معرفی
Mattias Villani is a Professor of Statistics at Stockholm University, where he has been employed since 2018. Previously, he was a professor at Linköping University and worked as a researcher at Sveriges Riksbank (the central bank of Sweden). His office is located in Room A 4626 at Albanovägen 12, Building 4, floor 6.
Dr. Villani's research focuses on developing computationally efficient Bayesian methods for inference, prediction, and decision making with flexible probability models. His work spans multiple domains including econometrics, machine learning, and neuroimaging. He has made significant contributions to Markov Chain Monte Carlo methods, particularly in developing subsampling techniques to make Bayesian computation feasible for large datasets.
His recent publications demonstrate a strong trend toward developing scalable Bayesian methods for big data applications. Villani's work on subsampling MCMC methods represents a significant advancement in computational statistics, allowing for efficient Bayesian inference with massive datasets. His research bridges theoretical statistics with practical applications across economics, neuroscience, and machine learning.
Dr. Villani currently teaches the master's courses "Statistical Theory and Modeling" (7.5 credits) and "Bayesian Learning" (7.5 credits). Every other year, he also teaches the doctoral course "Advanced Bayesian Learning" (8 credits).
