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About

Fani Deligianni is a prominent researcher at the intersection of artificial intelligence, robotics, and healthcare technology, with particular expertise in medical imaging, surgical robotics, human performance monitoring, and assistive technologies. Her early groundbreaking work on soft-tissue motion tracking for robotic-assisted minimally invasive surgery, now garnering over 150 citations, established her as a leading voice in surgical robotics and laid the foundation for safer, more precise robotic surgical systems. Deligianni has made significant contributions to gait analysis using RGB-D cameras, developing innovative approaches to detecting abnormal movement patterns in elderly and neurologically impaired patients — work critical to fall prevention and home-based healthcare. Her research on eye-tracking for workload estimation in space telerobotics (61 citations) demonstrates her broad interdisciplinary reach, bridging cognitive science and human-robot interaction. She has also advanced wearable robotics for upper-limb rehabilitation and explored brain connectivity through fNIRS to understand expertise development in complex motor tasks. With over 500 cumulative citations across her portfolio, Deligianni's work consistently addresses real-world clinical challenges, positioning her as an influential figure in translational AI and robotics research for healthcare applications.