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Prof Daniel Alexander
Department of Computer Science, UCL
Gower Street
  • Professor of Imaging Science
  • Dept of Computer Science
  • Faculty of Engineering Science
I work within the Centre for Medical Image Computing (CMIC) and the Vision and Imaging Sciences group in the Computer Science Department at UCL, where I lead the Microstructure Imaging Groupas well as development and maintenance of the Camino diffusion MRI toolkit. My core expertise is in computer science, computational modelling, parameter estimation, and imaging science. My first degree was a BA in Mathematics from Oxford completing in 1993. I then studied for MSc and PhD in Computer Science at UCL, completing in 1997. After a post-doc at the University of Pennsylvania, I returned to UCL as a lecturer in 2000 and I have been Professor of Imaging Science since 2009. More details here.
Research Summary

My research focusses on computational modelling and optimization for biomedical imaging and image analysis. The work involves both ends of the imaging pipeline: designing novel imaging techniques with sensitivity to new image features, and extracting new information from existing images. My background is in mathematics and computer science and I draw on ideas from medical imaging, computer vision, image processing and machine learning to construct models at various scales from tissue microstructure, through image regions or organs, to whole patient cohorts. Imaging data informs these models, so allows us to estimate their parameters and reveal new information about tissue, organs, patients or popluations.

For example, my EPSRC fellowship project works towards non-invasive histology, which aims to estimate using MRI features of tissue microstructure, such as cell size, shape and packing density, that traditionally require invasive biopsy and microscopy. Key applications are in brain connectivity mapping, white matter diseases like multiple sclerosis, and tumour-grading and treatment-planning for cancer. At the other end of the scale, my work on progression modelling aims to learn the progression pattern of particular diseases, ie the characteristic order in which symptoms and pathologies arise, using cross-sectional image databases from whole cohorts of patients. So far the work has focussed on neurodegenerative diseases, such as Alzheimer's disease and other dementias.

Teaching Summary

Currently, I am teaching an advanced MSc course on Computational Modelling for Biomedical Imaging. Previously, I have designed and delivered lecture courses on computer programming, data structures, image processing, computer vision, and research methods.  I was director for the advanced MSc in Vision Imaging and Virtual Environments (VIVE), now renamed MSc Computer Graphics Vision and Imaging (CGVI), in the computer science department from 2005-2008.  I have supervised around 75 undergraduate and MSc research projects and around 15 PhD projects (some on-going).

Academic Background
1997 PhD Doctor of Philosophy – Computer Science University College London
1994 MSc Master of Science – Computer Science University College London
1993 BA Bachelor of Arts – Mathematics University of Oxford
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