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About

Efi Psomopoulou is a robotics researcher whose work spans robot control, robotic manipulation, surgical robotics, and tactile sensing. She has made significant contributions to the development of intelligent control systems for robots that must interact safely and dexterously with complex, uncertain environments. Her early work on variable stiffness actuated robots — now with 90 citations — established robust prescribed performance control strategies that operate without full knowledge of system dynamics, a critical advance for compliant robotic systems. She has since extended her expertise to robotic hands and grasping, co-developing the BRL/Pisa/IIT SoftHand, a low-cost, 3D-printed underactuated hand (41 citations), and pioneering tactile-driven grasping strategies that use biomimetic fingertip sensors to enable gentle, adaptive manipulation in human-robot collaborative settings. In surgical robotics, Psomopoulou has proposed neural network-based methods for estimating tool-tissue interaction forces without external sensors — an important step toward safer minimally invasive surgery. Her research on human-inspired handover policies and finger motion tracking further demonstrates her commitment to bridging human and robot capabilities. Collectively, her portfolio reflects a researcher dedicated to making robots more adaptive, safe, and physically intelligent across healthcare and manufacturing domains.