Marshall Jiang
Postdoctoral Researcher at Sandia National Laboratories
Albuquerque, New Mexico, United States
Summary
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Senior🎓
Top SchoolMarshall Jiang is a postdoctoral researcher blending 12 years of experience in machine learning and applied mathematics, currently advancing computational science at Sandia National Laboratories. His work builds on a PhD in Applied Mathematics from Brown University and a strong quantitative foundation from Cornell, with focused research on fractional PDEs and probabilistic computation. He has a track record of building novel numerical methods and sampling algorithms—dating back to an MCMC implementation during an early scientific computing internship—and applying them to high-performance, real-world problems. Marshall bridges theory and practice, comfortable proving convergence results one day and profiling code on HPC clusters the next. Based in Albuquerque, he brings a collaborative, cross-disciplinary approach shaped by academic teaching and national-lab environments. An uncommon strength is his breadth across pure math, computational statistics, and software engineering, enabling rapid translation of mathematical insight into production-ready algorithms.
12 years of coding experience
6 years of employment as a software developer
Dual enrollment, N/A, Dual enrollment, N/A at Florida State UniversityDoctor of Philosophy - PhD, Applied Mathematics, Doctor of Philosophy - PhD, Applied Mathematics at Brown UniversityBachelor of Science (BS), Mathematics, Economics, Computer Science, Bachelor of Science (BS), Mathematics, Economics, Computer Science at Cornell UniversityStudy Abroad, Mathematics, Study Abroad, Mathematics at Budapest Semesters in Mathematics
English, Chinese
Github Skills (4)
git9
github8
pytorch4
neural-network3
Programming languages (3)
Github contributions (5)
runiteking1/larsons_solution
Jul 2014 - Jan 2015
Contributions:12 commits, 1 push in 5 months
runiteking1/aisec-project
Sep 2025 - Jun 2026
Contributions:8 pushes, 2 branches in 8 months
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