Reader in Engineering
Academic Division: Information Engineering
Research group: Machine Intelligence
Telephone: +44 1223 3 32750
Dr Gee's research involves the application of information engineering to topics in medical science and clinical practice. There are currently two main topics, one associated with imaging tissue stiffness using ultrasound, the other with investigating osteoporosis using CT.
A unifying theme is close collaboration with clinicians and the implementation of research tools in robust software that is suitable for use in clinical environments. Dr Gee is one of the authors of the Stradwin software suite, supporting ultrasound and CT research teams around the world.
Imaging tissue stiffness using ultrasound elastography, studying the femoral cortex using deconvolved CT and statistical parametric mapping.
Recently completed projects include elastography (EPSRC, Wellcome Trust), ultrasound deconvolution (EPSRC) and 3D ultrasound (EPSRC). Current projects, studying osteoporosis with CT, are sponsored by Eli Lilly and Amgen.
Chair of the Mathematics and Computing Subject Group, medical imaging, computer graphics, computer architecture, 4th year projects, Lego.
Director of Studies in Engineering, Queens' College
Andrew Gee obtained a BA in Electrical and Information Science at Cambridge University in 1990. He was awarded the PhD degree in 1993 from the same university for his thesis on the use of feedback neural networks for combinatorial optimization. In 1993 he was appointed to a Research Fellowship at Queens' College, Cambridge, where he started to work on computer vision. In October 1995 he became an Assistant Lecturer in Information Engineering and an Official Fellow of Queens' College, where he is now Director of Studies in Engineering. He was promoted to the post of Lecturer in January 1998, Senior Lecturer in October 2001 and Reader in October 2006. He teaches undergraduate courses in all aspects of computing: in 1998 he was awarded a Pilkington Prize by the Trustees of the Cambridge Foundation for excellence in teaching at the University of Cambridge. He has worked in a number of research areas, including medical imaging, computer vision, document image processing and neural networks. Currently, he is working on aspects of two- and three-dimensional ultrasound, elastography, and osseous cortical thickness estimation in CT. He has authored and co-authored around 180 papers.