Michael Sotzing

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About

Michael Sotzing is a rising innovator at the intersection of soft robotics, reconfigurable materials, and intelligent control systems. His primary research focuses on developing adaptive, morphing surfaces that can change shape on demand—a critical capability for advanced human-machine interfaces and bio-inspired robotics. Sotzing’s most notable contribution is the creation of the Passively Addressed Robotic Morphing Surface (PARMS), which integrates machine learning to solve the complex inverse control problem of coordinating numerous actuators in a compact, efficient manner. This work, published in 2023, has already garnered 19 citations, signaling its rapid impact in the field. By enabling arbitrary surface morphing with reduced hardware complexity, Sotzing’s research paves the way for next-generation haptic displays, adaptive aerodynamic surfaces, and soft robotic grippers. His approach represents a significant step toward practical, scalable morphing systems that bridge the gap between computational intelligence and physical reconfiguration. For students and researchers exploring the future of adaptive materials and embodied AI, Sotzing’s work offers a compelling blueprint for how machine learning can unlock the full potential of soft, shape-changing structures.