My main fields of research are probability theory and mathematical statistical mechanics. Some keywords describing my current research are random walks in (dynamic) random environment, interacting particle systems, chains of infinite order and Gibbs measures. 

I am part of the Statistics and Data Science Research Group at the Deparment of Mathematics.

Høst 2026 - STAT110 Grunnkurs i statistikk

Vår 2026 - STAT111 - Statistiske metoder

Høst 2025 - STAT221 - Sannsynlighetsteori

Vår 2025 - STAT111 - Statistiske metoder

Fall 2024: STAT101 

Fall 2023: STAT220

Spring 2023: STAT210

Fall 2022: STAT221

Fall 2021: STAT101 

Spring 2021: STAT210

Fall 2020: STAT101

All my papers and preprints are available on the arXiv:

• Mixing for Poisson representable processes and consequences for the Ising model and the contact process (with Malin Palö Forsström). (ArXiv preprint)
   
• Random walks on random walks: non-perturbative results in high dimensions (with Florian Völlering). (ArXiv preprint)
   
• Quenched local limit theorem for a directed random walk on the backbone of a supercritical oriented percolation cluster for d≥1  (with Matthias Birkner, Andrej Depperschmidt and Timo Schlüter). ArXiv preprint.
   
• Limit laws for random walks in a dynamic path-cone mixing random environment (with Florian Völlering). (ArXiv preprint)
   
• Local limit theorems for a directed random walk on the backbone of a supercritical oriented percolation cluster (with Matthias Birkner, Andrej Depperschmidt and Timo Schlüter) Electronic Journal of Probability, 28, 1-54 (2023) - ArXiv preprint.
   
• Quenched invariance principle for random walks on dynamically averaging random conductances (with Christian Hirch and Christian Mönch) Electronic Communications in Probability (2021) - ArXiv preprint.
   
• Graph constructions for the contact process with a prescribed critical rate (with Gabriel Baptista da Silva and Daniel Valesin) Journal of Theoretical Probability (2021) - ArXiv preprint.
   
• On projections of the supercritical contact process: uniform mixing and cutoff phenomenon. Lecture notes series Genealogies of Interacting Particle Systems, Institute for Mathematical Sciences, National University of Singapore: Volume 38, 315--340, 2020. (ArXiv preprint)
   
• One-sided continuity properties for the Schonmann projection (with Diana Conache) Journal of Statistical Physics, 172(4), 1147--1163, 2018. (ArXiv preprint)
   
• The contact process as seen from a random walk ALEA, Lat. Am. J. Probab. Math. Stat. 15, 571–585, 2018.
   
• Stochastic domination in space-time for the contact process (with Rob van den Berg). Random Structures Algorithms, 53(2), 221–237, 2018. (ArXiv preprint)
   
• Law of large numbers for random walks on attractive spin-flip dynamics (with Markus Heydenreich) Stochastic Processes and Applications 127(7), 2346-2372, 2017. (ArXiv preprint)
   
• Absolute continuity and weak uniform mixing for random walk in dynamic random environment (with Florian Völlering). Electron. J. Probab. 21, no. 71, 1-32, 2016.

Stein Andreas Bethuelsen is an Associate Professor at the Department of Mathematics at the University of Bergen, affiliated with the Statistics and Data Science group. He has previously worked at the University of Stavanger and the Technical University of Munich. He holds a PhD from the University of Leiden.

His main field of research is probability theory. His work focusses on the rigorous mathematical theory of certain stochastic processes, often with ties to questions originating from statistical mechanics or biology, and often evolving on an underlying network structure. Some keywords describing his current research are random walks in (dynamic) random environment, interacting particle systems, chains of infinite order and Gibbs measures.

Stein Andreas has been a member of the German-based DFG-Scientific Network Stochastic Processes on Evolving Networks (external link). He is currently a member of the EU Cost-action mSpace (external link), dedicated to developing a unified mathematical framework for multiscale systems.