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Greg Slabaugh
Has grant
Professor of Computer Vision and AI; Director, Digital Environment Research Institute
Research Interests
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About
Greg Slabaugh is a Professor and Director of the Digital Environment Research Institute (DERI) at Queen Mary University of London. His research encompasses deep learning applications in medical imaging, particularly in liver lesion segmentation and classification, as well as advancements in image processing and video quality enhancement. His recent contributions include work on personalized cardiac computational modeling and innovative algorithms for image restoration and super-resolution.
Recent Grants
Grant: Open
Enabling better use of digital tools and AI approaches for better health
Open Date: 2027-09-01
Close Date: 2034-09-01
Grant: Open
Advanced AI for Multimodal Spatial Biology
Open Date: 2026-09-01
Close Date: 2032-08-01
Grant: Open
Addressing Socio-technical Limitations of LLMs for Medical and Social Computing
Open Date: 2024-05-01
Close Date: 2028-03-01
Grant: Open
Multimodal AI for Multi omics Data Integration
Open Date: 2023-09-30
Close Date: 2027-09-29
Grant: Close
Developing Spatially Resolved Molecular Drug-Repurposing Assays for Treating Age-Related Frailty
Open Date: 2023-09-29
Close Date: 2025-10-29
Positions (1)
Greg Slabaugh
Queen Mary University of London
1 month ago
Queen Mary University of London is recruiting two Postdoctoral Research Associates to join research at the intersection of AI, computational modelling, cardiovascular medicine, and digital twins . The two openings are: • Computational Modelling for Cardiovascular Digital Twins • Machine Learning for Cardiovascular Digital Twins The roles sit within the Digital Environment Research Institute (DERI) and involve close collaboration across Queen Mary University of London and Barts Health NHS Trust . The research focuses on patient-specific cardiovascular digital twins , combining machine learning , mechanistic modelling , and clinical cardiology . Eligibility highlights: for the computational modelling role, experience in computational fluid dynamics and simulation is essential; for the machine learning role, experience in machine learning and deep learning is required. A strong track record in research is essential for both posts. The closing date is 11 October 2026 . The post says the job ads are linked in the comments, so interested candidates should follow the advertised application route there.
1 month ago
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Collaborators (22)
Luca Rossi
Assistant Professor
The Hong Kong Polytechnic University
Steven Niederer
reader
King’s College London
Devis Di Tommaso
Reader
Queen Mary University of London
Simon Lucas
Queen Mary University of London
Mohammed Y Khanji
-
Christopher R. S. Banerji
The Alan Turing Institute
Nay Aung
Clinical Senior Lecturer and Consultant Cardiologist
Queen Mary University of London
Patricia Munroe
Professor of Molecular Medicine
Queen Mary University of London
Manh Thang Hoang
Teaching Assistant
Hanyang University College of Medicine
Ahmed M Salih
Senior Research Associate
University of Leicester
Rachel Crespo Otero
Associate Professor
University College London
Steffen E Petersen
Professor of Cardiovascular Medicine
Queen Mary University of London
Qianni Zhang
Queen Mary University of London
Xavier L. Griffin
Chair Bone and Joint Health
Queen Mary University of London
Caroline Roney
Reader in Computational Medicine
Queen Mary University of London
Aleš Leonardis
Professor
University of Birmingham
Robert Smillie
Chief Medical Information Officer
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Cristobal Rodero
Research Associate
Imperial College London
Stefaan Verbruggen
Lecturer in Medical Technology
Queen Mary University of London
Wahbi El-Bouri
Senior Lecturer
University of Liverpool
Marc Masana Castrillo
Graz University of Technology (90000)
Anthony Mathur
Professor & Centre Lead
Queen Mary University of London
Make your next move.
Prepare your application
Review drafts before you send them.