Max Robotics — Global Service Robot Directory + US Certification

About

Behzad Boroujerdian is a leading researcher at the intersection of autonomous aerial robotics, deep reinforcement learning (DRL), and energy-efficient computing. His work centers on making Micro Aerial Vehicles (MAVs) more intelligent and practical by optimizing the tight coupling between algorithms and onboard hardware. Boroujerdian is best known for creating **Air Learning**, an open-source simulator and gym environment that has become a key benchmark for DRL research on resource-constrained drones. By incorporating domain randomization, his platform enables researchers to train robust navigation policies that transfer to real-world, challenging scenarios. His highly cited work—with the foundational Air Learning paper accumulating 43 citations—has established a standard for algorithm-hardware co-design in aerial robotics. Beyond simulation, Boroujerdian has made critical contributions to understanding the role of onboard compute in mission efficiency, demonstrating how hardware choices directly impact flight time and energy consumption. He also developed **RoboRun**, a runtime system that exploits spatial heterogeneity in operating environments to save energy. Through his open-source tools and rigorous benchmarking, Boroujerdian is empowering the next generation of autonomous drones to fly smarter, longer, and more efficiently.