Thomas Lipp
Principal Guidance Navigation And Control (GNC) Engineer
California, United States
Summary
👤
Senior🎓
Top SchoolThomas Lipp is a Principal Guidance, Navigation, and Control engineer with 12 years of experience applying high-speed and convex-optimization techniques to real-time embedded trajectory planning and control. At SpaceX he led GNC work from flight-proven Falcon 9 human-rating and landing burns to designing Starship booster catch systems and high-fidelity simulation tools that enable rapid reusability. He combines deep academic training—a Stanford PhD focused on interior-point methods and MPC—with hands-on production engineering, shipping guidance software and algorithms that run on flight hardware. An active contributor to numerical optimization tooling, he improved the Python interface of the widely used ECOS conic solver to make solver tolerances and parameters more ergonomic for users. Based in California, he’s known for translating advanced optimization research into robust, safety-critical aerospace systems.
12 years of coding experience
14 years of employment as a software developer
Bachelor's of Science in Engineering Mechanical and Aerospace Engineering, Bachelor's of Science in Engineering Mechanical and Aerospace Engineering at Princeton UniversityDoctor of Philosophy (Ph.D.) Mechanical Engineering, Doctor of Philosophy (Ph.D.) Mechanical Engineering at Stanford University
Github Skills (12)
python10
apidoc9
c119
api9
c179
optimization8
optimisation8
numerical-methods8
optmization8
performance-optimization8
scipy6
numpy6
Programming languages (2)
Github contributions (2)
embotech/ecos
May 2014 - May 2014
A lightweight conic solver for second-order cone programming.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:15 commits in 7 days
Contributions summary:Thomas primarily focused on enhancing the Python interface for the ECOS solver, a conic programming tool. Their work involved adding functionality to handle optional parameters, particularly tolerances and iteration limits, through the modification of the `ecosmodule.c` and `ecos.py` files. These changes involved implementing parameter parsing and setting, updating documentation, and integrating kwargs to provide more flexibility in the solver's usage. This work directly improves the usability and configurability of the ECOS solver's Python API.
conicsecond-ordercone-programmingsatsolver
gummyboars/lunboks
Feb 2021 - Nov 2021
Contributions:40 reviews, 6 commits, 12 PRs in 8 months
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