Andy Park
Physics Ph.D. Researcher at Carnegie Mellon University
Pittsburgh, Pennsylvania, United States
Summary
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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 (14)
distortion8
binning8
python7
astronomy7
quantum-computing5
galsim5
simulation4
jax4
simulations3
javafx3
gpu2
mobile2
jetpack2
autodiff2
Programming languages (6)
Github contributions (5)
mr-superonion/xlens
Feb 2024 - Apr 2026
Contributions:3 PRs, 24 pushes, 7 branches in 2 years 2 months
andyyPark/dotfiles
May 2023 - Jan 2025
Contributions:27 pushes, 1 branch in 1 year 8 months
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