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Resume (English only)
Academic Achievements
Invited as Area Chair for ICLR 2026 (August 2025)
Ph.D. student Jingxiang Qu awarded the IACS Young Writer’s Award (May 2025)
Released multiple preprints in 2025 on LLM-based multi-agent drug discovery and advanced diffusion models for 3D molecular generation
Led team to win 1st place in MICCAI CREMI Cleft Detection Open Challenge
Member of the #3 team in the Open Catalyst Challenge
Contributor to the popular open-source library DIG: Dive Into Graphs
Background
Assistant Professor of Data Science at Stony Brook University, jointly appointed in the Department of Applied Mathematics & Statistics and the Department of Computer Science
Affiliated with the AI Innovation Institute and the Institute for Advanced Computational Science
Research interests broadly span machine learning, deep learning, and data mining, with specific focus on geometric deep learning, AI for Science (AI4Science), scientific machine learning (SciML), and LLMs for Science
Aims to develop novel AI methods to address critical problems in quantum chemistry, physics, PDEs, climate science, materials science, and biochemistry
Active in open challenges and open-source communities: leads the champion team in the MICCAI CREMI Cleft Detection Challenge, member of the #3 team in the Open Catalyst Challenge, and contributor to the open-source library DIG: Dive Into Graphs