Adam Coogan
Machine Learning Engineer at Zoox
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolAdam Coogan is a machine learning engineer with a decade of experience translating rigorous academic research in astrophysics into production-ready ML and software solutions for autonomous systems. He has moved from postdoctoral roles at Mila/Ciela and GRAPPA—where he built PyTorch simulators, diffusion-based astrophysics analyses, and scalable Gaussian process tools—to leading R&D and ML work for automotive autonomy at Volkswagen and Zoox. Adam excels at turning vague ideas into impactful proofs-of-concept and shipping models that improve planning and prediction, backed by a track record of accelerating scientific workflows by 100× and producing widely-adopted inference-checking methods. Comfortable communicating to both technical and nontechnical audiences, he combines deep quantitative skills with hands-on engineering across data, math, and ML to tackle high-impact problems.
10 years of coding experience
6 years of employment as a software developer
Bachelor of Science - BS, Theoretical and Mathematical Physics, Bachelor of Science - BS, Theoretical and Mathematical Physics at Brown UniversityUniversity of California Santa Cruz
Github Skills (48)
pytorch10
variational-inference10
probabilistic-programming10
python10
machine-learning10
bayesian10
deep-learning10
physics10
bayesian-inference10
gradient9
astrophysics9
control-flow9
gpu9
jax9
jit8
Programming languages (4)
Github contributions (5)
adam-coogan/diffbank
Feb 2022 - Dec 2022
Contributions:13 commits, 24 pushes in 10 months
adam-coogan/jaxinterp2d
Mar 2021 - May 2022
Bilinear interpolation on grids with jax
Contributions:6 commits, 3 PRs, 4 pushes in 1 year 1 month
bilinear-interpolationjax
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