Zoubin Ghahramani

Zoubin Ghahramani
File:Professor Zoubin Ghahramani FRS.jpg Zoubin Ghahramani in 2015, portrait from the Royal Society
Born	(1970-02-08) February 8, 1970 Iran
Residence	United Kingdom
Fields	Machine Learning Bayesian statistics
Institutions	University of Cambridge Carnegie Mellon University University College London University of Toronto
Alma mater	University of Pennsylvania Massachusetts Institute of Technology
Thesis	Computation and Psychophysics of Sensorimotor Integration (1995)
Doctoral advisor	Michael I. Jordan Tomaso Poggio
Doctoral students	Matthew Beal Shakir Mohamed Pedro Ortega Ryan Turner Jurgen Van Gael
Known for	Graphical models Variational Bayes Computational neuroscience
Notable awards	FRS (2015)
Website mlg.eng.cam.ac.uk/zoubin/

Zoubin Ghahramani FRS (born 8 February 1970) is an Iranian researcher and Professor of Information Engineering at the University of Cambridge. He holds joint appointments at Carnegie Mellon University and University College London.

Education

Ghahramani obtained his Ph.D from the Department of Brain and Cognitive Sciences at the Massachusetts Institute of Technology, under the supervision of Michael I. Jordan.

Research

Ghahramani has made significant contributions in the areas of Bayesian machine learning (particularly variational methods for approximate Bayesian inference), as well as graphical models and computational neuroscience.

Awards and honours

Ghahramani was elected Fellow of the Royal Society (FRS) in 2015. His certificate of election reads:

Zoubin Ghahramani is a world leader in the field of machine learning, significantly advancing the state-of-the-art in algorithms that can learn from data. He is known in particular for fundamental contributions to probabilistic modeling and Bayesian nonparametric approaches to machine learning systems, and to the development of approximate variational inference algorithms for scalable learning. He is one of the pioneers of semi-supervised learning methods, active learning algorithms, and sparse Gaussian processes. His development of novel infinite dimensional nonparametric models, such as the infinite latent feature model, has been highly influential.