Lasse Leskelä

Professori (Associate professor)
Professori (Associate professor)
T302 Dept. Mathematics and Systems Analysis

My research area is stochastics, the mathematical theory of random events, systems, and processes. The main focus is statistical network models and random graphs, together with random dynamical systems and stochastic processes acting on networks. The general objective is to derive fundamental mathematical laws for predicting the macroscopic behavior of large random systems and describing the accuracy of statistical learning algorithms for large network models. Such laws allow to make predictions using massive high-dimensional data sets for which classical methods of statistics and machine learning are often infeasible. Statistical network models under study include random intersection graphs, stochastic block models, and graphons. The archetypes of stochastic dynamics studied are branching processes, random walks, and first passage percolation. The formulas and methods have a wide range of applications ranging from information and social networks to biological and financial systems.

Full researcher profile
https://research.aalto.fi/...
Phone number
+358405375352

Areas of expertise

Probability theory, Stochastic processes, Random graphs, Statistical network models, Queueing Theory, Applied probability, Stochastics, Stochastic modeling, 112 Statistics and probability, Applied mathematics

Honors and awards

Varma-Sampo MSc thesis prize, Finnish Mathematical Society

Award or honor granted for a specific work Department of Mathematics and Systems Analysis Jan 2000

McKinsey Prize

McKinsey Prize for the best MSc degree completed in 1999 at the Helsinki University of Technology.
Award or honor granted for academic or artistic career Department of Mathematics and Systems Analysis Jan 2000

Research groups

  • Statistics and Mathematical Data Science, Professor (Associate Professor)

Publications

Recovering Static and Time-Varying Communities Using Persistent Edges

Konstantin Avrachenkov, Maximilien Dreveton, Lasse Leskela 2024 IEEE Transactions on Network Science and Engineering

Connectivity of random hypergraphs with a given hyperedge size distribution

Elmer Bergman, Lasse Leskelä 2024 Discrete Applied Mathematics

Clique and cycle frequencies in a sparse random graph model with overlapping communities

Tommi Gröhn, Joona Karjalainen, Lasse Leskelä 2024 Stochastic models

The influence of cross-border mobility on the COVID-19 epidemic in Nordic countries

Mikhail Shubin, Hilde Kjelgaard Brustad, Jørgen Eriksson Midtbø, Felix Günther, Laura Alessandretti, Tapio Ala-Nissila, Gianpaolo Scalia Tomba, Mikko Kivelä, Louis Yat Hin Chan, Lasse Leskelä 2024 PLoS computational biology

Distinguishing subsampled power laws from other heavy-tailed distributions

Silja Sormunen, Lasse Leskelä, Jari Saramäki 2024 Physical Review E

Multilayer Hypergraph Clustering Using the Aggregate Similarity Matrix

Kalle Alaluusua, Konstantin Avrachenkov, B. R.Vinay Kumar, Lasse Leskelä 2023 Algorithms and Models for the Web Graph - 18th International Workshop, WAW 2023, Proceedings

Tilastotieteen sanasto : verkkoversio (2023)

Juha Alho, Elja Arjas, Juha Karvanen, Lasse Leskelä, Esa Läärä, Pekka Pere 2023

Persistence in a large network of sparsely interacting neurons

Maximiliano Altamirano, Roberto Cortez, Matthieu Jonckheere, Lasse Leskelä 2023 Journal of Mathematical Biology

Clustering and percolation on superpositions of Bernoulli random graphs

Mindaugas Bloznelis, Lasse Leskelä 2023 RANDOM STRUCTURES AND ALGORITHMS

Normal and stable approximation to subgraph counts in superpositions of Bernoulli random graphs

Mindaugas Bloznelis, Joona Karjalainen, Lasse Leskelä 2023 Journal of Applied Probability