Gary Uppal
Data Scientist I (Domain Expert Lead)
Boston, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolGary Uppal is a computational scientist and data scientist with nine years of experience translating physics-first modeling into robust ML and scientific data systems. Currently at Amazon, he leads domain-level validation of complex physics datasets and builds internal tooling to streamline expert review and improve pipeline reliability. Previously he developed MCSPACE at Brigham and Women’s Hospital, applying Bayesian dynamical and generative models to spatial-temporal microbiome data and shipping reproducible pipelines across HPC and cloud. He combines deep domain expertise in multi-physics modeling and pharmacokinetic simulation with hands-on software engineering (Python, R, Bash, VS Code extensions) to deliver interpretable solutions for high-dimensional, sparse, and noisy data. Based in Boston with a PhD in Physics, he excels at converting intricate scientific questions into scalable, auditable computational frameworks that accelerate interdisciplinary research.
9 years of coding experience
1 year of employment as a software developer
Bachelor of Science Physics, Bachelor of Science Physics at University of California, DavisDoctor of Philosophy (Ph.D.) Physics, Doctor of Philosophy (Ph.D.) Physics at University of Notre DameMaster's Degree Physics, Master's Degree Physics at California State University, Fullerton
Punjabi, Hindi
Github Skills (3)
simulations5
simulation4
active-matter4
Programming languages (3)
Github contributions (5)
garyuppal/TechniSound
Jul 2019 - Nov 2024
A computer music system to ``compose'' tunes offline; hopefully with some real-time functionality and machine learning routines
Contributions:2 PRs, 15 pushes, 3 branches in 5 years 5 months
synthtunescomputer-musicmachine-learningcompose
gerberlab/MCSPACE
Mar 2024 - Dec 2024
Generative probabilistic model for analyzing mapseq data and learning spatial embeddings
Contributions:3 PRs, 102 pushes, 6 branches in 9 months
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