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 (72)
probabilistic-programming10
python10
density-estimation10
bayesian-inference10
variational-inference10
bayesian10
probabilistic-models10
pytorch10
machine-learning10
probabilistic10
probabilistic-graphical-models10
gpu9
deep-learning9
autodiff9
searching9
Programming languages (4)
Github contributions (5)
adam-coogan/diffbank
Feb 2022 - Dec 2022
Contributions:13 commits, 24 pushes in 10 months
adam-coogan/hazma_applications
Nov 2020 - Dec 2022
Contributions:16 commits, 13 pushes, 1 branch in 2 years 1 month
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