Max Robotics — Global Service Robot Directory + US Certification

About

Allan Zhao is a multidisciplinary researcher whose work spans wearable sensing technologies, soft robotics, and automated robot design. His most widely recognized contribution is his work on wearable microfluidic diaphragm pressure sensors, which leverage liquid-metal composites to achieve strains exceeding 200%, enabling robust applications in health monitoring, tactile sensing, and flexible electronics — a paper that has garnered nearly 600 citations and established him as a notable voice in wearable technology research. Zhao's subsequent work pivots toward computational robotics, with a particular focus on automated co-design frameworks that simultaneously optimize robot morphology and control. His RoboGrammar system (2020, 140 citations) introduced a graph grammar-based approach to automatically generating terrain-optimized robot structures, a significant methodological advance that has since inspired extensions to aerial vehicles, underwater robots, and heterogeneous fleets. His research into soft robot co-design further demonstrates his interest in bridging learning-based control with physical design. Spanning hardware fabrication, machine learning, and computational design, Zhao's body of work reflects a rare breadth — from 3D-printed embedded electronics to multi-objective robot optimization — making him a compelling researcher at the intersection of intelligent systems and physical robotics.