Aki Vehtari

Associate professor in computational science (focus on probabilistic modeling) at Aalto University
Visiting professor at Technical University of Denmark (DTU)
Aalto University
School of Science
Helsinki Institute for Information Technology HIIT
Department of Computer Science
Probabilistic Machine Learning Group

Office: Konemiehentie 2, 3rd floor, A314
Phone: +358 40 5333 747
Email: Aki.Vehtari(at)aalto.fi
Twitter: @avehtari

Research Activities

My research interests are Bayesian probability theory and methodology, especially inference methods such as Laplace, EP, VB, MC, model assessment and selection, non-parametric models such as Gaussian processes, dynamic models, and hierarchical models. Applications include brain signal analysis (MEG, fMRI, InI-fMRI ), personalized medicine, survival analysis, public and occupational health care data analysis, and spatio-temporal epidemiology.

BDA3: Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari and Donald B. Rubin (2013). Bayesian Data Analysis, Third Edition. Chapman and Hall/CRC. Publisher's webpage for the book. Home page for the book. Matlab/Octave demos. Python demos.

My blog postings

GPstuff - Gaussian process models for Bayesian analysis (software)

Full list of my publications

Recent publications


Last modified: 2015-09-17