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About

Chengdi Zhou is a pioneering researcher in the field of shape-changing robotics, with a primary focus on deformable robotic mannequins and human-robot interfaces. His work centers on developing intelligent, shape-controllable systems that can accurately mimic the diverse forms of the human body—a challenge that sits at the intersection of mechatronics, soft robotics, and computational design. Zhou’s major contributions include the design of a robotic mannequin composed of a flexible belt net and layered structures (shoulder, chest, waist, and hip), enabling multi-objective shape imitation for applications in garment design and online retail. His most cited paper, “Design of robotic mannequin formed by flexible belt net” (2019, 15 citations), established a foundational approach to deformable mannequins. More recently, he has advanced the field by integrating machine learning for shape control and reprogrammable stiffness, as seen in his 2024 work. Zhou’s bio-inspired, rigid-flexible-soft coupling methods, particularly for shoulder imitation, demonstrate his commitment to solving complex, real-world problems. With a growing citation record and a clear trajectory toward intelligent, adaptive robotic systems, Zhou is a rising voice in shape-changing robotics and human-centered design.