Summary
Tiara Hung is a data engineer with a PhD in Astronomy and Astrophysics and over eight years of experience building production-ready pipelines, scientific packages, and web apps using Python, Bash, and SQL. She transformed time-domain astrophysics workflows—applying ML, Gaussian processes, and MCMC—to improve rare transient selection by 20x and to infer physical parameters with quantified uncertainties. Her work spans academia and industry, from leading federally funded observing programs and mentoring students to shipping data products at HeadSpin and now Meta. She has first-authored seven papers and contributed to 30+ peer-reviewed publications with 5,000+ citations, and serves on NASA review panels and journal refereeing committees. Known for pragmatic visualization and interactive tools (Dash, Bokeh, Plotly) to make complex time-series interpretable, she pairs deep statistical rigor with production engineering. Based in San Francisco, she brings a rare combination of observational-domain expertise and scalable data engineering for mission-critical, time-sensitive systems.
8 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD, Astronomy and Astrophysics, Doctor of Philosophy - PhD, Astronomy and Astrophysics at University of Maryland
English, Chinese