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Samuel Ehrenstein
Mid-level Computer Vision & ML Researcher specializing in medical imaging and 3D vision
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About
PhD (CS) candidate with hands-on autonomy and robotics experience: improved safety-critical behavior for Kodiak’s self-driving 18-wheeler trucks, increasing overtaking clearance by ~2 feet and reducing safety alerts. Also debugged a C++ SLAM system for 3D colon reconstruction and built a low-budget distributed simulation cluster using Linux, Docker, and Python, plus implemented multi-hop SSH-based comms for an underwater robotics competition minibot.
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Key Strengths
- Improved autonomous truck overtaking-pull-over behavior using rule-based + deep learning inputs
- Applied physics-based modeling to tune smooth braking under jerk constraints
- Delivered measurable safety improvement: increased lateral clearance by ~2 ft (0.6 m) and reduced safety alerts
- Deep debugging of SLAM pipeline (C++ concurrency/mutex issue tied to GPU shader cache and constrained storage)
- Resourceful distributed compute: built an ad-hoc Linux cluster and orchestrated thousands of simulations with Docker + Python task pooling
- Pragmatic heterogeneous robot comms: multi-hop SSH tunnel for minibot video + control via Raspberry Pi Zero
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Experience
Education
Awards
Skills
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Publications
5 publications
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