Statistical Learning and Inference for Spatio-Temporal Data

Research expertise

We work on tackling theoretical statistical problems and developing statistical methods for solving real-life problems, which originate from various application areas, including automobile industry, biomedical engineering, conference telephony, criminology, epidemiology, forestry, geochemistry and hydrology, radiation oncology, spatial ecology, and sports science.

Regarding the statistical inference studied: statistical learning with sparsity, compressive sensing, hierarchical spatiotemporal modelling, nonparametric density/intensity estimation and smoothing techniques, statistical inference for hidden Markov models and random fields, summary statistics for point processes, and wavelet theory applied to statistical problems.

In terms of data analysis tools: intelligent data sampling using compressive sensing, large-scale environmental data model, multimodal image processing, tree growth models, and general modelling of biological populations in space and time.

Collaboration at Umeå University

CLiC
CMTF
UMIT
Umeå School of Sport Sciences
Department of Radiation Sciences: Thomas Asklund, Patrik Brynolfsson, Anders Garpebring, Christer Grönlund, Ida Häggström, Adam Johansson, Håkan Jonsson, Mikael Karlsson, Anne Larsson Strömvall, Tufve Nyholm, Urban Wiklund
Sports Medicine: Kajsa Gilenstam, Christer Malm, Michael Svensson
Magnus Ekström (Department of Statistics)
Göran Englund (Department of Ecology and Environmental Sciences)
Charlotte Häger (Department of Community Medicine and Rehabilitation)
Shafiq ur Rehman (Department of Applied Physics and Electronics)
Tor Söderström (Department of Pedagogy)
Johan Trygg (Department of Chemistry)
Patrik Eklund (Department of Computing Science)
Mats Johansson (Department of Computing Science)
Lili Jiang (Department of Computing Science)
Zonghua Gu (Department of Applied Physics and Electronics)

Main collaborators outside Umeå University:

Anastassia Baxevani (University of Cyprus, Nicosia, Cyprus)
Pavel Grabarnik (Russian Academy of Sciences, Pushchino, Russia)
Juha Heikkinen (The Finnish Forest Research Institute, Finland)
Dinghua Huang (China University of Geosciences, Wuhan, China)
M.N.M. van Lieshout (CWI research centre, Amsterdam, The Netherlands)
Zhengyan Lin (Department of Mathematical Sciences, Zhejiang University, China)
Stefan Löfgren (Department of Aquatic Sciences and Assessment, SLU)
Jorge Mateu (Department of Mathematics, Universitat Jaume I, Castellón, Spain)
Kenneth Nyström (Department of Forest Resource Management, SLU)
Henning Omre (Deaprtment of Mathematics, NTNU, Norway)
Nils Östlund (Konftel, Umeå)
Arne Pommerening (Department of Forest Resource Management, SLU)
Bo Ranneby (Centre of Biostochastics, SLU)
Holger Rauhut (Department of Mathematics, RWTH Aachen University, Germany)
Claudia Redenbach (Kaiserslautern University, Germany)
Aila Särkkä (Department of Mathematics Statistics, Chalmers University of Technology)
Mari Myllymäki (LUKE, Finland)
Juha Heikkinen (LUKE, Finland)
Jia Li (Penn State University, USA)
Jonas Örmin (Volvo GTO, Umeå)
Hans Wenngren (Volvo GTO, Umeå)
Kent Sundberg (Volvo GTO, Umeå)
Eric Lindahl (Volvo GTO, Umeå)
Sandra Finér (Volvo GTO, Umeå)
Kendall Rutledge (Novia, Finland)
Niklas Frände (Novia, Finland)
Petri Välisuo (University of Vasa, Finland)
Mohammad Virk (University of Tromsö, Norway)
Javier Martin-Torres (Luleå University of Technology)
Ricardo Fonseca (Luleå University of Technology)