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

Male researcher in lab, blue background light.

SEK 13 million for research into solving murders using AI

Was it murder, poisoning or was the death maybe caused by disease? Researchers have now been granted SEK 13 million from the Swedish Research Council to develop a methodology to solve crimes using detailed analyses and artificial intelligence.

Meet Akshay, student at Statistics and Machine Learning

Master's student awarded for research on traffic flow patterns

Akshay Gurudath receives the Christer Gilén Scholarship for his degree project in statistics and machine learning. In his thesis, Akshay presents and compares models he has built to predict positions of pedestrians, cyclists, and autonomous vehicles.

Chu Wanjun visar för gruppen vilka frukter roboten kan känna igen just nu. I förgrunden ligger en apelsin.

Minister for Energy and Digital Development visits IDA

On Wednesday, 20 april 2022, the minister for digital development Khashayar Farmanbar visited the Department of Computer and Information Science together with the Linköping municipal councillor Mari Hultgren.

Research at STIMA

Latest publications

2024

Jonas Malmborg, Magnus Larsson, Lars Jaeger, Anders Nordgaard (2024) Transfer, persistence, contamination and background levels of inorganic gunshot residues FORENSIC CHEMISTRY, Vol. 39, Article 100577 Continue to DOI
Amanda Olmin, Jakob Lindqvist, Lennart Svensson, Fredrik Lindsten (2024) On the connection between Noise-Contrastive Estimation and Contrastive Divergence
Yelin Zhao, Xinxiu Li, Joseph Loscalzo, Martin Smelik, Oleg Sysoev, Yunzhang Wang, A. K. M. Firoj Mahmud, Dina Mansour Aly, Mikael Benson (2024) Transcript and protein signatures derived from shared molecular interactions across cancers are associated with mortality Journal of Translational Medicine, Vol. 22, Article 444 Continue to DOI
Carl Edin, Mattias Ekstedt, Markus Karlsson, Bertil Wegmann, Marcel Warntjes, Eva Swahn, Carl Johan Östgren, Tino Ebbers, Peter Lundberg, Carl-Johan Carlhäll (2024) Liver fibrosis is associated with left ventricular remodeling: insight into the liver-heart axis European Radiology Continue to DOI
Filip Ekström Kelvinius, Fredrik Lindsten (2024) Discriminator Guidance for Autoregressive Diffusion Models Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, p. 3403-3411
Frank D. Mann, Adolfo G. Cuevas, Sean A.P. Clouston, Colin D. Freilich, Zlatan Krizan, Sascha Zuber, Linda Wänström, Graciela Muniz-Terrera, Patrick O'Keefe, Stacey Voll, Scott Hofer, Joseph L. Rodgers, Robert F. Krueger (2024) A novel approach to model cumulative stress: Area under the s-factor curve Social Science and Medicine, Vol. 348, Article 116787 Continue to DOI
Amirhossein Ahmadian, Yifan Ding, Gabriel Eilertsen, Fredrik Lindsten (2024) Unsupervised Novelty Detection in Pretrained Representation Space with Locally Adapted Likelihood Ratio International Conference on Artificial Intelligence and Statistics 2024, Proceedings of Machine Learning Research
Iulian Emil Tampu, Tamara Bianchessi, Anders Eklund, Neda Haj-Hosseini (2024) Pediatric brain tumor classification using MR-images with age fusion
Christoforos Spyretos, Iulian Emil Tampu, Juan Manuel Pardo Ladino, Neda Haj-Hosseini (2024) Comparison of state-of-the-art models for slide-level pediatric brain tumor histology classification
Frank Miller, Ellinor Fackle-Fornius (2024) Parallel Optimal Calibration of Mixed-Format Items for Achievement Tests Psychometrika Continue to DOI

Teaching - Bachelor, Masters and PhD

Contact us

Staff at STIMA

About the department