Summary
Ardi Loot is a Principal Software Engineer with nine years of experience building perception systems for autonomous vehicles, currently focused on advanced sensor fusion and detection at Microsoft after a multi-year tenure leading perception work at Starship Technologies. He holds a PhD in Physics from the University of Tartu and brings a research-first mindset to production problems, having translated experimental optics and simulation expertise into practical ToF, stereo, radar and ultrasonic perception algorithms. His work spans classical methods (multi-level clustering, Random Forests, Kalman filters) and neural pointcloud/semantic segmentation models for detecting stairs, holes, snowpiles and unmapped drivable areas, plus sensor calibration and hardware-emulating testbeds to improve reliability. Known for rewriting critical subsystems (radar) and creating machine-learned range estimators, he pairs deep analytical skills with hands-on product engineering. Active on GitHub, he maintains a portfolio that reflects breadth across algorithms, simulation and embedded-aware perception solutions.
10 years of coding experience
16 years of employment as a software developer
Hugo Treffner's High School
Physics, Physics at University of Toronto
Doctor of Philosophy - PhD, Physics, Doctor of Philosophy - PhD, Physics at University of Tartu
English, Estonian