Ravi Patel
Scientist at Sandia National Laboratories
Albuquerque, New Mexico, United States
Summary
👤
Senior🎓
Top SchoolRavi Patel is a scientist at Sandia National Laboratories with a decade of experience advancing scientific machine learning by blending ML with traditional numerical methods to produce physically realizable, numerically stable models. He developed MOR-Physics in 2018, one of the first operator learning methods, and has led multiple LDRD projects to translate operator learning into practical tools for national-lab scale problems. His background spans PhD-level computational mechanics and hands-on implementation—optimizing Fortran/MPI multiphase solvers, applying neural operator regression to turbulence closures, and conducting experimental microfluidics work—giving him rare cross-disciplinary fluency. Based in Albuquerque, he combines rigorous theory with production-oriented code development and a track record of bringing novel ML-enabled closure models from concept to large-scale simulation.
10 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy - PhD, Mechanical Engineering, Doctor of Philosophy - PhD, Mechanical Engineering at Cornell UniversityBachelor's degree, Mechanical Engineering, Bachelor's degree, Mechanical Engineering at Rutgers, The State University of New Jersey-New BrunswickMaster's degree, Mechanical Engineering, Master's degree, Mechanical Engineering at Rutgers University
Github Skills (10)
water4
floyd-warshall4
matrix4
python3
simulation3
paths3
simulator3
algorithm1
pathfinding1
snl-applications1
Programming languages (4)
Github contributions (5)
rgp62/MOR-Physics
Aug 2020 - Oct 2021
Contributions:7 commits in 1 year 2 months
rgp62/water
Oct 2015 - Oct 2015
Contributions:5 pushes, 1 branch in 9 days
simulatorwatersimulationshallow
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