James Koch
Data Scientist
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolJames Koch is a data scientist and aerospace-trained researcher with nine years of experience applying high-performance computing and numerical methods to high-enthalpy fluid flows, combustion, and detonation. He holds a PhD in Aerospace Engineering and dual MS degrees from the University of Washington and has moved between academia, national labs, and industry—most recently joining Blue Origin after five years at Pacific Northwest National Laboratory. James builds open-source engineering tools and scalable scientific computing workflows to turn nonlinear analysis and simulation research into reproducible, production-ready capabilities. His background includes hands-on propulsion and hypersonics experience from GE Aviation, JPL, and GoHypersonic, and he brings a rare mix of combustion physics intuition and data-driven modeling skills. Outside work he pursues amateur astronomy, motorcycle riding, and photography, often applying computational visualization techniques to his hobbies.
9 years of coding experience
13 years of employment as a software developer
Doctor of Philosophy (PhD), Aerospace, Aeronautical and Astronautical Engineering, Doctor of Philosophy (PhD), Aerospace, Aeronautical and Astronautical Engineering at University of WashingtonStephen T. Badin High SchoolBachelor of Science (BS), Mechanical Engineering, Bachelor of Science (BS), Mechanical Engineering at The University of Alabama
Github Skills (30)
constrained-optimization10
dynamical-systems10
predictive10
nonlinear-dynamics10
control-systems10
nonlinear-optimization10
system-identification10
model-predictive-control9
differentiable-programming8
parametric8
optimization8
deep-learning8
physics8
pytorch8
rubygems7
Programming languages (4)
Github contributions (5)
j-koch/j-koch.github.com
Dec 2018 - Dec 2018
Contributions:15 pushes, 1 branch in 15 days
j-koch/neuromancer
Aug 2023 - Aug 2023
Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.
Contributions:5 pushes, 1 branch in 6 days
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