Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
Creator of Dense Basis, a widely-used package for galaxy spectral analysis
Developed GP-SFH, a framework for modeling stochastic star formation histories
Co-founder of UniverseTBD, developing ML-based tools for astrophysical research
Launched Pathfinder, a free LLM-assisted tool for exploring astronomical literature
Publications available via Google Scholar and ADS; code on GitHub
Background
Currently a NASA Hubble Fellow at Columbia University
Works at the intersection of theoretical modeling, observations, and astrostatistical method development to understand the physical processes shaping the universe
Primarily a computational astrophysicist studying galaxy growth and evolution across cosmic time
Focuses on decoding galaxy life stories: star formation, environmental interactions, and evolution over billions of years
Enjoys applying astrostatistics and machine learning to noisy, heterogeneous datasets
Advocates for interpretable or physically-motivated ML methods and AI for model building
Recently exploring applications of generative AI in astronomy at both research and meta-literature levels