Brief Bio
Ben Glocker is Professor in Machine Learning for Imaging at the Department of Computing at Imperial College London where he co-leads the Biomedical Image Analysis Group. He is the Kheiron Medical Technologies / Royal Academy of Engineering Research Chair in Safe Deployment of Medical Imaging AI. He also leads the HeartFlow-Imperial Research Team and is Head of ML Research at Kheiron. He is also the Knowledge Transfer Lead of the EPSRC Causality in Healthcare AI Hub. He holds a PhD from TU Munich and was a postdoc at Microsoft and a Research Fellow at the University of Cambridge. His research is at the intersection of medical imaging and artificial intelligence aiming to build safe and ethical computational tools for improving image-based detection and diagnosis of disease. He has received several awards including an Imperial President’s Medal for Excellence in Impact, Philips Impact Award, a Medical Image Analysis – MICCAI Best Paper Award, and the Francois Erbsmann Prize. He is a member of the Young Scientists Community of the World Economic Forum and a member of the AI Task Group of the UK National Screening Committee advising the Government on questions around clinical deployment of AI for screening programmes. He was awarded an ERC Starting Grant in 2017.
Academic & Industry Positions
Since 2022: Professor, Imperial College London, UK
Since 2021: Head of ML Research, Kheiron Medical Technologies, UK
2019-2022: Reader, Imperial College London, UK
Since 2018: Adviser, HeartFlow, UK
2019-2021: Visiting Researcher, Microsoft Research Cambridge, UK
2017-2019: Senior Lecturer, Imperial College London, UK
2013-2017: Lecturer, Imperial College London, UK
2010-2013: Postdoctoral Researcher, Microsoft Research Cambridge, UK
2010-2012: Research Fellow, Darwin College, University of Cambridge, UK
2006-2010: Research Assistant, Technische Universitaet Muenchen, Germany
2006-2010: Visiting Researcher, Ecole Centrale Paris, France
Awards & Honours
Imperial President’s Medal for Excellence in Impact 2024
Awarded for impact across healthcare policy, societal engagement, and more.
MICCAI MLCN Workshop Best Paper Award 2022
Awarded for our work Automatic lesion analysis of traumatic brain injury
MICCAI UNSURE Workshop Best Paper Award 2021
Awarded for our work Confidence-based Out-of-Distribution Detection
MICCAI DART Workshop Best Paper Award – Runner-Up 2021
Awarded for our work Transductive Image Segmentation
Imperial President’s Award for Outstanding Research Team 2019
Awarded to the BioMedIA Group
Philips Impact Award – MIDL 2018
Awarded for our work NeuroNet
Member of the World Economic Forum’s Young Scientists Community
Selected as “extraordinary scientist under the age of 40”
NVIDIA Global Impact Award – Honorable Mention 2016
Awarded for our work on brain lesion segmentation using deep learning
ERCIM Cor Baayen Award – Honorable Mention 2013
Awarded to promising young researchers in the field of Informatics and Applied Mathematics
Medical Image Analysis – MICCAI Best Paper Award 2013
Awarded for our work Neighbourhood Approximation using Randomized Forests
Werner von Siemens Excellence Award 2007
Awarded for the diploma thesis
Francois Erbsmann Prize 2007
Awarded for the best oral presentation among all first-time presenters at IPMI 2007
Computational Challenge Awards
Winner of the Multimodal Brain Tumor Segmentation Challenge (BraTS) 2017
Kamnitsas et al. Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation
Winner of the Ischemic Stroke Lesion Segmentation Challenge (ISLES) 2015
Kamnitsas et al. Multi-Scale 3D Convolutional Neural Networks for Lesion Segmentation in Brain MRI
Winner of the Automatic Intervertebral Disc Segmentation Challenge 2015
Lopez-Andrade and Glocker. Complementary Classification Forests with Graph-cut Refinement for Accurate Intervertebral Disc Localization and Segmentation
Special Award a.k.a. “Left Field Award” at the Workshop Challenge on Segmentation: Algorithms, Theory and Applications (SATA)
Zikic et al. Multi-Atlas Label Propagation with Atlas Encoding by Randomized Forests
Winner of the Multimodal Brain Tumor Segmentation Challenge (BraTS) 2012
Zikic et al. Context-sensitive Classification Forests for Segmentation of Brain Tumor Tissues
Professional Activities
Editorial Board
Elsevier’s Journal on Medical Image Analysis (2015-2024)
Elsevier’s Journal on Image and Vision Computing (2016-2018)
Steering Committee
WEF Young Scientists’ Code of Ethics
Scientific Lead
HeartFlow-Imperial Research Team
Scientific Advisor
Kheiron Medical Technologies
Definiens (2017 – 2019)
Knowledge Transfer Lead
EPSRC Hub for Causality in Healthcare AI
Conference Chair
International Conference on Medical Imaging with Deep Learning 2019
Program Chair
