Sadegh Rabiee
Applied Scientist at Amazon Lab126
San Diego, California, United States
Summary
👤
Senior🎓
Top SchoolSadegh Rabiee is an applied scientist with a decade of experience building competence-aware perception and safe navigation systems for mobile robots, currently working on mapping for Amazon Astro in San Diego. He develops self-supervised, ML-driven perception algorithms that improve reliability in deployment, spanning obstacle avoidance, localization, and mapping for service, delivery, and autonomous vehicles. His academic path—PhD at UT Austin and MS at UMass Amherst—underpins a strong research-to-product trajectory, with hands-on experience like vision-based autodocking for OhmniLabs. Comfortable bridging rigorous research and production constraints, he focuses on robots that continually learn from the environments they operate in to boost operational safety and robustness.
10 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at The University of Texas at AustinUniversity of Massachusetts AmherstBachelor’s Degree, Electrical and Electronics Engineering, Bachelor’s Degree, Electrical and Electronics Engineering at University of Tehran
English, Persian, German
Github Skills (24)
carrot9
automata8
localization8
simultaneous8
planning6
robot6
markov5
computer-vision5
robotics5
infrastructure4
graph4
terraform4
ros4
slam4
nodes3
Programming languages (4)
Github contributions (5)
ut-amrl/IV_SLAM
Nov 2020 - Oct 2021
Introspective Vision for Simultaneous Localization and Mapping
Contributions:2 reviews, 14 commits, 4 pushes in 11 months
visioncomputer-visionmappingsimultaneouslocalization
ut-amrl/AirSim
Apr 2020 - May 2021
Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research
Contributions:3 PRs, 12 pushes, 3 branches in 1 year
airsimunreal-engineroboticsautonomousunity-engine
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