Research
My research focuses on AI-driven materials discovery, with a particular emphasis on inverse design using generative models. I am also interested in MLIPs, agentic AI, and computational simulations including DFT and MD.
Current Featured Projects
MOFFUSION (Nat. Commun., 2025)
Inverse Design Diffusion Models Generative AI
F-COF for K+ Ion Battery (Adv. Energy Mater., 2023)
Density Functional Theory Electronic Structure
ZeoDIFF (J. Mater. Chem. A, 2024)
Inverse Design Diffusion Models Generative AI
Genetic Algorithm for MOFs (Chem. Mater., 2023)
Inverse Design Genetic Algorithm GCMC Simulation