Misplaced Pages

Christopher K. I. Williams

Article snapshot taken from Wikipedia with creative commons attribution-sharealike license. Give it a read and then ask your questions in the chat. We can research this topic together.
This article is an autobiography or has been extensively edited by the subject or by someone connected to the subject. It may need editing to conform to Misplaced Pages's neutral point of view policy. There may be relevant discussion on the talk page. (September 2024) (Learn how and when to remove this message)
Professor of computer science

Christopher K. I. Williams
Born1960 (age 63–64)
NationalityBritish
Alma mater
Known forGaussian processes
AwardsFRSE (2021)
Scientific career
FieldsMachine learning, Computer vision
Institutions
Thesis Combining deformable models and neural networks for handprinted digit recognition  (1994)
Doctoral advisorGeoffrey Hinton
Websitehomepages.inf.ed.ac.uk/ckiw/ Edit this at Wikidata

Christopher Kenneth Ingle Williams (born 1960) is a professor at the School of Informatics, University of Edinburgh, working in Artificial intelligence, and particularly the areas of Machine learning and Computer vision.

Education

Williams received a BA in Physics and Theoretical Physics from the University of Cambridge in 1982, followed by Part III Mathematics (1983). He did a MSc in Water Resources at the University of Newcastle-Upon-Tyne, then worked in Lesotho on low-cost sanitation. In 1988, he studied at the Department of Computer Science of the University of Toronto under the supervision of Geoffrey Hinton. He obtained his MSc and PhD both in computer science, in 1990 and 1994, respectively.

Career and research

In 1994, Williams moved to Aston University as a Research Fellow. He became a Lecturer in August 1995. He moved to the University of Edinburgh in July 1998 and became Reader in 2000. He obtained a Personal Chair in Machine Learning in 2005 in the School of Informatics.

Williams has been a Fellow of the European Laboratory for Learning and Intelligent Systems (ELLIS) since 2019.

Williams' research interests are in machine learning and computer vision. He has worked on new models for understanding time-series and images, and for finding structure in data. He is best known for his work on Gaussian processes and for the book Gaussian Processes for Machine Learning, co-authored with Carl Rasmussen. The book received the 2009 DeGroot Prize of the International Society for Bayesian Analysis.

Williams was an organizer of the PASCAL Visual Object Classes (VOC) project (2005–2012) along with Mark Everingham, Luc van Gool, John Winn, and Andrew Zisserman.

Awards and honours

In 2021 Williams was elected a Fellow of the Royal Society of Edinburgh (FRSE).

References

  1. ^ "Christopher Williams". University of Edinburgh Research Explorer. Retrieved 5 January 2024.
  2. Williams, Chris. "Fellows". European Lab for Learning & Intelligent Systems. Retrieved 22 December 2023.
  3. Rasmussen, Carl Edward; Williams, Christopher K. I. (23 November 2005). Gaussian Processes for Machine Learning. The MIT Press. doi:10.7551/mitpress/3206.001.0001. ISBN 978-0-262-25683-4.
  4. "DeGroot Prize | International Society for Bayesian Analysis". Retrieved 22 December 2023.
  5. "The PASCAL Visual Object Classes Homepage". host.robots.ox.ac.uk. Retrieved 22 December 2023.
  6. Everingham, Mark; Van Gool, Luc; Williams, Christopher K. I.; Winn, John; Zisserman, Andrew (1 June 2010). "The Pascal Visual Object Classes (VOC) Challenge". International Journal of Computer Vision. 88 (2): 303–338. doi:10.1007/s11263-009-0275-4. hdl:20.500.11820/88a29de3-6220-442b-ab2d-284210cf72d6. ISSN 1573-1405.
  7. Everingham, Mark; Eslami, S. M. Ali; Van Gool, Luc; Williams, Christopher K. I.; Winn, John; Zisserman, Andrew (1 January 2015). "The Pascal Visual Object Classes Challenge: A Retrospective". International Journal of Computer Vision. 111 (1): 98–136. doi:10.1007/s11263-014-0733-5. hdl:20.500.11820/bb32678e-cd9b-4bc2-96dd-558806cda288. ISSN 1573-1405. S2CID 207252270.
  8. "Professor Christopher Williams". Royal Society of Edinburgh. Retrieved 22 December 2023.

External links

Categories: