Max Robotics — Global Service Robot Directory + US Certification

About

Aaron Gokaslan is a leading researcher at the intersection of embodied AI, robotics, and simulation, whose work is fundamentally redefining how we train and evaluate intelligent agents for the physical world. His primary research areas include sim-to-real transfer, interactive 3D simulation platforms, and reinforcement learning for robotic manipulation. Gokaslan made a landmark contribution with his work on the **Sim2Real gap** (39 citations), critically questioning whether progress in simulated environments translates to real-world robotics—a foundational paper that has shaped the field’s evaluation standards. He is a core architect of **Habitat 2.0** (25 citations), a groundbreaking simulation platform that provides the data, physics, and benchmarks necessary to train home assistants for complex rearrangement tasks. More recently, he led the development of **Galactic**, a framework achieving 100,000 steps-per-second for end-to-end reinforcement learning, dramatically accelerating training for mobile manipulation. Beyond simulation, Gokaslan is also a leader in responsible AI, co-authoring influential work on the standardization of behavioral use clauses for AI licensing. His work consistently bridges the gap between high-fidelity simulation and deployable robotic intelligence.