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About

Sergey Yaroshenko is a robotics researcher whose work centers on advancing bimanual teleoperation and robot learning through accessible, high-performance hardware design. His primary contributions lie in developing low-cost, robust platforms that enable the collection of diverse, high-quality demonstration data—a critical bottleneck for scaling dexterous manipulation in robotics. Yaroshenko is best known as a co-author of the highly influential ALOHA 2 system (2024), an enhanced iteration of the original ALOHA hardware that significantly improves performance, durability, and ease of use for bimanual teleoperation. This work has already garnered attention with 8 citations in its first year, reflecting its immediate impact on the field. By dramatically lowering the cost barrier while increasing reliability, Yaroshenko’s research empowers laboratories worldwide to generate richer datasets, directly fueling advances in imitation learning and generalizable robot skills. His engineering-driven approach exemplifies how thoughtful hardware design can unlock new capabilities in learning-based robotics, making sophisticated manipulation research more democratic and reproducible.