John F. Wu
Baltimore, Maryland, United States
Summary
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SeniorJohn Wu is an Associate Astronomer at the Space Telescope Science Institute, blending physics with AI/ML to advance astronomical discovery. As the Applied AI Scientist in the STScI Data Science Mission Office, he leads efforts to evaluate LLMs for research and literature review and ships forward‑looking, interpretable AI tools for astronomy. He has steered technical leadership for the Roman Space Telescope's Data Monitoring Tool and contributed as a Roman instrument scientist, bridging research with operational tooling. He earned a PhD in Astrophysics from Rutgers University–New Brunswick and a BS in Physics/Astrophysics from Carnegie Mellon University, with postdoctoral and research roles at Johns Hopkins and STScI. Based in Baltimore, his work spans identifying the largest-ever sample of faint nearby galaxies with deep learning and building calibration/imaging pipelines for large radio surveys like MeerKAT LADUMA, reflecting a rare mix of scientific impact and software engineering.
9 years of coding experience
Github Skills (113)
diffusion-probabilistic10
bayesian10
contrastive-learning10
fractions9
denoising9
galaxy9
astronomy9
mass9
notebooks9
generative-model9
predict9
nancy9
stellar9
telescope8
self-supervised-learning8
Programming languages (8)
Github contributions (5)
rutgers-physics-ml/astro-hack-2018-spring
Jan 2018 - Apr 2018
Contributions:39 commits, 19 PRs, 9 pushes in 2 months
spsrasastro
jwuphysics/xSAGA
Dec 2020 - Dec 2021
Extending the SAGA survey to the wide-field regime using deep learning
Contributions:3 releases, 161 commits, 2 PRs in 11 months
deep-learningsagasaga-surveyfieldsurvey
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