My research focuses on AI for Science — taking hypergraphs as a new tool for scientific discovery and exploring high-order-correlation-driven computing paradigms, with applications in real-world scenarios such as geometric correlation modeling, protein structure modeling, and tumor microenvironment analysis.
I lead projects including an NSFC General Program, an NSFC Young Student Basic Research Program (PhD Candidate), and a subproject of a national major S&T program. I have published 40+ papers in Nature Communications, IEEE TPAMI (14 papers), ICLR, etc., with 7500+ Google Scholar citations; my most cited first-author paper has been cited 3000+ times. I led the development of DeepHypergraph, the first hypergraph computation toolbox, and Hyper-Extract, a hypergraph knowledge reasoning toolkit that ranked 2nd on GitHub Trending.
Feel free to reach out if you are interested in these directions or would like to collaborate. I am currently on the job market for faculty positions, mainly in Beijing — any information or referrals would be greatly appreciated.