Baskın Şenbaşlar
Senior Software Engineer, Behavior Planning - Autonomous Vehicles at NVIDIA
California, United States
Summary
👤
Senior🎓
Top SchoolBaskın Şenbaşlar is a Senior Software Engineer specializing in behavior planning and prediction for autonomous vehicles, currently building urban and highway planning stacks at NVIDIA. With 11 years of experience spanning industry internships at Google and NVIDIA and a PhD-focused research track at USC, he bridges rigorous academic research in multi-robot planning with production-grade systems engineering. He has a strong algorithmic background demonstrated by contributions to CGAL—implementing and optimizing the Garland-Heckbert edge collapse algorithm—and practical experience integrating uncertainty-aware probabilistic planning into AV stacks. Based in California, he combines low-level algorithm work, real-time decision making for drones and ground vehicles, and large-scale traffic engineering exposure to deliver robust, performant motion planners.
11 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Southern CaliforniaBachelor of Science - BS, Computer Engineering, 3.89/4.0, Bachelor of Science - BS, Computer Engineering, 3.89/4.0 at Orta Doğu Teknik Üniversitesi / Middle East Technical University
English, Turkish
Stackoverflow
1reputation
59reached
0answers
1question
Github Skills (11)
computational-geometry10
algorithms10
c-language10
cgal10
template-tags10
template-engine10
geometry10
cprogramming-language10
templater10
mesh-processing10
eigen9
Programming languages (5)
Github contributions (5)
CGAL/cgal
Jun 2019 - Jul 2019
The public CGAL repository, see the README below
Role in this project:
Back-end Developer
Back-end DeveloperContributions:10 commits, 1 issue in 1 month
Contributions summary:Baskın implemented and refined the Garland-Heckbert edge collapse algorithm within the CGAL library. Their contributions included core algorithm implementation, handling non-invertible matrix cases, and addressing issues related to border simplification. They also added examples and timing functionality to demonstrate the algorithm's performance and usage, demonstrating an understanding of algorithm optimization and application.
cgalc-plus-plusgeometrycpptemplate-library
USC-ACTLab/rlss
Feb 2018 - Jan 2022
Contributions:218 commits, 14 pushes, 1 branch in 3 years 11 months
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