Christopher Bishop | |
---|---|
Born | [1] | April 7, 1959
Residence | Cambridge, UK |
Fields | Machine learning Neural networks Pattern recognition Natural language processing |
Institutions | University of Oxford Culham Centre for Fusion Energy AEA Technology Aston University University of Edinburgh Microsoft Research Royal Institution |
Alma mater | St Catherine's College, Oxford University of Edinburgh |
Thesis | The semi-classical technique in field theory: some applications (1983) |
Doctoral advisor | David Wallace Peter Higgs[2] |
Doctoral students | Neil Lawrence[3] |
Known for | Royal Institution Christmas Lectures (2008)[4] |
Notable awards | Fellow of the Royal Academy of Engineering (2004) Fellow of the Royal Society of Edinburgh (2007) |
Website research |
Christopher Michael Bishop (born 7 April 1959) FREng, FRSE, is a Distinguished Scientist at Microsoft Research Ltd in Cambridge where he leads the Machine Learning and Perception group. He also holds a Chair of Computer Science at the University of Edinburgh.
Education[edit]
Bishop was educated at Earlham School in Norwich then went to study for a Bachelor of Arts degree in Physics at St Catherine's College, Oxford, graduating in 1980. He then went on to the University of Edinburgh for a PhD in Theoretical Physics supervised by Peter Higgs and David Wallace.[2][5]
Research[edit]
Bishops research interests include machine learning,[6] neural networks, pattern recognition[7] and natural language processing and their applications.[8][9][10][11][12][13]
Career[edit]
Bishop was a research scientist at the Culham Centre for Fusion Energy from 1983 to 1993[1] and a Professor of Computer Science at Aston University from 1993 to 1997.[1] He has been a Professor at Edinburgh since 1997.
References[edit]
- ^ a b c "‘BISHOP, Prof. Christopher Michael’, Who's Who 2013, A & C Black, an imprint of Bloomsbury Publishing plc, 2013; online edn, Oxford University Press".(subscription required)
- ^ a b Christopher Bishop at the Mathematics Genealogy Project
- ^ Lawrence, Neil (2001). Variational inference in probabilistic models (PhD thesis). University of Cambridge.
- ^ "Christmas Lectures 2008 - Hi-tech Trek by Christopher Bishop".
- ^ Bishop, Christohper (1983). The semi-classical technique in field theory: some applications (PhD thesis). University of Edinburgh.
- ^ Bishop, Christopher (2006). Pattern recognition and machine learning. Berlin: Springer. ISBN 0-387-31073-8.
- ^ Bishop, Christopher (1995). Neural networks for pattern recognition. Oxford: Clarendon Press. ISBN 0-19-853864-2.
- ^ List of publications from Microsoft Academic Search
- ^ http://scholar.google.com/scholar?q=christopher+bishop
- ^ List of publications from the DBLP Bibliography Server
- ^ Tipping, M. E.; Bishop, C. M. (1999). "Probabilistic Principal Component Analysis". Journal of the Royal Statistical Society: Series B (Statistical Methodology) 61 (3): 611. doi:10.1111/1467-9868.00196.
- ^ Bishop, C. M.; Svensén, M.; Williams, C. K. I. (1998). "GTM: The Generative Topographic Mapping". Neural Computation 10: 215. doi:10.1162/089976698300017953.
- ^ Tipping, M. E.; Bishop, C. M. (1999). "Mixtures of Probabilistic Principal Component Analyzers". Neural Computation 11 (2): 443–482. doi:10.1162/089976699300016728. PMID 9950739.