Max Robotics — Global Service Robot Directory + US Certification

About

Minjune Hwang is a rising star in embodied AI and human-robot interaction, pioneering methods to make robots useful for everyday life. His research centers on brain-robot interfaces, reinforcement learning from human feedback, and large-scale simulation benchmarks. In his highly cited work "NOIR," Hwang introduced a general-purpose, intelligent system that allows humans to command robots to perform daily tasks using only neural signals, bridging the gap between brain activity and robotic action. His "SEED" framework tackles the challenge of long-horizon manipulation by combining primitive skills with human evaluative feedback, dramatically improving sample efficiency and safety in real-world learning. As a core contributor to the BEHAVIOR-1K benchmark, Hwang helped create a comprehensive simulation environment grounded in a survey of 1,000 everyday activities people want robots to perform. With over 20 citations across his key papers, Hwang's work is shaping the future of assistive robotics, making it more intuitive, safe, and aligned with human needs. His achievements demonstrate a rare ability to integrate neuroscience, machine learning, and robotics into practical, human-centered systems.