Summary
Enzhi Li is an Applied Scientist II in San Diego with 11 years of experience bridging machine learning, graph algorithms, and numerical simulation for high-stakes applications such as financial risk control. He holds a PhD in computational physics and a BEng in engineering mechanics, bringing deep applied-math and numerical-analysis expertise to production ML systems. Proficient in Python, Scala, C++, Fortran and SQL, he has a track record of maintaining legacy scientific codebases while shipping modern ML solutions at Amazon and prior machine learning roles. His background in strongly correlated electron research and topological insulator theory gives him a rare theoretical perspective that informs robust modeling and simulation choices in industry. Active on GitHub, he blends research rigor with pragmatic engineering to tackle complex, data-driven problems end to end.
11 years of coding experience
10 years of employment as a software developer
Bachelor's degree, Engineering Mechanics, Bachelor's degree, Engineering Mechanics at Nanjing University of Aeronautics and Astronautics
Doctor of Philosophy - PhD, Physics, Doctor of Philosophy - PhD, Physics at Louisiana State University