory for Language AgentsICML
2026CASPER in the Machine: Insights into Character Variety in LLM-Generated StoriesACL
34 T1 · 60 papers · 7 members · 17 alumni
USMichiganElectrical and Computer Engineering
Qing QuAssistant Professor, EECS – Electrical and Computer Engineering
Studies high-dimensional data analysis and nonconvex optimization for machine learning, including the theory of deep and diffusion models and computational…
Learning theory & optimization
Generative & foundation models
Computational imaging & photography
2026AlphaFlow: Understanding and Improving MeanFlow ModelsICLR
2026Generalization of Diffusion Models Arises with a Balanced Representation SpaceICLR
31 T1 · 41 papers · Group size not listed
USMichiganElectrical and Computer Engineering
Samet OymakAssociate Professor, EECS – Electrical and Computer Engineering
Studies principled methods and theory for machine learning, including the foundations of transformers and resource-efficient, trustworthy learning.
Learning theory & optimization
Trustworthy & safe ML
Efficient training & inference
2026Continuous Chain of Thought Enables Parallel Exploration and ReasoningICLR
2026SmartChunk Retrieval: Query-Aware Chunk Compression with Planning for Efficient Document RAGICLR
30 T1 · 38 papers · Group size not listed
USMichiganComputer Science and Engineering
Rada MihalceaJanice M. Jenkins Collegiate Professor of Computer Science and Engineering; Professor, EECS – Computer Science and Engineering; Director, Artificial Intelligence Lab
Studies natural language processing and computational social science, including multimodal understanding of human behavior.
Language & society
Multimodal & grounded language
Vision-language & multimodal
2026AtlasNLP: A Country-Aware Atlas of Dataset Representation in NLPEMNLP
2026Copyright Detective: A Forensic System to Evidence LLMs Flickering Copyright Leakage RisksACL
26 T1 · 108 papers · 16 members · 102 alumni
USMichiganComputer Science and Engineering
Stella YuProfessor, EECS – Computer Science and Engineering
Studies visual perception in computer vision, including unsupervised and grouping-based learning of visual representations.
Recognition, detection & segmentation
Robot perception & SLAM
2026Adaptive Optical Correction for in vivo Two-Photon Fluorescence Microscopy with Neural FieldsNature Methods
2026Aligning Forest and Trees in Images and Long Captions for Visually Grounded UnderstandingNeurIPS
23 T1 · 45 papers · 15 members · 59 alumni
USMichiganRobotics
Maani GhaffariAssociate Professor, Naval Architecture and Marine Engineering and Robotics
Studies robot perception, machine learning and planning under uncertainty, including geometric and equivariant methods for state estimation.
Robot perception & SLAM
Planning, control & multi-robot systems
Probabilistic & causal inference
2026Ego-Vision World Model for Humanoid Contact PlanningICRA
2026RIGS: Radar-Informed Gaussian Splatting for Uncertainty-Aware 3D Occupancy and Motion PredictionECCV
19 T1 · 45 papers · 9 members · 46 alumni
USMichiganComputer Science and Engineering
Jeong Joon ParkAssistant Professor, EECS – Computer Science and Engineering
Studies 3D reconstruction and generative models in computer vision and graphics, with applications to robotics, medical imaging and science.
3D vision & neural rendering
Computational imaging & photography
Generative & foundation models
2026Prospective Dynamic 3D MRI Reconstruction via Latent-Space Motion Tracking from Single MeasurementCVPR
2026SierpinskiCam: Camera-Controlled Video Retaking with Sierpinski Triangle Pattern CuesNeurIPS
18 T1 · 19 papers · 7 members
USMichiganElectrical and Computer Engineering
Lei YingProfessor, EECS – Electrical and Computer Engineering
Studies reinforcement learning and stochastic systems, including safe online learning, cloud and communication networks and graph mining.
Reinforcement learning
Learning theory & optimization
2026Diffusion-Network Alignment: An Efficient Algorithm and Explicit Probability BoundsCOLT
2026Divide and Conquer: Selective Value Learning and Policy Optimization for Offline Safe Reinforcement LearningTrans. Mach. Learn. Res.
17 T1 · 29 papers · Group size not listed
USMichiganComputer Science and Engineering
Michał DerezińskiAssistant Professor, EECS – Computer Science and Engineering
Studies statistical learning theory and scalable optimization, with a focus on randomized numerical linear algebra and dimensionality reduction for machine…
Learning theory & optimization
2026Approaching Optimality for Solving Dense Linear Systems with Low-Rank StructureSODA
2026Debiasing Random Oblique Projections for Subsampled OLS and Fast CUR in High DimensionsNeurIPS
Studies reinforcement learning, including reward design, intrinsic motivation and computational game theory for adaptive agents.
Reinforcement learning
Learning theory & optimization
2026Code World Models for General Game PlayingICLR
2025Generating Creative Chess PuzzlesNeurIPS
16 T1 · 20 papers · 7 members · 18 alumni
USMichiganComputer Science and Engineering
David JurgensAssociate Professor, EECS – Computer Science and Engineering; Associate Professor, School of Information
Studies natural language processing and computational social science, including how generative AI models social interaction and crowdsourced language data.
Language & society
Generative & foundation models
Computational social science
2026Modeling Annotator Disagreement with Demographic-Aware Experts and Synthetic PerspectivesACL
2026Interpreting Style Representations via Style-Eliciting PromptsFindings of ACL
Studies robot learning, motion planning and manipulation, including manipulation of deformable objects.
Manipulation & robot learning
Planning, control & multi-robot systems
Physics-based simulation & animation
2026Diffusing Trajectory Optimization Problems for Recovery During Multi-Finger ManipulationICRA
2026Multimodal Diffusion Forcing for Forceful ManipulationICRA
15 T1 · 25 papers · Group size not listed
USMichiganElectrical and Computer Engineering
Liyue ShenAssistant Professor, EECS – Electrical and Computer Engineering
Studies biomedical AI, including deep learning for medical image reconstruction and analysis and AI for precision health.
Medical imaging & healthcare AI
Medical image analysis
3D vision & neural rendering
2026Antithetic Noise in Diffusion ModelsICLR
2026Beyond Time Series: Spatial Reasoning for Epidemic Forecasting via Multimodal LearningKDD
15 T1 · 25 papers · Group size not listed
USMichiganComputer Science and Engineering
Michael WellmanInterim Associate Dean for Academic Affairs; Lynn A. Conway Collegiate Professor of Computer Science and Engineering; Professor, EECS – Computer Science and Engineering
Studies strategic reasoning in multi-agent systems, including empirical game-theoretic analysis and AI for electronic commerce and financial markets.
Reasoning & neuro-symbolic AI
Reasoning & agents
Planning, control & multi-robot systems
2026Computing Perfect Bayesian Equilibria, with Application to Empirical Game-Theoretic AnalysisAAMAS
2026Conservative Equilibrium Discovery in Offline Game-Theoretic Multiagent Reinforcement LearningAAMAS
15 T1 · 28 papers · Group size not listed · 85 alumni
USMichiganComputer Science and Engineering
Wei HuAssistant Professor, EECS – Computer Science and Engineering
Studies the theory and science of deep learning, including generalization, training dynamics and the behavior of large language models.
Learning theory & optimization
Large language models
2026Robust Sparse Mean Estimation via Incremental LearningTMLR
2026Skill-Aware Data Selection and Fine-Tuning for Data-Efficient Reasoning DistillationACL