Yuan (Cyrus) Chiang

Welcome. I am Yuan Chiang (江元, pronounced as ‘You-an John’). I also go by Cyrus. I am a PhD candidate in Materials Science and Engineering at UC Berkeley and Lawrence Berkeley National Laboratory, under the guidance of Prof. Mark Asta. I leverage density functional theory calculations and develop machine learning models and frameworks at scale to drive our understanding and innovations in AI for physical sciences.

I work on the development and benchmarking of foundation machine learning interatomic potential (MLIP) and use them as a probe to understand and design ferroelectric materials and metal-salt interface in Gen IV molten salt fission reactors (MSRs).

I trained the MACE-MP-0 and built the MLIP Arena. I have been fortunate to collaborate with Prof. Gábor Csányi, Prof. Aditi Krishnapriyan, and many others through these works.

My research interests more broadly lie in computational materials physics and chemistry at the atomic and molecular levels, with an emphasis on the theory and application of ab-initio calculations, molecular dynamics, and AI/ML to tackle challenges across energy, materials, pharmaceutics, devices, and computing.