Zoubin Ghahramani Professor of Information Engineering Department of Engineering University of Cambridge Associate Research Professor Machine Learning Department Carnegie Mellon University Adjunct Faculty Gatsby Computational Neuroscience Unit University College London

Machine Learning @ Cambridge Research Papers [New] [Older] Research Interests Former Students and Postdocs Contact Information CV and Short Bio

Students and Postdocs: Sebastien Bratieres John Cunningham Frederik Eaton Jurgen van Gael Katherine Heller David Knowles Alex Ksikes Simon Lacoste-Julien Shakir Mohamed Peter Orbanz Pedro Ortega Ed Snelson Richard E Turner Sinead Williamson Yue Wu

Memorial Site for my friend and colleague, Sam Roweis, 1972-2010

News

• 3/09: We are organising the 2009 Machine Learning Summer School in Cambridge

• 1/09: We win a Google Research Award for our work on large scale Bayesian methods

• 10/08: Karsten Borgwardt publishes an article featured on the front page of Nature on decoding the Malaria genome; read the news story in the University of Cambridge Newletter

• 9/08: Iain Murray's PhD Dissertation wins the 2007 Savage Award Honorable Mention for Bayesian Theory and Methods.

• 3/08: Video lectures of Machine Learning @ CUED Tutorials and of the Newton Institute day are now online.

• 1/08: Jurgen van Gael wins a Microsoft Research PhD Scholarship.

• 11/07: Two Postdoctoral Positions in Machine Learning available starting in 2008, funded by the EPSRC

• 11/07: Karsten Borgwardt's PhD thesis wins the Heinz Schwärtzel Dissertation Award on Foundations of Computer Science!

• 10/07: I am now Associate Editor-in-Chief of IEEE Transactions on Pattern Analysis and Machine Intelligence, currently the IEEE's most cited journal, and second most cited in all of Electrical Engineering.

• 10/07: Katherine Heller wins an EPSRC Postdoctoral Fellowship in Theoretical Computer Science!

• 10/07: We have launched the Cognitive Systems Engineering website

• 10/07: New PhD students: Finale Doshi, Jurgen van Gael, Shakir Mohamed

• 7/07: We have launched the Machine Learning @ Cambridge website!

• 7/07: Summary presentation, videos and full proceedings of the International Conference on Machine Learning are now available.

• 3/07: Dr Carl Edward Rasmussen joined the Department as a Lecturer in the Machine Learning Group!

• 2/07: I am serving as the Program Chair for the International Conference on Machine Learning (ICML 2007)

• 1/07: Advanced Tutorial Lecture Series on Machine Learning, Thursdays from 4pm-6pm, this term.

• 1/07: Machine Learning Reading Group @ CUED

• 1/07: See our: Online Image Retrieval and Annotation Demo

• 10/06: Microsoft Live Labs Research Award

• 9/06: I'm teaching a new course on Machine Learning (4F13), this Michaelmas term (Fall 2006) at Cambridge

• 9/06: New PhD students: Frederik Eaton, Pedro Ortega, and Sinead Williamson

Research Areas and Papers by Topic

For recent publications see the Machine Learning Group Publications Webpage

	Gaussian Processes		Clustering		Graphical Models
	Monte Carlo Methods		Semi-Supervised Learning		Non-parametric Bayesian Methods
	Approximate Inference		Bioinformatics		Information Retrieval
	Sensorimotor Control and Robotics		Time Series Models		Review Articles and Tutorials

Talks and Tutorials:

• Bayesian Hidden Markov Models and Extensions, invited talk at CoNLL 2010, Uppsala, Sweden.
• A Brief Overview of Nonparametric Bayesian Models presented at the NIPS 2009 Workshop on Nonparametric Bayesian Methods.
• The Indian Buffet Process and Extensions presented at the 7th Workshop on Bayesian Nonparametrics, Turin 2009.
• Video Lectures of the Machine Learning Summer School
• Video Lectures available online on Graphical Models, Bayesian Learning, and Non-parametric Bayesian methods.
• UAI 2005 Tutorial on Nonparametric Bayesian Methods
• ICML 2004 Tutorial on Bayesian Machine Learning
• NIPS 1999 Tutorial on Probabilistic Models for Unsupervised Learning
• An Old Talk on Bayesian Model Comparison

Teaching:

• Machine Learning (4F13), Lent, Cambridge
• Signal and Pattern Processing (3F3), Lent, Cambridge
• Image Searching and Modelling (Part IB, Paper 8), Cambridge
• Unsupervised Learning Course (GI02), Fall 2005, UCL
• Gatsby Machine Learning Qualifying Exam Topic List
• Statistical Approaches to Learning and Discovery, Spring 2002, CMU
• Old Course Websites

Conferences and Workshops:

• International Conference on Machine Learning (ICML 2007), Portland, Oregon
• Open Issues in Gaussian Processes for Machine Learning, NIPS Workshop, Vancouver, Dec 10, 2005
• The 10th International Workshop on Artificial Intelligence and Statistics, Barbados, Jan 6-8, 2005
• Workshop on Learning Theoretic and Bayesian Inductive Principles, London, July 19-21, 2004
• NIPS Conference

Other:

• Very Brief Introduction to Bayesian Machine Learning
• Software
• www.Variational-Bayes.org website
• Interested in a PhD in Machine Learning? Apply to the Engineering Department at the University of Cambridge.
• CV and Short Bio
• Miscellaneous

Academic Links:

• The Machine Learning @ Cambridge University website.
• My web page at the Machine Learning Department, Carnegie Mellon University
• Machine Learning Group at the Department of Computer Science, University College London
• Journal of Machine Learning Research
• Bayesian Analysis
• IEEE Transactions on Pattern Analysis and Machine Intelligence
• Machine Learning
• PASCAL Research Network
• Many other machine learning links

Contact Information:

Mail: Department of Engineering University of Cambridge Trumpington Street Cambridge CB2 1PZ, UK Office: 449

Tel: Office  +44 (0)1223 748 531 Fax     +44 (0)1223 332 662 Email: zoubin - at - eng.cam.ac.uk (replace -at- by @)

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