International Conference on Medical Image Computing and Computer Assisted Intervention 2024
Program Committee & Area Chair
ECR 2020 Imaging Informatics Scientific Subcommittee
MICCAI 2013/15/16, SPIE Medical Imaging 2015-18/20, WBIR 2014/20, ISVC Special Track 2009
Co-Organizer
Fairness of AI in Medical Imaging Workshop 2022
MICCAI 2020/23 Tutorials on Causality in Medical Image Computing
IPAM Workshop on Deep Learning and Medical Applications 2020
{U|I|K}CL Bio-Imaging Symposia
MICCAI 2018 Tutorial on Deep Learning for Medical Imaging
Workshop Medical Imaging meets NeurIPS 2017-20
British Machine Vision Conference 2017
MedIAN CodeFest 2017 – Medical Imaging Hackathon
International Workshop on Biomedical Image Registration 2016
BIH 2015 Symposium on Clinical Applications of Machine Learning in Neuroimaging
MICCAI Workshop & Challenge CSI 2014-16, mTOP 2016, MSKI 2017
ISBI 2015 Special Session on Graphical Models for Biomedical Image Analysis
MICCAI 2010 Tutorial on Intensity-based Deformable Registration
1st Russian-Bavarian Conference on Biomedical Engineering 2005
Departmental and College Activities
Champion for Public Engagement (2017 – 2020)
CRUK Imperial Centre Development Fund Committee
Affiliations
Cancer Research UK Early Detection & Diagnosis Research Committee
AI Task Group of the UK National Screening Committee
World Economic Forum’s Young Scientists Community
UKRI Centre for Doctoral Training in AI for Healthcare
EPSRC Centre for Doctoral Training in Smart Medical Imaging
Guest Editor
Medical Image Analysis Special Issue on Medical Imaging with Deep Learning 2019
Medical Image Analysis: Special Issue on Discrete Graphical Models in Biomedical Image Analysis
International Journal of Computer Vision: Special Issue BMVC 2017
Society Memberships
MICCAI Society, European Society of Medical Imaging Informatics, British Machine Vision Association, European Society of Radiology, Association for Computing Machinery
Journal & Conference Reviewer
IEEE T-PAMI, TMI, TIP, TBME, Springer Nature, IJCV, Elsevier MedIA, Brain, CVIU, IMAVIS, Annals of Biomedical Engineering, MICCAI, IPMI, NeurIPS, ICLR, CVPR, ICCV, ECCV, ISBI, SPIE
Funding Body Reviewer
European Research Council, Engineering and Physical Sciences Research Council (UK), The Wellcome Trust (UK), Technology Foundation STW (NL), Action Medical Research
Invited Talks, Lectures & Panels
MPEP 2024: AI in Imaging and Treatment Planning
Causal Considerations in Medical Imaging AI
Online, November 12, 2024
Converging on Cancer Seminar Series
Causal Considerations in Medical Imaging AI
Online, October 17, 2024
Westminster Health Forum
Safe deployment of medical imaging AI
Online, July 6, 2023
Conference on Health, Inference & Learning
Safe deployment of medical imaging AI
The Broad Institute, Cambridge, MA, June 22, 2023
AI & Data Science in Healthcare
Safe deployment of medical imaging AI
The Royal Society, London, June 20, 2023
Hamlyn Winter School on Surgical Imaging and Vision
Safety nets in medical imaging AI
London, November 18, 2022
MICCAI Workshop on Uncertainty for Safe Utilization of ML in Medical Imaging
Bias in Chest X-ray Disease Detection Models
Singapore, September 18, 2022
AI for Doctors Workshop
Safety nets for clinical deployment of medical imaging AI
Munich, June 24, 2022
CVPR Medical Computer Vision Workshop 2022
Safety nets in medical imaging AI
Hybrid, June 19, 2022
Responsible AI Seminar
Algorithmic encoding of protected characteristics
Online, March 30, 2022
The Alan Turing Institute – AI UK 2022
AI for early detection of diseases
Hybrid, March 23, 2022
STFC Cancer Diagnostic Network – Data Science Workshop
AI for image-based detection of disease
Online, October 5, 2021
MICCAI Workshop on Predictive Intelligence in Medicine
Deep Structural Causal Models for Counterfactual Inference
Online, October 1, 2021
Artificial Intelligence in Future Health & Care: Regulation, Evaluation & Policies
Safeguards in Medical Imaging AI
Online, September 21, 2021
MIUA 2021 Keynote
Towards Safer AI in Medical Imaging
Online, July 14, 2021
Pitt-CMU MLxMed Seminar
Towards Safer AI in Medical Imaging
Online, June 23, 2021
DoC Public Lecture Series
Spot the Lesion
London (online), May 27, 2021
Hamlyn Winter School
Causality in Medical Imaging
London (online), December 2, 2020
Artificial Intelligence in MRI
AI in Radiology: The Story Behind the Data
Virtual IPEM Workshop, November 18, 2020
MICCAI Workshop on Domain Adaptation and Representation Transfer
The Quest for Robust Machine Learning
Virtual MICCAI conference, October 8, 2020
Artificial Intelligence in Clinical Medical Imaging
AI in Radiology: The Story Behind the Data
sitem-insel (online), Bern, Switzerland, September 3, 2020
ECR 2020: Artificial intelligence in radiology: the basics you need to know
Training data for deep learning: what is needed?
