Summary
Mingda Li is a research scientist at Meta with a decade of experience bridging device physics and machine learning to build practical simulation and modeling tools. Trained with a PhD in Electrical and Computer Engineering from Cornell, he developed next-generation energy-efficient transistor models and the custom simulators that enabled several publications, teaching himself algorithms and software engineering along the way. He now focuses on integrating deep learning with Bayesian reasoning for scientific data modeling, translating research insights into production-ready systems. Beyond devices, he launched an AWS-backed web app to detect passive-voice grammar errors in Chinese, reflecting a knack for applying technical methods to diverse, real-world problems. Colleagues describe him as someone who pairs rigorous experimental validation with creative algorithm design to drive long-term societal benefit.
10 years of coding experience
6 years of employment as a software developer
Bachelor of Science (BS), Microelectronics, Bachelor of Science (BS), Microelectronics at Fudan University
Doctor of Philosophy (PhD), Major in Electrical and Computer Engineering; Minor in Computer Science, Doctor of Philosophy (PhD), Major in Electrical and Computer Engineering; Minor in Computer Science at Cornell University
Master's degree, Electrical and Electronics Engineering, Master's degree, Electrical and Electronics Engineering at University of Notre Dame
English, Chinese