Professor David Hogg

Profile

David Hogg is Professor of Artificial Intelligence at the University of Leeds. He is internationally recognized for his work on computer vision, particularly in the areas of video analysis and activity recognition. He works extensively across disciplinary boundaries, applying AI in engineering design, biology, medicine and environmental sciences. He has been a visiting professor at the MIT Media Lab, Pro-Vice-Chancellor for Research and Innovation at the University of Leeds (2011-2016), Chair of the ICT Strategic Advisory Team at the Engineering and Physical Sciences Research Council (EPSRC) in the UK, Chair of an international review panel for Robotics and Artificial Intelligence commissioned by EPSRC (2017), and a Turing Fellow. Until 2018, he was Chair of the Academic Advisory Group of the Worldwide Universities Network (WUN), helping to promote collaborative research between over 20 prominent research intensive universities from around the globe. He is Director of the UKRI Centre for Doctoral Training in AI for Medical Diagnosis and Care; and a Co-Director of the Northern Pathology Imaging Co-operative. David is a Fellow of the European Association for Artificial Intelligence (EurAI), a Distinguished Fellow of the British Machine Vision Association, and a Fellow of the International Association for Pattern Recognition.

David is Director of the Artificial Intelligence research theme in the School of Computing. At present, he is not taking on the supervision of new PhD students.

Responsibilities

• Director of Artificial Intelligence research theme
• Director of UKRI Centre for Doctoral Training in AI for Medical Diagnosis and Care

Research interests

David pioneered the use of three-dimensional geometric models for tracking flexible structures (e.g. the human body) in natural scenes, and contributed to establishing statistical approaches to learning of shape and motion as one of the pre-eminent paradigms in the field. Current research is on representation and learning of activities from video, specifically models of interaction, and applications of machine learning in science and engineering. Part of this work is exploring the integration of vision within a broader cognitive framework that includes audition, language, action, and reasoning.

Selected recent publications and project pages

Talking Head from Speech Audio using a Pre-trained Image Generator

Deep learning of Parkinson's movement from video, without human-defined measures

Mapping the extent of giant Antarctic icebergs with deep learning

3D shape reconstruction of semi-transparent worms

Self-supervised 3d human pose estimation from a single image

Mapping Antarctic crevasses and their evolution with deep learning applied to satellite radar imagery

Online perceptual learning and natural language acquisition for autonomous robots

Advancing spatial reasoning in large language models: An in-depth evaluation and enhancement using the stepgame benchmark

Understanding the robustness of skeleton-based action recognition under adversarial attack

Unsupervised human activity analysis for intelligent mobile robots

Selected recent projects

Nowcasting with Artificial Intelligence for African Rainfall: NAIAR (2024-2027)

Advanced Crystal Shape Descriptors for Precision Particulate Design, Characterisation and Processing (Shape4PPD) (2021-2024)

Forecasting volcanic activity using deep learning (DEEPVOLC) (2020-2026)

Towards intelligent engineering design systems (2019-2022)

Current PhD students

Caitlin Howarth
Claire Bartholomew
Mikael Down
Fangjun Li
Eilish O’Grady
Chen Jiang
Arpita Saggar

Project pages for some earlier research

A short talk on AI in the Public Sector

Qualifications

• BSc Applied Mathematics, Warwick, 1975
• MSc Computer Science, Western Ontario, 1976
• DPhil, Sussex, 1984

Professional memberships

• British Machine Vision Association (BMVA)
• The Society for the Study of Artificial Intelligence and the Simulation of Behaviour (AISB)
• International Association of Pattern Recognition (IAPR)

Research groups and institutes

• Artificial Intelligence