Rey Pocius

University of Southern California, Oregon State University

Papers

Total Citations

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About

Rey Pocius investigates the intersection of human-robot interaction, assistive manipulation, and computational education. Their research focuses on enhancing shared autonomy systems, where human teleoperation blends with robot intelligence to improve control in assistive scenarios. A key contribution is their work on communicating robot goals through haptic feedback during manipulation tasks, which addresses the critical challenge of maintaining user control authority when robots predict and act on human intentions. This paper has garnered 7 citations, reflecting its relevance to the assistive robotics community. Pocius also advanced reinforcement learning for high-degree-of-freedom robots like the PR2, using neural networks to reduce state-space dimensionality—a foundational step toward making complex personal robots viable in real-world settings. Beyond robotics, Pocius has made notable contributions to broadening participation in computing, developing a low-cost, scalable research-practitioner collaboration to build early elementary teachers’ confidence in teaching computer science. This work targets under-resourced districts, addressing an urgent need for computational literacy in primary education. With a portfolio spanning technical robotics innovation and educational equity, Pocius demonstrates a commitment to both advancing assistive technology and ensuring its benefits reach diverse communities.