Rate My Professor Stamatia Giannarou

Stamatia Giannarou is a Reader in Surgical Cancer Technology and Imaging in the Department of Surgery and Cancer within the Faculty of Medicine at Imperial College London. She serves as a Royal Society University Research Fellow at the Hamlyn Centre for Robotic Surgery and heads the Cognitive Vision in Robotic Surgery research group. Her research specializes in robotics and computing, with a primary focus on robotic vision for surgical navigation, AI-guided robot-assisted tissue scanning, real-time image reconstruction for minimally invasive interventions, and technologies for enhanced tumor resection in cancer surgery. Giannarou's work advances cognitive vision systems that integrate multimodal imaging, deep learning for tissue characterization, and intraoperative guidance to improve surgical precision and patient outcomes.

She obtained her MEng degree in Electrical and Computer Engineering from Democritus University of Thrace, Greece, in 2003, followed by an MSc in Communications and Signal Processing from Imperial College London in 2004, and a PhD in object recognition from the Department of Electrical and Electronic Engineering at Imperial College London in 2008. Her career at Imperial College has progressed through research fellowship to lecturer and senior lecturer positions, culminating in her promotion to Reader. Giannarou has secured major grants including the Royal Society University Research Fellowship, an MRC award for Oncological Resection Guidance Across Scales valued at £977,288, and funding from NIHR Imperial Biomedical Research Centre. She was honored with Imperial College London's President's Award for Outstanding Early Career Researcher in 2017, along with best paper awards at MICCAI workshops, IPCAI, and Philips/IPCAI. With over 135 publications and more than 3,600 citations, her influential works include 'Vision-based deformation recovery for intraoperative force estimation of tool–tissue interaction for neurosurgery' (2016), 'Surgical data science – from concepts toward clinical translation' (2022), 'Benchmark of soft-tissue trackers for robotic surgery' (2024), 'Explainable Image Classification with Improved Confidence via Spatial-Frequency Guided Risk Estimation' (2024), and 'Multimodal imaging platform for enhanced tumor resection' (2025). Her contributions extend to editorial roles, conference organization such as IPCAI and Hamlyn Symposium, and public engagement through invited lectures on AI in robotic surgery.