Machine Learning and Perception

The Machine Learning and Perception group is one of the major research groups at Microsoft Research Cambridge. Its research broadly aims at structure and exploiting structure in real-world data sets, with applications such as matchmaking in online gaming, intelligent image processing, web search and analysis of DNA data.

Research Areas

Computer Vision
Vision is the study of how computers can be programmed to understand and react to images and video. At Microsoft we take an approach that spans the range from theory to practice.

Information Retrieval
Understanding and improving Search – through theory, modelling, experimentation and implementation.

Machine Learning
Advancing the theory of machine learning along with provision of the corresponding tools for application ranging from processing of digital ink to analysis of DNA data.

Full-Time Staff

Primary Contacts:

Bishop, Chris	Blake, Andrew	Craswell, Nick	Criminisi, Antonio	Fitzgibbon, Andrew
Graepel, Thore	Guiver, John	Herbrich, Ralf	Kohli, Pushmeet	Le Roux, Nicolas
Lehrach, Wolfgang	Lempitsky, Victor	Minka, Tom	Quiñonero Candela, Joaquin	Robertson, Stephen
Rother, Carsten	Sharp, Toby	Shokouhi, Milad	Shotton, Jamie	Snelson, Ed
Stern, David	Svensén, Markus	Szummer, Martin	Taylor, Michael	Torresani, Lorenzo
von Billerbeck, Bodo	Winn, John	Yilmaz, Emine

Associated Members

Besides the full-time staff, a number of contractors, consultants, interns and collaborators from other parts of Microsoft also belong to the Machine Learning and Perception Group.

Jung, Kyomin	Iofciu, Tereza	Jost, Markus	Kannan, Anitha	Kolmogorov, Vladimir
Ormesher, Ian	Robertson, Duncan	Nguyen, Minh Hoai	Stegle, Oliver	Tan, Vincent
Yang, Zhirong	Yi, Zhao	Yin, Zhijun