Imperial College London

Dr Ben Glocker

Faculty of EngineeringDepartment of Computing

Reader in Machine Learning for Imaging
 
 
 
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Contact

 

+44 (0)20 7594 8334b.glocker Website CV

 
 
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Location

 

377Huxley BuildingSouth Kensington Campus

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Summary

 

Overview

Ben Glocker is Reader in Machine Learning for Imaging at the Department of Computing at Imperial College London where he co-leads the Biomedical Image Analysis Group with more than 45 research staff. He also leads the HeartFlow-Imperial Research Team and is scientific advisor for Kheiron Medical Technologies and a Visiting Researcher at Microsoft Research Cambridge. 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 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.

Guest Lectures

Towards Safer AI in Medical Imaging, MIUA 2021 Keynote, Online, 2021

Towards Safer AI in Medical Imaging, Pitt-CMU MLxMed Seminar, Online, 2021

Causality in Medical Imaging, Hamlyn Winter School, London (online), 2020

AI in Radiology: The Story Behind the Data, Artificial Intelligence in MRI, Virtual IPEM Workshop, 2020

The Quest for Robust Machine Learning, MICCAI Workshop on Domain Adaptation and Representation Transfer, Virtual MICCAI conference, 2020

AI in Radiology: The Story Behind the Data, Artificial Intelligence in Clinical Medical Imaging, sitem-insel, Bern, Switzerland, 2020

Training data for deep learning: what is needed?, ECR 2020: Artificial intelligence in radiology: the basics you need to know, Online, 2020

Uncertainty, causality and generalization: Attempts to improve predictive modelling, Data Science Seminar | heidelberg.ai, DKFZ, Heidelberg, Germany (online), 2020

Uncertainty, causality and generalization: Attempts to improve predictive modelling, BL.MIA Seminar Series, MIT CSAIL (online), 2020

Causal considerations for machine learning in medical imaging, ELLIS Health Workshop, Online, 2020

Episode 6 - The one with whole body MRI, ESR Connect – Reasons to do AI with Friends, Broadley Studios, London, UK, 2020

Causality Matters in Medical Imaging, Machine Learning in Medicine: Virtual Seminar Series, Cornell, New York, USA, 2020

Causality Matters in Medical Imaging, IPAM Workshop: Deep Learning and Medical Applications, UCLA, Los Angeles, USA, 2020

Good and bad data in machine learning for imaging, BIR/RCR Meeting: AI in Radiology 2020, Cavendish Conference Centre, London, 2020

Spot-the-Lesion: Image- based disease detection with deep learning, Machine Learning for Translational Medicine & Personalized Healthcare, ITMAT Annual Workshop, Hammersmith Hospital, London, 2019

Value-based healthcare: How technologies can improve care across the EU, Horizon Europe: New Parliament, new Commission, new agenda, Science | Business, Brussels, Belgium, 2019

Machine Learning for Imaging, ConISyM – Converging Imaging and Systems Medicine, Castle Ringberg, Germany, 2019

Hopes and Hurdles for AI in Radiology, East Anglian Radiological Society Annual Meeting (EARS), St. Catharine’s College, University of Cambridge, UK, 2019

Artificial Intelligence in Healthcare, European Commission Expert Group on Liability and New Technologies, European Commission, Brussels, Belgium, November 27, 2018

Machine Intelligence in Clinical Imaging, Artificial Intelligence and Machine Learning in Clinical Imaging Research: Progress and Promise, Alan Turing Institute, London, Uk, 2018

Machine Learning in Medical Imaging, BIR Annual Congress, ETC Venues St. Paul's, London, UK, 2018

AI in Medical Imaging, Imperial Global Science Policy Forum, Imperial College London, 2018

Deep Learning in Medical Imaging: Beyond Human-level Performance, Deep Learning in Healthcare Summit, Deep Learning in Healthcare Summit, 2018

Deep Learning for MR Image Analysis, ISMRM 2018: Machine Learning for Magnetic Resonance in Medicine, Paris expo Porte de Versailles, Paris, 2018

Machine learning for analysing medical images, ECR 2018: Artificial intelligence: a strategic view, Austria Center Vienna, Austria, 2018

Deep learning for fully automatic segmentation of normal and pathological structures in medical images, ECR 2018: Artificial intelligence and radiology: a perfect match?, Austria Center Vienna, Austria, 2018

Can we build a machine capable of interpreting medical scans with super-human performance?, Emerging Technologies in Medicine: Artificial Intelligence and Robotics, Universitaets-Klinik Essen, 2018

Unlocking patterns in medical images with AI, EuSoMII Academy 2017: Game Changers in Radiology, Erasmus MC, Rotterdam, Netherlands, 2017

Brain Tumour Segmentation with Deep Neural Nets, BMVA Symposium: Computer Vision in Cancer, British Computer Society, London, UK, 2017

Deep Learning in Medical Imaging – Successes and Challenges, Deep Learning in Healthcare Summit, LSO St Luke’s, London, 2017

Deep Learning for Brain Lesion Segmentation, Medical Computer Vision: Algorithms for Big Data, MICCAI Workshop, Athens, Greece, 2016

Solving Continuous Problems with Discrete Optimization, Bayesian and Graphical Models for Biomedical Imaging (BAMBI) 2016, MICCAI Workshop, Athens, Greece, 2016

Medical Imaging meets Machine Learning, Medical Imaging Summer School – MISS, Favignana, Sicily, Italy, 2016

UCL Medical Image Computing Summer School, CMIC, London, UK, 2016

Computer Science in Medical Imaging, Girls’ Engineering Summer School, Imperial College London, 2016

Unlocking Patterns in Medical Images with Artificial Intelligence, World Economic Forum IdeasLab, WEF Annual Meeting of the New Champions, Tianjin, China, 2016

Deep Learning for Semantic Understanding of Medical Images, Deep Learning in Healthcare Summit, LSO St Luke’s, London, 2016

Machine Learning for Complex Data Analyses, Academy of Medical Sciences, London, UK, 2016

Big Data, Multimodality & Dynamic Models in Biomedical Imaging, Turing Gateway to Mathematics, Isaac Newton Institute, Cambridge, UK, 2016

Machine Learning Event, Royal College of Radiologists, London, UK, 2016

Big data in medical imaging: passing fad or paradigm shift, Alan Turing Institute, British Library, London, UK, 2015

UCL Medical Image Computing Summer School, CMIC, University College London, London, UK, 2015

Medical Augmented Reality, Girls' Engineering Summer School, Imperial College London, 2015

Launch Event: Imperial's Clinical Imaging Facility and the Biological Imaging Centre, Imperial College, Wolfson Education Centre, Hammersmith Campus, London, UK, 2015

1st ICML Workshop on Machine Learning meets Medical Imaging, International Conference on Machine Learning, Lille, France, 2015

3rd Biomedical Image Analysis Summer School, Institut Henri Poincaré, Paris, France, 2015

CSAIL Biomedical Imaging and Analysis Seminar Series, MIT, Boston, USA, 2014

London Critical Care Data Marathon, London, UK, 2014

The Rank Prize Funds Symposium on Medical Imaging Meets Computer Vision, Grasmere, Lake District, UK, 2014

Darwin College Sciences Group, University of Cambridge, Cambridge, UK, 2010