Julyando Phan

Tokyo University of Agriculture and Technology

Papers

Total Citations

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About

Julyando Phan is a robotics and control systems researcher whose work bridges the fields of adaptive control, human-robot interaction, and autonomous robotic systems. His research focuses primarily on developing intelligent control architectures that enable robots to move and behave in socially meaningful ways, with a particular emphasis on expressive motion generation in robotic arms. Phan's most significant contributions center on the application of adaptive fuzzy logic and robust predictive control methods to produce lifelike, dynamic movement in social robots. His 2019 paper on adaptive fuzzy and predictive controllers for expressive robot arm movement has garnered 15 citations, building on earlier foundational work published in 2018 that explored how robots can convey believability and emotional states through motion in interactive contexts. Together, these works represent a cohesive body of research addressing one of the central challenges in social robotics: making machines feel natural and responsive to humans. Earlier in his career, Phan contributed to autonomous robotic systems through PICARSO, a cable-driven robotic graffiti artist capable of autonomously rendering both raster and vector images — a creative demonstration of image processing integrated with robotic control. With a modest but growing citation profile, Phan's work offers meaningful contributions to the intersection of expressive robotics and intelligent control design.