Jordan Vincent
Research Scientist And Electrical Engineer at Tekla Research Inc
Alexandria, Virginia, United States
Summary
👤
Senior🎓
Top SchoolJordan Vincent is a research scientist and electrical engineer with 21 years of experience applying scientific computing, machine learning, and real-time systems to defense and aerospace problems. He combines hands-on software development in C/C++, Fortran, CUDA and HPC frameworks with expertise in data fusion, inertial navigation, and image/signal processing to deliver production-grade algorithms and avionics controllers. At Tekla Research he develops real-time acquisition and video processing systems for Naval optical countermeasures, and his prior work includes leadership on radar/EOIR modeling and missile defense engagement simulation. He is a contributor to the QMCPACK quantum Monte Carlo codebase, where he implemented and debugged Diffusion Monte Carlo features with GPU-aware performance considerations. Trained as a physicist (Ph.D., UIUC), he blends deep theoretical grounding with practical engineering—often tackling numerical and parallel-computing challenges that others hand off to specialists.
21 years of coding experience
13 years of employment as a software developer
Ph.D., Physics, Ph.D., Physics at University of Illinois Urbana-ChampaignB.S, Physics, B.S, Physics at The Ohio State University
Github Skills (12)
ec10
cuda10
cpp10
monte-carlo10
cplus10
scientific-computing9
accelerated-computing9
parallel-computing9
high-performance9
cluster-computing9
mpi9
roc8
Programming languages (1)
Github contributions (1)
QMCPACK/qmcpack
Dec 2004 - Sep 2005
Main repository for QMCPACK, an open-source production level many-body ab initio Quantum Monte Carlo code for computing the electronic structure of atoms, molecules, and solids with full performance portable GPU support
Role in this project:
Back-end Developer
Back-end DeveloperContributions:42 commits in 9 months
Contributions summary:Jordan primarily focused on implementing and debugging the Diffusion Monte Carlo (DMC) algorithm within the QMCPACK framework. They made modifications to the DMC particle-by-particle implementation, including bug fixes and the addition of node-crossing handling. The user also implemented improvements such as scaling the drift in the DMC algorithm and made changes to the branching function.
ab-initiogpumonte-carloquantum-monte-carloelectronic-structure
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