Department of Mathematics and Systems Analysis

Research groups

Stochastics and statistics

Stochastic analysis and statistical modeling are key methodologies for analyzing random interactions in today's information systems. Our research group applies and develops methods in probability theory and mathematical statistics related to applications in communication and transportation networks, engineering, and natural sciences. The main research areas are: stochastic networks and queueing systems, asymptotic statistics, and random spatial structures.


We teach courses in probability and statistics at all levels. Many of the offered MSc courses are eligible as a basis for an SHV degree in insurance mathematics. PhD education in stochastics and statistics is coordinated by the Finnish Doctoral Education Network in Stochastics and Statistics (FDNSS).


MSc/PhD courses 2016-2017

BSc courses 2016-2017

 Basic courses 2016-2017



Assistant Professor Pauliina  Ilmonen
Assistant Professor
Pauliina Ilmonen
Assistant Professor Kalle  Kytölä
Assistant Professor
Kalle Kytölä
Associate Professor Lasse  Leskelä
Associate Professor
Lasse Leskelä
Doctoral Candidate Matias  Heikkilä
Doctoral Candidate
Matias Heikkilä
Doctoral Candidate Joona  Karjalainen
Doctoral Candidate
Joona Karjalainen
Doctoral Candidate Alex  Karrila
Doctoral Candidate
Alex Karrila
Doctoral Candidate Niko  Lietzén
Doctoral Candidate
Niko Lietzén
Doctoral Candidate Hoa  Ngo
Doctoral Candidate
Hoa Ngo
Postdoctoral Researcher Heikki  Seppälä
Postdoctoral Researcher
Heikki Seppälä
Postdoctoral Researcher Christian  Webb
Postdoctoral Researcher
Christian Webb

Affiliated postdocs: Steven Flores (University of Helsinki), Giancarlo Pastor (VTT Research Centre), Lauri Viitasaari (University of Saarbrücken).

Affiliated PhD students: Mikko Kuronen (University of Jyväskylä), Matias Leppisaari (Model IT), Eveliina Peltola (University of Helsinki), Mika Sirviö (Insurance Centre), Tarja Sirén (Financial Supervisory Authority).

Affiliated docents: Kari ElorantaTeemu Pennanen (King's College London), Karl Sigman (Columbia University).

Aalto Stochastics Wiki


Giancarlo Pastor Figueroa 1.3.2016–31.8.2017


  • 29.8. 15:15  Mikko Pakkanen (Imperial College): Rough volatility: empirical evidence and efficient simulation method (further info) – M3 (M234)

    In their recent, yet already seminal, paper (arXiv:1410.3394) Jim Gatheral, Thibault Jaisson, and Mathieu Rosenbaum suggested that financial market volatility should be modelled by stochastic processes that are rougher than Brownian motion. In the first part of my talk, I will present some new (corroborative) empirical evidence of the roughness of volatility, based on ultra-high-frequency financial data. The second part will be more methodological and introduce the so-called hybrid scheme for simulation of rough stochastic processes. In particular, the hybrid scheme can be used to make Monte Carlo-based option pricing in rough volatility models more efficient. The results of this talk have been obtained in collaboration with Mikkel Bennedsen and Asger Lunde.




Selected publications



Helena Aro (Etera)
Ehsan Azmoodeh (University of Luxembourg)
Zhe Chen
Milla Kibble (FIMM Institute for Molecular Medicine Finland)
Matti Kiiski (ETH Zürich)
Ilkka Mellin (University teacher emeritus)
Igor Morlanes (Stockholm University)
Amitava Mukherjee (XLRI- Xavier School of Management)
Ari-Pekka Perkkiö (Technische Universität Berlin)
Heikki Tikanmäki (Finnish Centre for Pensions)
Esko Valkeila (1951–2012)


Page content by: webmaster-math [at] list [dot] aalto [dot] fi