2019 Programme is now online: Hamlyn Winter School 2019 Programme

Programme Overview


 Adrien Bartoli Adrien Bartoli Université Clermont Auvergne, France Adrien Bartoli has held the position of Professor of Computer Science at Université Clermont Auvergne since fall 2009 and is a member of Institut Universitaire de France since fall 2016. He leads the Endoscopy and Computer Vision (EnCoV) research group at the University and Hospital of Clermont-Ferrand. His main research interests are in computer vision, including image registration and Shape-from-X for rigid and deformable environments, and its application to computer-aided endoscopy.
 Christos Bergeles Christos Bergeles King’s College London, UK Christos Bergeles (King’s), Senior Lecturer, directs the “Robotics and Vision in Medicine Lab” whose mission is to develop micro-surgical robots that deliver regenerative therapies deep inside the human body. Dr Bergeles has been awarded an ERC Starting Grant and holds i4i NIHR funding for the development of instrumentation that delivers stem cells to diseased retinal layers. His active grant funding as PI is > £2.5M, which supports his team of 6 PhD students and 4 PDRAs. He has co-authored > 40 articles in top-tier conferences and journals, and his research has been cited > 800 times. He is an Associate Editor of the IEEE Transactions on Robotics, and the IEEE Int. Conf. Robotics and Automation. He is regularly invited as an invited speaker at international workshops and schools. His team and he are very active in public engagement and patient involvement activities, and regularly deliver keynotes to broad engineering audiences (e.g. at the IET Savoy Place, attracting more than 200 participants), but also children and lay members of the public (e.g. Pint of Science, and Secret Cinema in collaboration with the Royal Institution).
 Dan Elson Dan Elson Imperial College London, UK Daniel Elson is a Professor in the Hamlyn Centre for Robotic Surgery, Department of Surgery and Cancer and the Institute of Global Health Innovation. Research interests are based around the development and application of photonics technology with endoscopy for surgical imaging applications, including multispectral imaging, polarization-resolved imaging, fluorescence imaging, and the use of fluorescently labelled gold nanorods for theranostics. Further projects include work on the development of illumination and vision systems for endoscopy combining miniature light sources such as LEDs and laser diodes with computer vision techniques for structured lighting and tissue surface reconstruction as well as the use of robotic guidance of optical probes. These devices are finding application in minimally invasive surgery and in the development of new flexible robotic assisted surgery systems. Professor Elson has published over 100 peer reviewed journal articles, one edited book, twelve book chapters and has contributed to more than 300 conferences.
 Dan Stoyanov Dan Stoyanov University College London, UK Dan Stoyanov is a Senior Lecturer at the Department of Computer Science, University College London (UCL) and also an academic at the Centre for Medical Image Computing (CMIC). His research interests are in the development of surgical vision or surgical robot vision, which refers to computer vision and pattern analysis techniques applied to images obtained during minimally invasive surgery and robotic assisted surgery. These stem from his doctoral work on soft-tissue 3D reconstruction and motion tracking at the Royal Society/Wolfson MIC Laboratory and the Hamlyn Centre for Robotic Surgery, Imperial College London.
 Daniel Rueckert Daniel Rueckert Imperial College London, UK Daniel Rueckert is Head of the Department of Computing at Imperial College London. He joined the Department of Computing as a lecturer in 1999 and became senior lecturer in 2003. Since 2005 he is Professor of Visual Information Processing. He has founded and leads the Biomedical Image Analysis groupconsisting of four academics, 15 post-docs and 20 PhD students. He received a Diploma in Computer Science (equiv. to M.Sc.) from the Technical University Berlin and a Ph.D. in Computer Science from Imperial College London. Before moving to Imperial College, he was a post-doctoral research fellow at King’s College London where he has worked on the development of non-rigid registration algorithms for the compensation of tissue motion and deformation. The developed registration techniques have been successfully used for the non-rigid registration of various anatomical structures, including in the breast, liver, heart and brain and are currently commercialized by IXICO, an Imperial College spin-out company. During his doctoral and post-doctoral research he has published more than 500 journal and conference articles as well as graduated over 45 PhD students. Professor Rueckert is an associate editor of IEEE Transactions on Medical Imaging, a member of the editorial board of Medical Image Analysis, Image & Vision Computing, MICCAI/Elsevier Book Series, and a referee for a number of international medical imaging journals and conferences. He has served as a member of organising and programme committees at numerous conferences, e.g. he has been General Co-chair of MMBIA 2006 and FIMH 2013 as well as Programme Co-Chair of MICCAI 2009ISBI 2012 and WBIR 2012. In 2014, he has been elected as a Fellow of the MICCAI society and in 2015 he was elected as a Fellow of the Royal Academy of Engineering and as fellow of the IEEE. More recently has been elected as Fellow of the Academy of Medical Sciences (2019).
