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About

B. N. Babich is a leading researcher in robot learning and simulation, whose work has fundamentally advanced the field of legged locomotion. Their key research areas include reinforcement learning for robotics, simulation-to-reality transfer, and interactive robot learning environments. Babich’s most impactful contribution is the development of **Orbit**, a unified simulation framework powered by NVIDIA Isaac Sim that has garnered 226 citations since 2023. This modular platform enables researchers to create photo-realistic robotic environments with high-fidelity rigid and deformable body simulation, establishing a new standard for interactive robot learning. In quadrupedal locomotion, Babich pioneered **dynamics randomization** techniques that systematically bridge the simulation-reality gap, with their 2021 case study accumulating 75 citations. Their **GLiDE** framework (43 citations) introduced a centroidal model for generalizable locomotion across diverse environments, while **Geometric Fabrics** (29 citations) generalized classical mechanics to capture the physics of behavior. Babich also developed a contact-adaptive hierarchical controller (25 citations) that robustly combines model-based control with reinforcement learning for the Unitree Laikago quadruped. Through these innovations, Babich has become a pivotal figure in making simulated robot training more realistic, efficient, and transferable to the physical world.