Jake Stevens-haas
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolJake Stevens-haas is an applied mathematics PhD and engineer who builds production-ready ML libraries and research software, best known as lead developer of PySINDY, an open-source toolbox with 1,700+ GitHub stars for discovering sparse nonlinear dynamical systems. With eight years of experience across academia, industry, and the US Navy, he combines rigorous stochastic calculus, likelihood methods, and convex optimization with practical software engineering to move models from research to deployed libraries. He has led teams and projects at Booz Allen creating ML products and internal libraries, contributed advanced optimizers and axis-aware data structures to PySINDY, and applied his research to seaglider navigation problems. His background in naval operations adds uncommon systems-level discipline and real-world decision-making to his technical work, enabling reliable delivery under high-stakes constraints.
8 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Applied Mathematics, Doctor of Philosophy - PhD, Applied Mathematics at University of WashingtonBachelor of Science - BS, Econometrics and Quantitative Economics, 3.92, Bachelor of Science - BS, Econometrics and Quantitative Economics, 3.92 at United States Naval Academy
French, Arabic
Stackoverflow
1,366reputation
425kreached
29answers
9questions
database
top-5%
csv
top-5%
sqlite
top-5%
Github Skills (22)
python10
optimizers10
machine-learning10
optimisation10
optimization10
algorithm9
scikit9
sqlite9
scikit-learn9
database9
csv9
data-structures8
data-structure8
algorithms8
pip6
Programming languages (11)
Github contributions (5)
dynamicslab/pysindy
May 2022 - Oct 2022
A package for the sparse identification of nonlinear dynamical systems from data
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:2 releases, 132 reviews, 142 commits in 4 months
Contributions summary:Jake contributed to the `pysindy` repository by implementing and improving core functionality related to sparse identification of dynamical systems. Their work included adding features such as the handling of linearly dependent columns in the FROLS optimizer, adapting to multiple trajectories, and introducing the `AxesArray` class for managing axis semantics. The user also refactored code for better organization and performance, including moving differentiation calculations and control variable handling into a more unified system.
nonlinear-dynamicsnonlinearstructural-engineeringsparse-regressiondynamical-systems
Jacob-Stevens-Haas/seattle
Sep 2019 - Aug 2023
A python distribution as a self-guided tour.
Contributions:1 PR, 5 pushes, 1 branch in 4 years
guided-tourpythondistributionguided
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