The Division of Statistics and Machine Learning (STIMA)

The Division of Statistics and Machine Learning is part of the Department of Computer and Information Science. The research and teaching activities at the division are focused on modern data analysis. 

Research

STIMA is a division of Statistics and Machine Learning that belongs to a department of computer science. This fact makes us unique in Sweden, and we like to view ourselves as Sweden's most modern division of statistics with a clear focus on state-of-the-art data analysis, prediction and decision making in complex systems.

We are engaged in basic methodological research, motivated by a wide range of problems in areas that span from journalism and psychology to genetics and robotics.

Teaching

The division hosts the unique bachelor's programme Statistics and Data Analysis and the international master's programme Statistics and Machine Learning.

We are responsible for the course in machine learning taught at the engineering programmes at Linköping University, as well as the PhD study programme in Statistics.


Seminar series at STIMA

News at STIMA

News and major articles

Innovative idea for more effective cancer treatments rewarded

Lisa Menacher has been awarded the 2024 Christer Gilén Scholarship in statistics and machine learning for her master’s thesis. She utilised machine learning in an effort to make the selection of cancer treatments more effective.

Tomas Landelius and Carolina Natel de Moura.

The focus period resulted in new collaborations for the climate

In the fall of 2024, researchers from around the world once again gathered at Linköping University for ELLIIT's five-week focus period. This time, the goal was to initiate and deepen collaborations in climate research using machine learning.

Participants are listening to a lecture.

Symposium aiming to improve the climate

In the fall of 2024, Linköping University once again hosted ELLIIT's five-week-long focus period. This guest researcher program aimed for greater breadth in interdisciplinarity this year, with the theme of machine learning for climate science.

Research at STIMA

Latest publications

2025

Robert Thornberg, Linda Wänström, Björn Sjögren, Jun Sung Hong, Ylva Bjereld, Silvia Edling, Peter Edward Gill (2025) Well-functioning class climate and classroom prevalence of bullying victims: a short-term longitudinal class-Level path analysis Social Psychology of Education, Vol. 28, Article 158 (Article in journal) Continue to DOI
Amirhossein Ahmadian, Fredrik Lindsten (2025) Improved Contrastive Predictive Coding for Time Series Out-Of-Distribution Detection Applied to Human Activity Data Pattern Recognition Letters, Vol. 197, p. 132-138 (Article in journal) Continue to DOI
Linda Wänström, Robert Thornberg (2025) A 4-Year Longitudinal Validation Study of the School Bullying Victimization Scale (SBVS) and the School Bullying Perpetration Scale (SBPS) for Students in Middle Childhood and Adolescence Psychology of Violence (Article in journal) Continue to DOI
Andreas Lindholm, Fredrik Lindsten (2025) Learning dynamical systems with particle stochastic approximation em FOUNDATIONS OF DATA SCIENCE (Article in journal) Continue to DOI
Louis Ohl, Fredrik Lindsten (2025) Discriminative ordering through ensemble consensus
Jonas Bjermo, Ellinor Fackle‐Fornius, Frank Miller (2025) Optimizing calibration designs with uncertainty in abilities British Journal of Mathematical & Statistical Psychology (Article in journal) Continue to DOI
Maciej K. Wozniak, Hariprasath Govindarajan, Marvin Klingner, Camille Maurice, B. Ravi Kiran, Senthil Yogamani (2025) S3PT: Scene Semantics and Structure Guided Clustering to Boost Self-Supervised Pre-Training for Autonomous Driving 2025 IEEE/CVF WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION, WACV, p. 1660-1670 (Conference paper) Continue to DOI
J. R. Andersson, O. Kochukhov, Zheng Zhao, J. Sjolund (2025) Probabilistic Zeeman-Doppler imaging of stellar magnetic fields: I. Analysis of t Scorpii in the weak-field limit Astronomy and Astrophysics, Vol. 699, Article A63 (Article in journal) Continue to DOI
Ioannis Athanasiadis, Fredrik Lindsten, Michael Felsberg (2025) Prior Learning in Introspective VAEs Transactions on Machine Learning Research, Vol. 06, p. 1-41 (Article in journal)
Xiao-Pan Hu, Bayu Brahmantio, Krzysztof Bartoszek, Martin J. Lercher (2025) Most bacterial gene families are biased toward specific chromosomal positions Science, Vol. 388, p. 186-191 (Article in journal) Continue to DOI

Teaching - Bachelor and Master's programme

PhD studies

Contact us

Staff at STIMA

About the department