AI for Physics
Interatomic potentials and reliable molecular simulation.
Taoyong Cui · 崔涛镛
Molecular and physical systems · world models · scientific agents.
Ph.D. student at CUHK CSE, working with the AI4LS Laboratory and MMLab; visiting Ph.D. researcher at Stanford University.

About
CUHK: AI4LS Laboratory and MMLab. Co-supervised by Prof. Pheng Ann Heng and Prof. Wanli Ouyang.
Stanford: collaborating with Prof. Le Cong.
Background: Master's in Biomedical Engineering, Tsinghua University; Microsoft Research Asia; Shanghai AI Laboratory.
Reviewer: Nature Communications, AISTATS, ICML, ICLR, NeurIPS, AAAI.
Interatomic potentials and reliable molecular simulation.
Dynamics, uncertainty, and generalization.
Planning and tool use for research workflows.
Selected publications
Nature Communications · 2026
Efficient uncertainty quantification for interatomic potentials.
Read paperNature Communications · 2025
Test-time adaptation for out-of-distribution atomic structures.
Read paperNature Machine Intelligence · 2024
Geometry-aware pretraining for interatomic potentials.
News
Nature Communications paper accepted.
Scientific Data paper accepted.
Current Opinion in Structural Biology paper accepted.
Advanced Science paper accepted.
Nature Communications paper accepted.
VLDB paper accepted.
Nature Machine Intelligence paper accepted.
Talks
Contact