Andy Park
PhD Candidate
Pittsburgh, Pennsylvania, United States
Summary
👤
Senior🎓
Top SchoolAndy Park is a Physics PhD candidate at Carnegie Mellon University who applies machine learning to problems in computational and observational cosmology, with nine years of research and engineering experience. He has built and optimized CNNs and ResNets for galaxy tomography and image modeling using PyTorch and JAX, and has scaled simulations and GPU workflows for DESI and LSST projects. His background in physics, mathematics, and computer science enables him to bridge theoretical modeling (e.g., Schrödinger equation simulations for dark matter) with practical data-driven pipelines for large survey datasets. Active in DESI and the LSST Dark Energy Science Collaboration, he combines hands-on coding, cluster workflows, and mentor experience to deliver reproducible scientific software. Notably, he has experience generating large synthetic image datasets and optimizing Fisher matrix computations for GPU execution—skills that accelerate analysis at survey scale.
9 years of coding experience
Doctor of Philosophy - PhD, Physics, Doctor of Philosophy - PhD, Physics at Carnegie Mellon UniversityUniversity of California, Irvine
Korean, English, Spanish
Github Skills (26)
distortion9
binning8
cosmology8
automatic-differentiation6
galaxy6
uci6
machine-learning6
python6
astronomy6
simulation4
simulations4
pipeline3
javafx3
java3
acceleration2
Programming languages (5)
Github contributions (5)
andyyPark/dotfiles
May 2023 - Jan 2025
Contributions:27 pushes, 1 branch in 1 year 8 months
sukhdeep2/skylens_lite
Jun 2022 - May 2023
Contributions:6 PRs, 21 pushes in 11 months
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