Ei valokuvaa Tommi Mononen

Tommi Mononen

  • PL 65 (Viikinkaari 1)

    00014

    Suomi

20002021

Tutkimustuotoksia vuodessa

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Henkilökohtainen profiili

Tutkimuksen ja opetuksen kuvaus

I got my PhD degree in computer science in January 2010. The main target was to develop computationally efficient methods for the normalized maximum likelihood (NML) model selection criterion, which can be used to select the best statistical model for a given observed data set. To gain the maximum computational efficiency, computation methods must be specifically tailored for each individual model family. In the PhD thesis I developed methods that are suitable for simple Bayesian networks.

I joined the Metapopulation Research Group (MRG) in March 2009. I took part in developing theoretical models for metapopulation research (in collaboration with Professor Ilkka Hanski). The developed models were then fitted to empirical observations and the results revealed the new relevant information of existing metapopulations and their dynamics.

I spent four years at Aalto University (2012-2015). During the first two years, I investigated the validity of singular statistical model selection criteria for the Gaussian process framework and during the latter two years, I investigated the relationship of two brain imaging methods (MEG and fMRI).

I joined MRC for the second time in the beginning of 2016 for continuing to do research with spatio-temporal models, this time, in the host-pathogen framework (in collaboration with Lasse Ruokolainen). In the beginning of 2018, I was a member of a plant biology group lead by Prof. Anna-Liisa Laine.

I was a member of Bioinformatics and Evolution research group (lead by Prof. Ville Mustonen) in 2018-2020 and I applied optimal control theory into ecological problems.

Currently, I am a member of the LIFEPLAN project (Prof. Otso Ovaskainen) working with automated species identification and camera-trap data.

Tieteenalat

  • 1181 Ekologia, evoluutiobiologia
  • 113 Tietojenkäsittely- ja informaatiotieteet
  • 3112 Neurotieteet

Kansainvälinen ja kotimainen yhteistyö

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