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About

Jiaqi Tu is an emerging research leader at the intersection of soft electronics, tactile sensing, and human-machine interfaces. His work centers on developing advanced stretchable and flexible sensor systems that mimic the sophisticated sensory capabilities of human skin, integrating these technologies with machine learning to enable intelligent, responsive systems. Tu's most influential contribution, "Fusing Stretchable Sensing Technology with Machine Learning for Human–Machine Interfaces" (159 citations), established a foundational framework for combining soft sensor hardware with data-driven algorithms. His pioneering work on tactile near-sensor analogue computing (121 citations) addressed critical bottlenecks in artificial skin by eliminating redundant data conversion processes, enabling ultrafast response times with transformative applications in prosthetics and robotics. His bimodal force-softness sensor arrays (60 citations) pushed tactile technology into clinically relevant territory, enabling identification of human body features for medical diagnostics. More recently, Tu has advanced bio-inspired multi-modal mechanoreceptors and sensorimotor integration in soft robotics, reflecting a deepening ambition to replicate biological sensing systems holistically. With over 470 total citations accumulated across just a few productive years, Tu's research trajectory signals him as a significant voice shaping the future of intelligent soft robotic and wearable sensing technologies.