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About

Pakpoom Patompak is a robotics researcher whose work spans two compelling domains: human-robot social interaction and underwater vehicle control. He is best known for his pioneering contributions to socially aware robot navigation, particularly his development of learning-based frameworks that enable robots to adapt their behavior to individual human preferences and cultural norms. His most influential work, "Learning Proxemics for Personalized Human–Robot Social Interaction" (2019), has garnered 61 citations and introduced sophisticated approaches for modeling the invisible social boundaries — known as proxemics — that govern how people comfortably interact in shared spaces. Building on this, his research into the Social Force Model and culturally adaptive interaction demonstrates a nuanced understanding that effective human-robot collaboration must account for personal and cultural variability. Earlier in his career, Patompak made significant contributions to underwater robotics, developing robust adaptive control algorithms and backstepping sliding-mode controllers for remotely operated vehicles navigating challenging hydrodynamic environments. Together, his body of work reflects a versatile engineering mind committed to making robots safer, more intuitive, and more socially intelligent across diverse real-world settings.