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 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 a 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

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
Elsevier’s Journal on Image and Vision Computing

Steering Committee
WEF Young Scientists’ Code of Ethics

Scientific Lead
HeartFlow-Imperial Research Team

Scientific Advisor
Kheiron Medical Technologies
Definiens (2017 – 2019)

Conference Chair
International Conference on Medical Imaging with Deep Learning 2019

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

Fairness of AI in Medical Imaging Workshop 2022
MICCAI 2020 Tutorial 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

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
EPSRC Centre for Doctoral Training in Neurotechnology for Life and Health

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

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


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