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About

Yuri Lapusta is a leading researcher at the intersection of soft robotics and smart materials, whose work is redefining dexterous manipulation and actuation. His core research areas include soft robotic grippers, shape memory alloys (SMAs), and tactile sensing. Lapusta’s most significant contribution is the development of a fully dexterous soft robotic gripper featuring an active palm and reconfigurable fingers, which enables complex in-hand manipulation without added mechanical complexity—a breakthrough cited 78 times. He has also advanced the field through a comprehensive review of neural network modeling for SMAs (53 citations), addressing the challenge of nonlinear behavior in real-time simulations. In tactile sensing, Lapusta designed a large-area, low-cost capacitive sensor (51 citations) that is flexible and easy to fabricate, making it ideal for soft robotic applications. His work on optimizing a dexterous robotic finger with a sliding, rotating, and soft-bending mechanism (18 citations) further demonstrates his commitment to maximizing dexterity while minimizing dimensions. Lapusta’s innovative use of deep learning, including LSTM networks for controlling antagonistic SMA systems, showcases his ability to merge artificial intelligence with smart materials. His research is widely recognized for its practical impact, offering scalable solutions for robotics, sensors, and actuators.