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About

Hanna Kossowsky is a researcher at the forefront of haptic feedback and human-robot interaction, with a specific focus on transforming robot-assisted minimally invasive surgeries (RAMIS). Her work addresses a critical gap in current surgical systems: the lack of comprehensive haptic feedback, which is essential for a surgeon’s perception of tissue stiffness and safe manipulation. Kossowsky’s key contributions include demonstrating how combining artificial tactile noise (skin-stretch) with kinesthetic force feedback can significantly enhance stiffness perception and grip force control, a finding that has direct implications for improving surgical precision and safety. Her research also extends to autonomous surgical systems; she has developed predictive models using artificial neural networks to anticipate camera movements from instrument kinematics, aiming to reduce surgical interruptions. Furthermore, Kossowsky has identified a novel power law linking tool-tip orientation speed to geometry in teleoperation, a fundamental motor invariant that can inform the design of more intuitive surgical interfaces. With her most cited work accumulating over 25 citations since 2022, Kossowsky is establishing herself as a rising innovator in surgical robotics, bridging the gap between human sensorimotor control and advanced robotic systems.