 Edward Johns Edward Johns Imperial College London, UK Edward Johns is the Director of the Robot Learning Lab at Imperial College London, where he is also a Lecturer and Royal Academy of Engineering Research Fellow. His work lies at the intersection of Robotics, Computer Vision, and Machine Learning, and his lab is studying learning-based approaches for visually-guided robot manipulation. He received a BA and MEng in Electrical and Information Engineering from Cambridge University, and a PhD in visual place recognition from Imperial College. Following his PhD, he was a postdoc at UCL, before returning to Imperial College as a founding member of the Dyson Robotics Lab along with Andrew Davison, where he led the robot manipulation team. In 2017, he was awarded a Royal Academy of Engineering Research Fellowship for his project "Empowering Next-Generation Robots with Dexterous Manipulation: Deep Learning via Simulation", and then in 2018 he was appointed as a Lecturer and founded the Robot Learning Lab.
 Erik Mayer Erik Mayer Imperial College Healthcare NHS Trust, UK  
 Ferdinando Rodriques Y Baena Ferdinando Rodriques Y Baena Imperial College London, UK Ferdinando Rodriguez y Baena is Professor of Medical Robotics in the Department of Mechanical Engineering at Imperial College, where he leads the Mechatronics in Medicine Laboratory ( He is also the Mechanical Engineering Postgraduate Tutor, and the current Speaker for the Imperial College Robotics Forum ( His current research interests lie in the application of mechatronic systems to medicine, in the specific areas of clinical training, diagnostics and surgical intervention. His team has a strong translational focus, while his work encompasses both “blue skies” research and “near-to-market” development. Prof Rodriguez y Baena graduated with a First Class Honours degree in Mechatronics and Manufacturing Systems Engineering from King’s College London in 2000 and gained a PhD in Medical Robotics from Imperial College in 2004. He was an Associate Editor for the IEEE Robotics and Automation Magazine, and he is the Chair of the Programme Committee for the International Society for Computer Assisted Orthopaedic Surgery, the International Workshop on Medical Robotics and the Joint Workshop on New Technologies for Computer/Robot Assisted Surgery; he is also the Chair of the IET’s Communities Committee for Technical and Professional Networks, a Leverhulme Prize winner (engineering), a former ERC grant holder, and the coordinator of an €8.3M European project on robotic-assisted neurosurgical drug delivery ( He has published over 150 papers and has secured in excess of £12M in research funding to date.
 Hani Marcus Hani Marcus National Hospital for Neurology and Neurosurgery, University College London, UK  
 Hutan Ashrafian Hutan Ashrafian Imperial College Healthcare NHS Trust, London, UK Hutan Ashrafian is a Clinical Lecturer in Surgery. His research objectives are to develop innovative and technological strategies to resolve the global healthcare burden of obesity, metabolic syndrome, obesity-related cardiorespiratory disease, musculoskeletal dysfunction and cancer. His work encompasses clinical and mechanistic studies of metabolic bariatric surgery, complex biostatistical models, networks and evidence synthesis to guide policy decisions, computational physiology and systems medicine, novel health technology assessment and diagnostic accuracy of biomarkers, robotics and artificial intelligence agents in healthcare, ancient history analytics, academic impact & leadership metrics and regenerative strategies including sports-based and bio-inspired bionic therapies.
 Keno März Keno März

German Cancer Research Center, Germany Dr. Keno März received his Master Degree in 2013 and finished his PhD in 2018 with distinction from Heidelberg University. He conducted his postdoctoral studies at the Division Computer Assisted Medical Interventions (CAMI) at the German Cancer Research Center (DKFZ) under the lead of Professor Lena Maier-Hein, for whom he acts as a deputy. His studies focus on the field of surgical data science and heterogeneous data modeling, where he managed the OR4.1 project dealing with the translation of algorithms and applications into the clinical workflow and the complete assessment of data generated in the OR.
