Yuan (Cyrus) Chiang

Welcome to my cyber nook! I am Yuan Chiang (江元, pronounced as ‘You-an John’). I also go by my coffee name 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 scales to drive our understanding and innovations in AI for physical sciences.

I work on the development and benchmark 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.

Previously I earned my BS in Civil Engineering and MS in Structural Engineering at National Taiwan University, under the supervision of Prof. Shu-Wei Chang. I was a structural engineering intern at T.Y. LIN in 2018 and was a full-stack intern at Ucarer in 2021.

Yes! I had an unorthodox transition from “civil” to “materials science” (they are at the opposite ends of spectrum in terms of the length scale if you will) after years of working with Prof. Chang in civil engineering department because he is too nice and I was too numb not seeing what I really want to pursue, thanks to the spoon-feeding education system in Taiwan and my self-deception from the uninformed, vague childhood interest in civil structure 🙃. Fortunately, I had Prof. Chang’s unwavering guidance that enlightened me to use my gift and interest for fundamental science and technology.