Research interests
Statistical models are used in all areas of science to describe stochastic relations between variables. In statistical modeling, probability theory is used to describe the uncertainty that is present due to inaccurate measurements, model mismatch, missing data, etc. The process of drawing conclusions based on statistical models is called statistical inference. The aim of my research is to develop novel statistical methodology, which includes:
- Formulating probabilistic models and devising procedures for computational inference, evaluation, and validation.
- Applying the developed methodology to solve problems in various application areas in science and industry.
Collaborators
Kristoffer Jon Albers,
Tommy Sonne Alstrøm,
Karen Sandø Ambrosen,
Kasper Winther Andersen,
Morten Arngren,
Michael Bache,
Jan Michael Bauer,
Anja Boisen,
Mads G. Chrisensen,
Eldad Davidov,
Tim Dyrby,
Casper T. Eriksen,
Kasper B. Frøhling,
Jacob Frøsig,
Fumiko Kano Glückstad,
Marcel A. J. van Gerven,
Kunal Ghosh,
Lars Kai Hansen,
Tue Herlau,
Jesper Løve Hinrich,
Fu-Tien Hsiao,
Karsten Wedel Jacobsen,
Mogens H. Jakobsen,
Bjørn S. Jensen,
Søren H. Jensen,
Peter B. Jørgensen,
Natalie V. Kostesha,
Marco D. F. Kristensen,
Jan Larsen,
Juan Maria García Lastra,
Hans Laurberg,
Kristoffer H. Madsen,
Murat Mesta,
Shakir Mohamed,
Andreas Leon Aagaard Moth,
Morten Mørup,
Søren F. V. Nielsen,
Rasmus K. Olsson,
Nicolai A. B. Riis,
Patrick Rinke,
Estefania Garijo del Rio,
Tomas Rindzevicius,
Michael S. Schmidt,
Daniel Seddig,
Suranjan Shil,
Hartwig Roman Siebner,
Annika Stuke,
Marcus Svendstorp,
Kristian Thygesen,
Milica Todorovic,
Aki Vehtari,
Ole Winther.
Google Scholar profile
Brain connectivity: Non-parametric Relational Modeling of Functional and Structural Brain Connectivity.
Technical University of Denmark profile
ORCID profile: 0000-0001-6927-8869