Summary
Jennifer Li is a research scientist at NCSA who combines a Ph.D. in Astronomy & Astrophysics with a decade of experience applying machine learning and Bayesian inference to astrophysical problems. She has advanced black hole science by developing RNNs and simulation-based inference that sped up parameter estimation by over 1,000×, and has published six first-author papers within a 1000+ citation body of work. Comfortable coding production-grade Python pipelines and automating image reduction, she bridges observational astronomy, time-series modeling, and scalable data analysis on HPC systems. An active mentor and outreach advocate, she designs hands-on curricula for high-school students and promotes equity in STEM, reflecting a rare mix of technical depth and community commitment. Based in Urbana, IL, she also brings practical unix/git fluency and a playful willingness to tackle JavaScript when needed.
10 years of coding experience
6 years of employment as a software developer
Bachelor of Science (BS), Atmospheric Sciences and Meteorology, Bachelor of Science (BS), Atmospheric Sciences and Meteorology at National Taiwan University
University of Illinois Urbana-Champaign
English, Chinese