Summary
Zhenpeng Yao is an Associate Professor at Shanghai Jiao Tong University and a computational materials scientist with 11 years’ experience translating first-principles DFT, high-throughput screening, autonomous lab workflows, and deep learning into next-generation battery materials. His work spans anode/cathode design, solid electrolytes, and MOFs, and he has led methodological innovations such as the NEPS approach for conversion reactions and design of anionic-redox-active Fe cathodes during appointments at the U.S. DOE and Harvard. Trained at Northwestern (PhD) and top-ranked programs in China, Zhenpeng blends rigorous theory with practical R&D—earlier at General Motors—bridging fundamental prediction and application for Li-ion and solid-state systems. An enthusiast for AI and robotics, he actively integrates machine learning and automation to accelerate materials discovery, reflected in his research portal compumatsresearch.com.
11 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Material Science And Engineering, 3.7/4.0, Doctor of Philosophy (Ph.D.), Material Science And Engineering, 3.7/4.0 at Northwestern University
Bachelor of Science (B.S.), 3.5/4.0, Rank: Top 5%, Bachelor of Science (B.S.), 3.5/4.0, Rank: Top 5% at Huazhong University of Science and Technology
Master of Science (M.S.), 3.7/4.0, Rank: 1/115, Master of Science (M.S.), 3.7/4.0, Rank: 1/115 at Shanghai Jiao Tong University
Chinese, English