Online, July 15, 2020
Data Science Seminar | heidelberg.ai
Uncertainty, causality and generalization: Attempts to improve predictive modelling
DKFZ (online), Heidelberg, Germany, July 8, 2020
BL.MIA Seminar Series
Uncertainty, causality and generalization: Attempts to improve predictive modelling
MIT CSAIL (online), Boston, USA, June 18, 2020
ELLIS Health Workshop
Causal considerations for machine learning in medical imaging
Online, June 16, 2020
ESR Connect – Reasons to do AI with Friends
Episode 6 – The one with whole body MRI
Broadley Studios, London, UK, Feb 19, 2020
Machine Learning in Medicine: Virtual Seminar Series
Causality Matters in Medical Imaging
Cornell (online), New York, USA, Feb 14, 2020
IPAM Workshop: Deep Learning and Medical Applications
Causality Matters in Medical Imaging
UCLA, Los Angeles, USA, Jan 30, 2020
BIR/RCR Meeting: AI in Radiology in 2020
Good and bad data in machine learning for imaging
Cavendish Conference Centre, London, Jan 23, 2020
Machine Learning for Translational Medicine & Personalized Healthcare
Spot-the-Lesion: Image- based disease detection with deep learning
ITMAT Annual Workshop, Hammersmith Hospital, London, Sep 19, 2019
Horizon Europe: New Parliament, new Commission, new agenda
Value-based healthcare: How technologies can improve care across the EU
Science | Business, Brussels, Belgium, Sep 10, 2019
ConISyM – Converging Imaging and Systems Medicine
Machine Learning for Imaging
Castle Ringberg, Germany, May 23, 2019
East Anglian Radiological Society Annual Meeting (EARS)
Hopes and Hurdles for AI in Radiology
St. Catharine’s College, University of Cambridge, UK, March 20, 2019
European Commission Expert Group on Liability and New Technologies
Artificial Intelligence in Healthcare
European Commission, Brussels, Belgium, November 27, 2018
Artificial Intelligence and Machine Learning in Clinical Imaging Research
Machine Intelligence in Clinical Imaging
Alan Turing Institute, London, UK, November 6, 2018
BIR Annual Congress
Machine Learning in Medical Imaging
ETC Venues St. Paul’s, London, UK, November 2, 2018
Imperial Global Science Policy Forum
AI in Medical Imaging
Imperial College London, UK, October 30, 2018
Deep Learning in Healthcare Summit
Deep Learning in Medical Imaging: Beyond Human-level Performance
ETC Venues 155 Bishopsgate London, UK, September 21, 2018
ISMRM 2018: Machine Learning for Magnetic Resonance in Medicine
Deep Learning for MR Image Analysis
Paris expo Porte de Versailles, Paris, June 20, 2018
ECR 2018: Artificial intelligence and radiology: a perfect match?
Deep learning for fully automatic segmentation of normal and pathological structures in medical images
Austria Center Vienna, Austria, March 1, 2018
ECR 2018: Artificial intelligence: a strategic view
Machine learning for analysing medical images
Austria Center Vienna, Austria, March 1, 2018
Emerging Technologies in Medicine: Artificial Intelligence and Robotics
Can we build a machine capable of interpreting medical scans with super-human performance?
