The Finnish Doctoral Programme in Stochastics and Statistics

Front page

Overview

Participating departments and institutions

Board and contact information

Researchers – Advisors

Doctoral students

Theses

Past events

Summer School on Probability Theory


Academy of Finland

Researchers – Advisors

The main responsibility for adequate advising and consulting lies with the professors and senior researchers at the participating institutions. By furthering national and international cooperation the network can greatly enlarge the pool of expertise available for the individual doctoral student.

The list is divided into broad categories, but many persons might be placed under two or more categories.


Markov Processes with Applications, Actuarial Mathematics

Stochastic Analysis and Stochastic Control Theory with Applications

Stochastic Networks, Random Structures and Spatial Models

  • Prof. Lasse Leskelä (Aalto University School of Science), stochastic networks, stochastic analysis, ergodic theory, stochastic control, coupling techniques, computational methods, lasse.leskela[at]tkk.fi
  • Dr. Petteri Mannersalo (Technical Research Centre of Finland VTT), large deviations, spatial models, petteri.mannersalo[at]vtt.fi
  • Research Professor, Doc. Ilkka Norros (Technical Research Centre of Finland VTT and University of Helsinki), queueing theory, random graphs, network dependability, ilkka.norros[at]vtt.fi
  • Dr. Hannu Reittu (Technical Research Centre of Finland VTT), random structures and algoithms, hannu.reittu[at]vtt.fi

Statistical Methodology

Computer Intensive Methods and Data Analysis

  • Prof. Lasse Holmström (University of Oulu), nonparametric function estimation, neural nets, pattern recognition with application to information technology and natural sciences, http://cc.oulu.fi/~llh/
  • Prof. Aapo Hyvärinen (University of Helsinki), neuroinformatics related to statistical data analysis, http://www.cs.helsinki.fi/u/ahyvarin/
  • Prof. Mikko J. Sillanpää (University of Oulu), Bayesian variable selection and prediction methods from big data (large k, small n) problems with applications in agriculture, biology and medicine, www.rni.helsinki.fi/~mjs/

Biostatistics

Econometrics, Economic Statistics and Finance

Official Statistics

Social and Business Statistics