I am Weihan Li (黎维瀚), a PhD student at Georgia Tech CSE, advised by Prof. Anqi Wu. Previously, I was an undergraduate at Zhejiang University, working with Prof. Gang Pan. My CV is available here.
Research
I work on robot learning for dexterous manipulation: teaching multi-fingered robot hands to perform bimanual manipulation skills learned from human demonstrations, in simulation and on real hardware.
Before moving to robotics, I worked on modeling communication across multiple brain regions and on analyzing animal behavior from pose and video.
Current Dexterous Manipulation Bimanual Robot Skills Learning from Human Demonstrations Sim-to-Real Transfer
Previously Multi-Region Brain Communication Animal Behavior Analysis
Publications
See also my Google Scholar profile.
NeurIPS 2026
Learning When Visual Context Matters for Mouse Behavior Analysis
Weihan Li, Jingyang Ke, Qinheng Pu, Yule Wang, Chengrui Li, Anqi Wu
NeurIPS 2026Spotlight
MICE: Multi-animal Interaction Context Encoder — A Hierarchical Foundation Model for Mouse Behavior
Yen-Shuo Su, Weihan Li, Anqi Wu
NeurIPS 2026
QDMouse4M: A Multi-View 3D Mouse Spontaneous Behavior Dataset with Quantum-Dot Markers
Jingyang Ke, Amartya Pradhan, Xueling Zhang, Weihan Li, Anqi Wu, Jeffrey E. Markowitz
Evaluations and Datasets Track
Preprint
BehaviorVLM: Unified Finetuning-Free Behavioral Understanding with Vision-Language Reasoning
Jingyang Ke*, Weihan Li*, Amartya Pradhan, Jeffrey Markowitz, Anqi Wu
*Equal contribution
ICML 2026Spotlight
A Factorized Low-Rank RNN Framework for Uncovering Independent Neural Latent Dynamics and Connectivity
Chengrui Li, Yunmiao Wang, Yule Wang, Weihan Li, Dieter Jaeger, Anqi Wu
ICLR 2026
Uncovering Semantic Selectivity of Latent Groups in Higher Visual Cortex with Mutual Information-Guided Diffusion
Yule Wang, Joseph Yu, Chengrui Li, Weihan Li, Anqi Wu
ICML 2025Oral
Learning Time-Varying Multi-Region Brain Communications via Scalable Markovian Gaussian Processes
Weihan Li, Yule Wang, Chengrui Li, Anqi Wu
NeurIPS 2024
Exploring Behavior-Relevant and Disentangled Neural Dynamics with Generative Diffusion Models
Yule Wang, Chengrui Li, Weihan Li, Anqi Wu
ICML 2024
Multi-Region Markovian Gaussian Process: An Efficient Method to Discover Directional Communications Across Multiple Brain Regions
Weihan Li, Chengrui Li, Yule Wang, Anqi Wu
ICML 2024
A Differentiable Partially Observable Generalized Linear Model with Forward-Backward Message Passing
Chengrui Li, Weihan Li, Yule Wang, Anqi Wu
ICLR 2024Spotlight
Forward χ2 Divergence Based Variational Importance Sampling
Chengrui Li, Yule Wang, Weihan Li, Anqi Wu
NeurIPS 2022
Online Neural Sequence Detection with Hierarchical Dirichlet Point Process
Weihan Li, Yu Qi, Gang Pan
EMBC 2021
Efficient Point-Process Modeling of Spiking Neurons for Neuroprosthesis
Weihan Li*, Cunle Qian*, Yu Qi, Yiwen Wang, Yueming Wang, Gang Pan
*Equal contribution
Service
Reviewer: NeurIPS, ICML, ICLR
