Summary
Oliver Elbert is a computer scientist and computational physicist who builds high-performance scientific software to advance weather, climate, and astrophysics modeling. With a PhD in physics and over a decade of production coding in Python, C/C++, MATLAB, and JavaScript, he specializes in porting legacy Fortran models into Python-embedded domain-specific languages that compile to optimized C++/CUDA for leadership-class supercomputers. He has run and benchmarked codes on national HPC systems since 2012 and helped bring NOAA’s FV3GFS model to 1-km resolution through DSL work at Vulcan, AI2, and NOAA. Comfortable at the intersection of domain science and tooling, he combines numerical algorithm development with workflow and infrastructure design to make complex models accessible to scientists. An avid data explorer, he applies Bayesian methods, GANs, and machine learning to create interpretable models—and his background in computational astrophysics gives him a track record of producing higher-resolution simulation datasets than previous studies.
9 years of coding experience
5 years of employment as a software developer
Bachelor of Science (B.S.), Astrophysics, Bachelor of Science (B.S.), Astrophysics at Haverford College
University of California, Irvine