Professor Fernando Bello is a computer scientist and engineer working at the intersection of medicine, education and technology. He obtained his PhD in Biomedical Systems from Imperial College in 1996 and worked as a postdoctoral Research Fellow on brain image analysis and Computer Aided Surgery from 1996-1998 at Guy's Hospital, and at the University of Kent, where in 1998 he became a Lecturer in Electronic Engineering.
He re-joined Imperial in September 2000 and is currently Professor of Surgical Computing and Simulation Science within the Department of Surgery and Cancer, where he is Director of the Centre for Engagement and Simulation Science, leading the SiMMS - Simulation and Modelling in Medicine and Surgery research group. A multi-disciplinary research group aiming at building suitable models and simulations of clinical processes, including clinical examination, clinical diagnosis, interventional procedures and care pathways.
Prof Bello is particularly interested in the use of virtual / mixed reality environments and haptics in the context of education and training, pioneering advanced patient specific simulation of a number of surgical procedures and clinical examinations, online and mobile simulation tools, as well as innovative approaches to contextualised simulation. He has published widely in technological, medical and educational journals, is involved in several simulation-based training programmes in the UK and abroad and is Academic Co-director of Imperial’s MSc in Surgical Innovation.
et al., 2020, Rectal 3D MRI modelling for benign and malignant disease, British Journal of Surgery, Vol:107, ISSN:0007-1323, Pages:e561-e562
et al., 2020, Effectiveness of technology-enhanced simulation in teaching digital rectal examination: a systematic review narrative synthesis, Bmj Simulation and Technology Enhanced Learning
et al., 2020, A review of training and guidance systems in medical surgery, Applied Sciences, Vol:10, ISSN:2076-3417, Pages:1-35
Haghighi Osgouei R, Soulsby D, Bello F, 2020, Rehabilitation Exergames: use of motion sensing and machine learning to quantify exercise performance in healthy volunteers, Jmir Rehabilitation and Assistive Technologies, Vol:7, ISSN:2369-2529
et al., 2020, Augmented reality system for digital rectal examination training and assessment: system validation, Journal of Medical Internet Research, Vol:22, ISSN:1438-8871, Pages:1-13