Summary
Pengfei Cai is a PhD candidate at MIT with eight years of multidisciplinary experience applying generative models and differentiable simulations to materials discovery, including degradable thermoset plastics under Rafael Gomez-Bombarelli. He blends deep learning (GNNs, generative models) with quantum chemistry, Bayesian optimization, and experimental validation from prior work at NUS and A*STAR, driving projects from virtual screening to lab synthesis. Pengfei has entrepreneurial chops—co-founding TinyJobs and sgTuitions and launching user-facing products and GUIs—plus brief industry experience building large recommendation models at TikTok. Based in Cambridge, MA, he focuses on “AI for science,” translating advanced ML into tangible materials insights and prototypes, and often pairs simulation differentiability with generative modeling to accelerate discovery in ways not obvious from titles alone.
8 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Computational Materials Science and Engineering, Doctor of Philosophy - PhD, Computational Materials Science and Engineering at Massachusetts Institute of Technology
A Levels, Physics, Semiconductor Physics, Chemistry, Mathematics, Geography, A Levels, Physics, Semiconductor Physics, Chemistry, Mathematics, Geography at Dunman High School
Bachelor's Degree, Materials Science and Engineering, Highest Distinction, Bachelor's Degree, Materials Science and Engineering, Highest Distinction at National University of Singapore