The stochastics group at the department comprises researchers active in the fields of

- probability, statistics, data science, optimization, and operations research.

The group is responsible for the study programs in

- statistics, data science and mathematics-economics

and was recently extended with the Applied Statistics Laboratory, which provides statistical support and consultancy to other departments at Aarhus University.

There is a strong tradition in the group for interdisciplinary research as well as for national and international collaborations. To see the breadth of research interests consult the business cards below.

Debarghya Ghoshdastidar
(TU München)

Stochastics Seminar
(Stochastics Group)

Workshop
(Stochastics Group)

Fomichov, V., Franceschi, S. & Ivanovs, J. (2022). Probability of total domination for transient reflecting processes in a quadrant. *Advances in Applied Probability*, *54*(4), 1094-1138. https://doi.org/10.1017/apr.2022.2

Røikjer, T., Hobolth, A. & Munch, K. (2022). Graph-based algorithms for phase-type distributions. *Statistics and Computing*, *32*(6), [103]. https://doi.org/10.1007/s11222-022-10174-3

Laursen, R. & Hobolth, A. (2022). A Sampling Algorithm to Compute the Set of Feasible Solutions for NonNegative Matrix Factorization with an Arbitrary Rank. *SIAM Journal on Matrix Analysis and Applications*, *43*(1), 257-273. https://doi.org/10.1137/20M1378971

Ljungdahl, M. M. & Podolskij, M. (2022). Multidimensional parameter estimation of heavy-tailed moving averages. *Scandinavian Journal of Statistics*, *49*(2), 593-624. https://doi.org/10.1111/sjos.12527

Shanmugam, S., Hefner, M., Labouriau, R., Trinchera, A., Willekens, K. & Kristensen, H. L. (2022). Intercropping and fertilization strategies to progress sustainability of organic cabbage and beetroot production. *European Journal of Agronomy*, *140*, [126590]. https://doi.org/10.1016/j.eja.2022.126590

The links take you to the personal homepage in AU's system (pure), where you find publications and contact information.

Professor

Machine learning, statistical learning, statistical methods in molecular biology, stochastic processes.

Associate professor

Topological data analysis, large deviations theory, spatial random networks, stochastic geometry, spatial statistics

Associate professor

Nonparametric statistics, stochastic processes, statistical learning

Associate professor

Applied probability, stochastic processes, extremes, distributional robustness, simulation, high-frequency statistics

Associate professor

Statistics, Statistical Learning / Machine Learning, Deep learning for medical images, Monte Carlo Simulation, Bioinformatics

Associate professor

Stochastic geometry, convex geometry, geometric tomography, spatial statistics

Associate professor

Free probability theory, random matrices, Lévy processes, operator algebras.

Associate professor

Statistics – stochastic geometry, stereology, computational and nonparametric statistics, multiple testing

Emerita professor

Statistics – stochastic geometry, stereology, spatial statistics

Emeritus associate professor

Operations research, inventory control, Markov decision processes, simulation, cost accounting