	Department of Engineering Computational and Biological Learning Lab

University of Cambridge > Department of Engineering > Information Engineering > Computational and Biological Learning Lab > Yunus Saatçi

Yunus Saatçi

Ph.D. Student
Department of Engineering
University of Cambridge, UK

Academic Biography

For my undergraduate studies I studied Computer Science at Cambridge University. After completing my undergraduate degree, I worked for one year as a research and teaching assistant under the supervision of Dr. Richard Gibbens. The research involved analysing M25 traffic data for the purposes of journey-time prediction. After the assistantship, I moved to Edinburgh University to pursue a Master's Degree in Informatics, focussing on the "Learning From Data" specialism. I was supervised by Dr. Amos Storkey. I am now a Ph.D. student back in Cambridge under the supervision of Dr. Carl Rasmussen. For further details please see my CV.

Research Interests

I am interested in machine learning methods as applied to nonstationary time series data. In particular, my research involves:

Bayesian Change-point Algorithms.
State Space Models and Switching State Space Models.
Bayesian inference for Point Processes.

Bayesian inference can be performed exactly for only the simplest cases. Hence, I am also interested in variational and MCMC methods for performing approximate inference for the cases above.

Publications

Saatci, Y. and Town, C.P. "Cascaded Classification of Gender and Facial Expressions using Active Appearance Models", Proc. International Conference on Automatic Face and Gesture Recognition, 2006 PDF
Gibbens, R.J. and Saatci, Y. "Data, Modelling and Inference in Road-traffic Networks", Royal Society Phil. Trans. A, 2008 PDF
Van Gael, J., Saatci, Y., Teh, Y.W., Ghahramani, Z. "Beam sampling for the Infinite Hidden Markov Model", International Conference on Machine Learning (ICML), 2008 PDF

Contact Information

Department of Engineering
Trumpington Street
Cambridge CB2 1PZ, UK
Room BE440
Phone: +44 (0) 122 374 851 2
Fax: +44 (0) 1 223 332 662
Mobile: +44 (0) 7817 322 150
Email: ys267 [AT] cam.ac.uk