Prof. David Hogg

Prof. David Hogg

Position: Professor of Artificial Intelligence
 
Areas of expertise: computer vision; machine learning
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, and Chair of an international review panel for Robotics and Artificial Intelligence commissioned by EPSRC (2017). 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, a Fellow of the International Association for Pattern Recognition, and a Turing Fellow.
 
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.
 
David is Director of the Artificial Intelligence research theme in the School of Computing, and Lab Director of the Computer Vision group.
 
Qualifications
BSc Applied Mathematics, Warwick, 1975
MSc Computer Science, Western Ontario, 1976
DPhil, Sussex, 1984
Professional memberships
IEEE Computer Society
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)
Student education
I teach in the School of Computing in the general areas of Artificial Intelligence, Machine Learning and Computer Vision.
 
Research groups and institutes
Artificial Intelligence

Contact Details

  • E-mail:
  • Address
    E C Stoner Building
  • City
    Leeds
  • State or Province
    West Yorkshire
  • Zip Code
    LS2 9JT
  • Country
    United Kingdom