Chuntian Cao

Brookhaven National Laboratory

Computational Science
Bldg. 725, Room 199
P.O. Box 5000
Upton, NY 11973-5000

ccao@bnl.gov

Research | Education | Appointments | Highlights

Research Activities

Machine learning interatomic potentials (MLIPs)  to model complex material systems: 
https://journals.aps.org/prxenergy/abstract/10.1103/PRXEnergy.4.023004
https://www.bnl.gov/newsroom/news.php?a=122451
Related work: https://www.science.org/doi/full/10.1126/sciadv.ady6869

Simulate X-ray absorption spectroscopy (XAS) using first-principles methods: 
https://www.cell.com/cell-reports-physical-science/fulltext/S2666-3864(24)00145-0
https://pubs.acs.org/doi/full/10.1021/acsami.4c14388

Graph neural networks (GNNs) for XAS prediction and interpretation: 
https://pubs.acs.org/jpcbfk/article/130/19/5084/5096138/Deciphering-the-Solvation-Structure-of-Aqueous 

Uncertainty aware ML for SAXS analysis: 
https://pubs.acs.org/psabes/article/1/4/252/5226462/Uncertainty-Aware-Machine-Learning-for-Small-Angle

Lithography photomask design using automatic differentiation: 
https://arxiv.org/abs/2608.05488

Education

Ph.D., Materials Science and Engineering, Stanford Univerisity (2018) 
B.S., Applied Physics, University of Science and Technology of China (2012) 
M.S., Online Master of Science in Computer Science (OMSCS), Georgia Institute of Technology (2025)

Professional Appointments

05/2024 - Present, Assistant Computational Scientist, Brookhaven National Laboratory
05/2021 – 05/2024, Research Associate in Computational Science Initiative, Brookhaven National Laboratory
01/2021 – 05/2021, PostDoc in Chemical and Biological Engineering, University of Colorado Boulder 
05/2018 – 12/2020, PostDoc in Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory

Research Highlights

Develop and apply neural network potentials to model complex material systems with ab initio accuracy, enabling large-scale molecular dynamics (MD) simulations. This approach provides atomic-level insights into structural and transport properties across a wide range of materials. 
https://www.bnl.gov/newsroom/news.php?a=122451