Mark Yoder
Research Computing Consultant at Stanford Research Computing and Stanford Doerr School of Sustainability
United States
Summary
👤
Senior🎓
Top SchoolMark Yoder is a research computing consultant and physicist with 11 years of experience applying big-data, numerical simulation, and machine-learning methods to geophysics, natural hazards, and scientific computing workflows. He manages research compute infrastructure at Stanford’s Doerr School of Sustainability while advising teams on pragmatic, production-ready approaches that blend physics-based models with modern data science. His background includes leading development of an MPI-enabled earthquake simulator (Virtual Quake) and production ML systems for real-time radiation dosimetry, reflecting a rare mix of high-performance C++/MPI and Python data-science practice. Comfortable turning complex physical models into validated, scalable code, he also brings experience in grant writing and teaching, making him effective at translating research questions into reproducible computational solutions. An often-overlooked strength is his history of integrating scientific constraints into ML pipelines, yielding interpretable, physics-informed predictions rather than black-box models.
11 years of coding experience
14 years of employment as a software developer
BA, Physics and the liberal arts, BA, Physics and the liberal arts at Wesleyan UniversityPhD, Physics, PhD, Physics at University of California, Davis Department of Physics
French
Github Skills (95)
python10
data-manipulation10
windows10
scientific-computing10
dataframes10
pandas10
linux10
data-science10
macos10
build-tools10
package-manager10
data-analysis10
hpc10
manipulation10
data-structures10
Programming languages (8)
Github contributions (5)
jeffersonscientific/AM4_runtime
Nov 2020 - Oct 2022
Runtime scripts and analysis codes for NOAA-GFDL AM4 .
Contributions:1 review, 1 PR, 40 pushes in 1 year 11 months
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markyoder/misc_and_dev
Jun 2015 - Aug 2019
Contributions:13 pushes, 1 branch in 4 years 2 months
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