 Lourdes Agapito Lourdes Agapito University College London, UK Lourdes Agapito received her BSc in Physics and PhD in Computer Vision from the Universidad Complutense de Madrid in Spain in 1991 and 1996 respectively. She was an EU Marie Curie Postdoctoral Research Fellow with the Robotics Research Group at The University of Oxford from 1997 to 1999 and then held a Postdoctoral Fellowship funded by the Spanish Ministry of Science and Education in the same research group for a further 2 years. In September 2001 she joined Queen Mary, University of London as a Lecturer. In 2007 she was promoted to Senior Lecturer and in 2011 to Reader in Computer Vision. In 2008, she was awarded an ERC Starting Independent Researcher Grant to conduct research in 3D modelling of non-rigid scenes from video sequences. In July 2013 she joined the Computer Science Department at UCL where she leads her research team with 3 PhD students and 3 Postdocs. Her research in the area of 3D Computer Vision has consistently focused on the inference of 3D information from video. In November 2008, she was awarded an ERC Starting Independent Researcher Grant (HUMANIS) to focus on the problem of reconstructing 3D models which represent the full geometry of deforming and articulated objects, such as the human body, but in particular in acquiring them automatically and only from the stream of images acquired with a single conventional camera, rather than using multiple-camera setups, specialised sensors (such as depth cameras), prior knowledge about the objects to be reconstructed or training data – a purely data-driven approach.
 Pete Mountney Pete Mountney Odin Vision, UK Peter Mountney PhD. Peter’s research interests lie in the fields of machine learning and medical imaging. His research focuses on developing deep technology and translating it into applications. He carried out his PhD and post-doctoral work at Imperial College London before joining Siemens Healthineers. Working at Siemens for almost a decade, he led programmes of research, development and technology translation across a wide range of clinical applications. He was a Visiting Lecturer at Kings College London in the Department of Biomedical Engineering. He is a Royal Society Entrepreneur in Residence, a Royal Academy of Engineering Enterprise Fellow and CEO of Odin Vision.
  Sophie Camp Imperial College Healthcare NHS Trust, London, UK  
 Stamatia (Matina) Giannarou Stamatia (Matina) Giannarou Imperial College London, UK Stamatia (Matina) Giannarou received the MEng degree in Electrical and Computer Engineering from Democritus University of Thrace, Greece in 2003, the MSc degree in communications and signal processing and the Ph.D. degree in image processing from the department of Electrical and Electronic Engineering, Imperial College London, UK in 2004 and 2008, respectively. Currently she is a Royal Society University Research Fellow and a Lecturer in Surgical Cancer Technology and Imaging at the Hamlyn Centre for Robotic Surgery, Department of Surgery and Cancer, Imperial College London, UK. Her research focuses on enhanced surgical vision for intraoperative navigation in minimally invasive and robot-assisted operations. She received best paper awards at the “Rank Prize Symposium on Medical Imaging Meets Computer Vision 2013”, the MICCAI 2014 workshop on “Modeling and Monitoring of Computer Assisted Interventions” (M2CAI) and the 2016 International Conference on Information Processing in Computer-Assisted Interventions (IPCAI). Recently, she won “The President’s Award for Outstanding Early Career Researcher 2017” at Imperial College London. She has also been invited to present her work at a number of international workshops and symposia.  She is a regular reviewer for high impact journals and conferences in the fields of medical robotics, medical imaging and biomedical engineering and one of the main organisers of the annual Hamlyn Winter School on Surgical Imaging and Vision.
 Tom Vercauteren Tom Vercauteren King’s College London, UK Tom Vercauteren is Professor of Interventional Image Computing at King’s College London since 2018 where he holds the Medtronic / Royal Academy of Engineering Research Chair in Machine Learning for Computer-assisted Neurosurgery. From 2014 to 2018, he was Associate Professor at UCL where he acted as Deputy Director for the Wellcome / EPSRC Centre for Interventional and Surgical Sciences (2017-18). From 2004 to 2014, he worked for Mauna Kea Technologies, Paris where he led the research and development team designing image computing solutions for the company’s CE- marked and FDA-cleared optical biopsy device. His work is now used in hundreds of hospitals worldwide. He is a Columbia University and Ecole Polytechnique graduate and obtained his PhD from Inria in 2008. Tom is also an established open-source software supporter.
Summary of the table's contents