Universitaets-Klinik Essen, Germany, February 16, 2018
EuSoMII Academy 2017: Game Changers in Radiology
Unlocking patterns in medical images with AI
Erasmus MC, Rotterdam, Netherlands, November 18, 2017
BMVA Symposium: Computer Vision in Cancer
Brain Tumour Segmentation with Deep Neural Nets
British Computer Society, London, UK, October 11, 2017
Deep Learning in Healthcare Summit
Deep Learning in Medical Imaging – Successes and Challenges
LSO St Luke’s, London, UK, February 28, 2017
Medical Computer Vision: Algorithms for Big Data
Deep Learning for Brain Lesion Segmentation
MICCAI Workshop Invited Talk, Athens, Greece, October 21, 2016
Bayesian and Graphical Models for Biomedical Imaging – BAMBI
Solving Continuous Problems with Discrete Optimization
MICCAI Workshop Keynote, Athens, Greece, October 21, 2016
Medical Imaging Summer School – MISS
Medical Imaging meets Machine Learning
Favignana, Sicily, Italy, July 31 – Aug 6, 2016
UCL Medical Image Computing Summer School
CMIC, London, UK, July 22, 2016
Girls’ Engineering Summer School
Computer Science in Medical Imaging
Imperial College London, UK, July 19/20, 2016
World Economic Forum IdeasLab
Unlocking Patterns in Medical Images with Artificial Intelligence
WEF Annual Meeting of the New Champions, Tianjin, China, June 26, 2016
Deep Learning in Healthcare Summit
Deep Learning for Semantic Understanding of Medical Images
LSO St Luke’s, London, UK, April 7, 2016
Academy of Medical Sciences
Machine Learning for Complex Data Analyses
London, UK, March 14, 2016
Big Data, Multimodality & Dynamic Models in Biomedical Imaging
Machine Learning for Medical Image Analysis
Isaac Newton Institute, Cambridge, UK, March 9, 2016
Royal College of Radiologists
Machine Learning Event
London, UK, January 7, 2016
Alan Turing Institute: Scientific Scoping Workshop
Big data in medical imaging: passing fad or paradigm shift
British Library, London, UK, December 7, 2015
UCL Medical Image Computing Summer School
Random Forests in Medical Image Analysis
CMIC, London, UK, August 10, 2015
Girls’ Engineering Summer School
Medical Augmented Reality
Imperial College London, UK, July 23, 2015
Launch Event: Imperial’s Clinical Imaging Facility and the Biological Imaging Centre
Semantic Imaging: Machine Learning in Medical Image Analysis
Wolfson Education Centre, Hammersmith Campus, London, UK, July 16, 2015
1st ICML Workshop on Machine Learning meets Medical Imaging
Lille, France, July 11, 2015
3rd Biomedical Image Analysis Summer School
Random Forests in Medical Image Analysis
Institut Henri Poincaré, Paris, France, July 6-10, 2015
CSAIL Biomedical Imaging and Analysis Seminar Series
Learning to Understand Medical Images
MIT, Boston, USA, September 12, 2014
London Critical Care Data Marathon
Semantic Imaging – Learning to Understand Medical Images
IDEALondon, London, UK, September 6, 2014
The Rank Prize Funds Symposium on Medical Imaging Meets Computer Vision
Neighbourhood Approximation Forests
Grasmere, Lake District, UK, March 18, 2013
Darwin College Sciences Group
Medical Image Computing – The role of computer science in clinical routine
University of Cambridge, UK, November 11, 2010
Patents
Modelling a Three-Dimensional Space
T. Whelan, R.F. Salas Moreno, S. Leutenegger, A. Davison, B. Glocker
Pub. No. US2018082435
Tracking using Sensor Data
A. Guzman-Rivera, P. Kohli, B. Glocker, J. Shotton, S. Izadi, T. Sharp, A. Fitzgibbon
Pub. No. US2015347846
Camera/Object Pose from Predicted Coordinates
J. Shotton, B. Glocker, C. Zach, S. Izadi, A. Criminisi, A. Fitzgibbon
Pub. No. US2014241617
Method for Combining Images and Magnetic Resonance Scanner
B. Glocker, N. Navab, C. Wachinger, J. Zeltner
Pub. No. US2010067762
System and Method for Dense Image Registration using Markov Random Fields and Efficient Linear Programming
N. Paragios, B. Glocker, N. Komodakis
Pub. No. US2009046951