HTTP/2 301 server: GitHub.com content-type: text/html location: https://chenningyu.com/ x-github-request-id: 6D7B:292AC1:9D069A:B05EBD:695389DB accept-ranges: bytes age: 0 date: Tue, 30 Dec 2025 08:14:19 GMT via: 1.1 varnish x-served-by: cache-bom-vanm7210020-BOM x-cache: MISS x-cache-hits: 0 x-timer: S1767082459.455425,VS0,VE196 vary: Accept-Encoding x-fastly-request-id: d591f26d98111098d05a4773ade99d34a73dd5f8 content-length: 162 HTTP/2 200 server: GitHub.com content-type: text/html; charset=utf-8 last-modified: Mon, 02 Jun 2025 23:27:54 GMT access-control-allow-origin: * etag: W/"683e337a-4368" expires: Tue, 30 Dec 2025 08:24:20 GMT cache-control: max-age=600 content-encoding: gzip x-proxy-cache: MISS x-github-request-id: A996:2685F2:9BE7D6:AF3FF9:695389DB accept-ranges: bytes age: 0 date: Tue, 30 Dec 2025 08:14:20 GMT via: 1.1 varnish x-served-by: cache-bom-vanm7210093-BOM x-cache: MISS x-cache-hits: 0 x-timer: S1767082460.916494,VS0,VE201 vary: Accept-Encoding x-fastly-request-id: 304865c6e5f6cbebf99483d1f0fe42dc8ba0dafc content-length: 3452

Chenning Yu I am a final year Ph.D. candidate at UCSD Computer Science & Engineering Department. I am very fortunate to have Sicun Gao as my advisor. We are currently working on compositional methods for generative models and robotics. Helping you makes me happy! I am always open to discussion and collaboration. Let me know how I can help you through this Google Form. Email  /  CV  /  Google Scholar  /  Github Compositional Value-based Methods for Planning and Generative Modeling Chenning Yu PhD Thesis, 2025 paper | slides | recording Improving Compositional Generation with Diffusion Models Using Lift Scores Chenning Yu and Sicun Gao ICML, 2025 paper | code | blog We propose a training-free compositional criterion for rejection / resampling with diffusion models. Efficient Motion Planning for Manipulators with Control Barrier Function-Inspired Neural Controller Mingxin Yu, Chenning Yu, Mahdi Naddaf, Devesh Upadhyay, Sicun Gao, and Chuchu Fan ICRA, 2024 paper | code | website Iterative Reachability Estimation for Safe Reinforcement Learning Milan Ganai, Zheng Gong, Chenning Yu, Sylvia Herbert, and Sicun Gao NeurIPS, 2023 paper | code | website Sequential Neural Barriers for Scalable Dynamic Obstacle Avoidance Hongzhan Yu, Chiaki Hirayama, Chenning Yu, Sylvia Herbert, and Sicun Gao IROS, 2023 / Best Robocup Paper Award paper | website Accelerating Multi-Agent Planning Using Graph Transformers with Bounded Suboptimality Chenning Yu*, Qingbiao Li*, Sicun Gao, and Amanda Prorok ICRA, 2023 paper | code | website Learning-based Motion Planning in Dynamic Environments Using GNNs and Temporal Encoding Ruipeng Zhang, Chenning Yu, Jingkai Chen, Chuchu Fan, and Sicun Gao NeurIPS, 2022 paper | code | website Learning Control Admissibility Models with Graph Neural Networks for Multi-Agent Navigation Chenning Yu, Hongzhan Yu, and Sicun Gao CoRL, 2022 paper | code | website Reducing Collision Checking for Sampling-Based Motion Planning Using Graph Neural Networks Chenning Yu and Sicun Gao NeurIPS, 2021 paper | code | website Original code of this website