Riley Young

The University of Texas Southwestern Medical Center, University of Wisconsin–Stout

Papers

Total Citations

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About

Riley Young is a uniquely interdisciplinary researcher whose work bridges the critical gap between surgical ergonomics and robotic wireless power systems. In medicine, Young has pioneered strategies to combat work-related musculoskeletal disorders (WMSDs) among surgeons, particularly in minimally invasive gynecologic surgery. Their landmark 2023 paper, "Growing pains: strategies for improving ergonomics in minimally invasive gynecologic surgery" (12 citations), systematically evaluates ergonomic strain factors and proposes actionable mitigation protocols—a contribution that addresses the alarming prevalence of chronic pain among surgical specialists. Simultaneously, Young has made significant advances in engineering, applying deep reinforcement learning to optimize wireless power transfer for IoT devices. Their 2022 work on "Optimal Path Planning for Wireless Power Transfer Robot Using Area Division Deep Reinforcement Learning" (9 citations) introduces novel algorithms for mobile RF transmitters to efficiently charge distributed sensor networks. A subsequent paper extends this framework using finite state machine reinforcement learning (3 citations). This dual-domain expertise—combining human-centered surgical safety with autonomous robotic energy systems—positions Young as a rare translational thinker whose work impacts both operating room well-being and sustainable IoT infrastructure.