Max Robotics — Global Service Robot Directory + US Certification

About

Wonse Jo is a versatile robotics researcher whose work spans unmanned systems, human-robot interaction, and affective computing. He is perhaps best known for his contributions to accessible unmanned surface vehicles (USVs), most notably his 2019 open-source, low-cost USV platform for real-time water quality monitoring, which has garnered 77 citations and demonstrated meaningful impact in environmental robotics. That same year, he extended this work to harmful algal bloom remediation, reflecting a sustained commitment to applied aquatic robotics. Jo's research equally addresses the human side of robotics. His work on adaptive workload allocation for multi-human multi-robot teams (26 citations) highlights his interest in optimizing collaboration between humans and autonomous systems, while his Autonomy Acceptance Model advances our understanding of how people perceive and trust security robots. His development of a ROSbag-based multimodal affective dataset further underscores his contributions to emotionally intelligent systems. An earlier thread of Jo's work focuses on musical robotics, particularly violin-playing robots, where he investigated bowing mechanics and auditory feedback to improve sound quality. More recently, he has explored personalized tour-guide robots and open-source HRI experimental tools. Across these diverse domains, Jo consistently prioritizes accessibility, real-world applicability, and meaningful human-robot collaboration.