Data Science

Timo Koski

Ph.D., Professor of Mathematical Statistics, KTH Royal Institute of Technology, Stockholm

Faculty Profile

Ph.D at Abo Akademi University in Finland. Teaching & research positions in Sweden: at Lulea University of Technology, Linkoping University, KTH Royal Institute of Technology (current position). Visiting researcher at University of North Carolina at Chapel Hill, Louisiana State University at Baton Rouge, UTIA of Czech Academy of Sciences, University of Warsaw, Institute of Advanced Study at Aalto University, Visiting lecturer and researcher at University of Helsinki, University of Turku, University of Makerere. Author (co-author) of three monographs.

Has worked in signal processing, biomathematics and genetics groups.

Experience

Jul 2007 – Present
Full Professor of Mathematical Statistics
Department of Mathematics at KTH Royal Institute of Technology
Jul 2000 – Jun 2007
Full Professor of Mathematical Statistics & Group Leader
Department of Mathematics at Linköpning Institute of Technology (LiTH) / Linköping University
Dec 1999 – Dec 2000
Professor of Mathematical Statistics
Department of Mathematics at Royal Institute of Technology (KTH)
1995 – 1999 | Stockholm
Senior Lecturer
Department of Mathematics at KTH Royal Institute of Technology

Honors & Awards

The Swedish Research Council (2013 - 2017)
The Swedish Research Council funding for a graduate student (2010 - 2014)
EU 5th Framework Programme (2003 - 2005)
The Swedish Research Council funding for a graduate student (2002 - 2005)

Publications

2016
T. Koski, E. Sandström & U. Sandström: Towards Field-adjusted Production: Estimating Research Productivity From a Zero-truncated Distribution
Journal of Informetrics, vol. 10, no. 4, pp. 1143-1152
2012
T. Koski & M. Singull: On the Distribution of Matrix Quadratic Forms
Communications in Statistics - Theory and Methods, vol. 41, no. 18, pp. 3403-3415
2010
T. Koski, J. Corander, & M. Gyllenberg: Learning Genetic Population Structures Using Minimization of Stochastic Complexity
Entropy, vol. 12, no. 5, pp. 1102-1124
2008
T. Koski, J. Corander & M. Ekdahl: Parallell Interacting MCMC for Learning of Topologies of Graphical Models
Data Mining and Knowledge Discovery, vol. 17, no. 3, pp. 431-456

Courses by Timo

Data Science

Theory of Probability and Statistics

18 Feb - 08 Mar 2019

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