Department of Biomedical Engineering and Computational Science

Bayesian Methodology Group

Starting 1st May 2015, the group has joined the new Probabilistic Machine Learning group at Department of Computer Science.

These pages are not updated anymore.

Bayesian methodology group lead by Aki Vehtari conducts research in the field of modern computational science and develops generic computational statistical methods. These include fast approximative inference methods as well as model assessment and selection methods for complex hierarchical, non-parametric, graphical, dynamic and spatio-temporal models. The developed methods can handle larger datasets using more elaborate and computationally intensive models than before while keeping the computation time reasonable to aid researchers in other scientific fields. The methods are applied to challenging scientific problems in, e.g., brain signal analysis (MEG, fMRI), epidemiology, genetics, bioinformatics, medicine, tomography, animal population research, audio signal processing, and tracking.

Group members


Senior reseacher

Doctoral students

  • Olli-Pekka Koistinen
  • Juho Kokkala
  • Juho Piironen
  • Arno Solin

Research students

  • Tuomas Sivula

Past members

  • Mari Myllymäki
  • Tomi Peltola
  • Ville Tolvanen
  • Jukka Koskenranta
  • Tommi Mononen
  • Pasi Jylänki
  • Janne Ojanen
  • Jaakko Riihimäki
  • Max Hurme
  • Eero Pennala
  • Heikki Peura
  • Pekka Marttinen
  • Jouni Hartikainen
  • Ville Pietiläinen
  • Jarno Vanhatalo
  • Aki Havulinna
  • Eli Parviainen
  • Saara Suikkanen
  • Olli-Pekka Kahilakoski
  • Matleena Kukkonen
  • Sasu Mäkelä
  • Sakari Cajanus
  • Jani Kuula
  • Roberto Calandra
  • Mudassar Abbas
  • Ernesto Ulloa
  • Enrique Lelo de Larrea Andrade
  • Tuomas Nikoskinen
  • Ville Pietiläinen
  • Ville Väänänen
  • Markus Siivola