Peyman Yadmellat
Staff Deep Learning Engineering - Motion Planning at Woven by Toyota
San Francisco Bay Area United States
Summary
👤
Senior🎓
Top SchoolPeyman Yadmellat is a Staff Deep Learning Engineer specializing in motion planning and control for autonomous vehicles, combining a Ph.D. in Electrical and Computer Engineering with 11 years of hands-on experience across industry and academia. He has led RL research, developed RL-friendly simulators, and driven system integration and road tests at scale for companies like Huawei and Woven by Toyota. His background spans control theory, magneto-rheological actuators, embedded systems, and geometric/heuristic optimization, enabling a unique blend of theoretical rigor and practical system design. Comfortable in C/C++, Python, ROS and MATLAB, he builds production-ready pipelines—from simulation to on-vehicle testing—while advancing novel RL approaches for safe, human-aware motion. An understated strength is his history of designing intrinsically safe actuators and haptic devices, reflecting a deep appreciation for physical system constraints that informs his autonomy work.
11 years of coding experience
17 years of employment as a software developer
PhD Electrical and Computer Engineering, PhD Electrical and Computer Engineering at Western UniversityAmirkabir University of Technology
English, Persian
Github Skills (13)
gazebo-simulator6
rendering5
simulator5
ros5
robotics5
robotics-simulation5
simulation5
gazebosim4
physics4
robot-simulator4
ignition3
openscenegraph3
sdf3
Programming languages (2)
Github contributions (5)
pyadmell/flying-car-udacity
Mar 2018 - Jul 2018
Contributions:45 commits, 93 pushes, 1 branch in 4 months
pyadmell/deep-reinforcement-learning-udacity
Jan 2019 - Mar 2019
Contributions:45 commits, 52 pushes, 6 branches in 2 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.