Aki Vehtari
ELLIS Institute
Academy Professor
T313 Dept. Computer Science
I work on the integration of computer science and Bayesian statistics, making fundamental contributions Bayesian workflow, probabilistic programming, inference methods such as Laplace, EP, VB, MC, inference and model diagnostics, model assessment and selection, Gaussian processes, and hierarchical models. I'm the leader of the Bayesian workflow group.
Full researcher profile
https://research.aalto.fi/...
Sähköposti
aki.vehtari@aalto.fi
Puhelinnumero
+358405333747
Osaamisalueet
Bayesian computational modeling, Bayesian workflow
Palkinnot
Youden Award in Interlaboratory Testing from the American Statistical Association
Youden Award in Interlaboratory Testing from the American Statistical Association awarded to paper Sebastian Weber, Andrew Gelman, Daniel Lee, Michael Betancourt, Aki Vehtari, and Amy Racine-Poon (2018). Bayesian aggregation of average data: An application in drug development. Annals of Applied Statistics, 12(3):1583-1604.
Award or honor granted for a specific work
Department of Computer Science
Jan 2020
Member of the winning team (Särkkä, Vehtari & Lampinen) in Time Series Prediction Competition - The CATS Benchmark 2004
Invitation or ranking in competition
Department of Computer Science
Jan 2004
2016 De Groot Prize
The DeGroot Prize, in honor of Morris H ("Morrie" DeGroot, is awarded to the author or authors of an outstanding published book in Statistical Science
Award or honor granted for a specific work
Department of Computer Science
Jun 2016
Tutkimusryhmät
- Computer Science Professors, Academy Professor
- Computer Science - Artificial Intelligence and Machine Learning (AIML) - Research area, Academy Professor
- Probabilistic Machine Learning, Academy Professor
- Professorship Vehtari Aki, Academy Professor
- Helsinki Institute for Information Technology (HIIT), Academy Professor
Julkaisut
Raw signal segmentation for estimating RNA modification from Nanopore direct RNA sequencing data
Guangzhao Cheng, Aki Vehtari, Lu Cheng
2025
eLife
Cross-Validatory Model Selection for Bayesian Autoregressions with Exogenous Regressors
Alex Cooper, Dan Simpson, Lauren Kennedy, Catherine Forbes, Aki Vehtari
2025
Bayesian Analysis
Active Learning of Molecular Data for Task-Specific Objectives
Kunal Ghosh, Milica Todorovic, Aki Vehtari, Patrick Rinke
2025
Journal of Chemical Physics
The ARR2 Prior: Flexible Predictive Prior Definition for Bayesian Auto-Regressions
David Kohns, Noa Kallioinen, Yann McLatchie, Aki Vehtari
2025
Bayesian Analysis
posteriordb: Testing, Benchmarking and Developing Bayesian Inference Algorithms
Måns Magnusson, Jakob Torgander, Paul Christian Bürkner, Lu Zhang, Bob Carpenter, Aki Vehtari
2025
Proceedings of the 28th International Conference on Artificial Intelligence and Statistics (AISTATS) 2025
Advances in projection predictive inference
Yann McLatchie, Sölvi Rögnvaldsson, Frank Weber, Aki Vehtari
2025
Statistical Science
Health octo tool matches personalized health with rate of aging
Sh Salimi, A. Vehtari, M. Salive, M. Kaeberlein, D. Raftery, L. Ferrucci
2025
Nature Communications
Uncertainty in Bayesian Leave-One-Out Cross-Validation Based Model Comparison
Tuomas Sivula, Måns Magnusson, Asael Alonzo Matamoros, Aki Vehtari
2025
Bayesian Analysis
The Piranha Problem: Large Effects Swimming in a Small Pond
Christopher Tosh, Philip Greengard, Ben Goodrich, Andrew Gelman, Aki Vehtari, Daniel Hsu
2025
Notices of the American Mathematical Society
Bayesian cross-validation by parallel Markov chain Monte Carlo
Alex Cooper, Aki Vehtari, Catherine Forbes, Dan Simpson, Lauren Kennedy
2024
STATISTICS AND COMPUTING