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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

STIMA leads two popular research seminar series

IDA Machine Learning Seminars

The Machine Learning Research Group at IDA invites to the research seminar series IDA Machine Learning Seminars. Welcome!

Seminars in Statistics and Mathematical Statistics

Here you can find all information about our seminars. Warm welcome!

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

robot dog Spot, drone, small helicopter, operator

WASP at Department of Computer and Information Science (IDA)

WASP, Wallenberg AI autonomous systems and software program, is the largest individual research investment in Sweden in modern times. One of the WASP research environments at LiU is located at the Department of Computer and Information Science.
Global networks combined with light.

ELLIIT

ELLIIT is a network organization for Information and Communication Technology (ICT) research at Linköping, Lund, Halmstad and Blekinge. The objective is scientific excellence in combination with industrial relevance and impact.

ELLIIT

Latest publications

2025

Marie-Ange Fleury, Louis Ohl, Lionel Tastet, Mickaël Leclercq, Frédéric Precioso, Pierre-Alexandre Mattei, Romain Capoulade, Kathia Abdoun, Élisabeth Bédard, Marie Arsenault, Jonathan Beaudoin, Mathieu Bernier, Erwan Salaun, Jérémy Bernard, Mylène Shen, Sébastien Hecht, Nancy Côté, Arnaud Droit, Philippe Pibarot (2025) Unsupervised Machine Learning Analysis to Enhance Risk Stratification in Patients with Asymptomatic Aortic Stenosis The European Heart Journal - Digital Health, Article ztaf115 (Article in journal) Continue to DOI
Jonas Malmborg, Ludvig Joborn, Mattias Beming, Anders Nordgaard, Ivo Alberink (2025) Comparing a machine learning approach with traditional methods for forensic source attribution using chromatographic data FORENSIC CHEMISTRY, Vol. 46, Article 100699 (Article in journal) Continue to DOI
Louis Ohl, Pierre-Alexandre Mattei, Frederic Precioso (2025) A Tutorial on Discriminative Clustering and Mutual Information ACM Computing Surveys, Vol. 58, Article 90 (Article in journal) Continue to DOI
Sourabh Balgi, Marc Braun, Jose M. Peña, Adel Daoud (2025) Sensitivity Analysis to Unobserved Confounding with Copula-Based Normalizing Flows International Journal of Approximate Reasoning, Vol. 187, Article 109531 (Article in journal) Continue to DOI
Arnaud Doucet, Victor Elvira, Fredrik Lindsten, Joaquin Miguez (2025) Preface special issue onsequential monte carlo methods FOUNDATIONS OF DATA SCIENCE, Vol. 7 (Article in journal) Continue to DOI
Annika Tillander, Susanna Lehtinen-Jacks, Nisha Singh, Oskar Halling Ullberg, Ulrika Florin, Katarina Balter (2025) Data for assigning a proxy variable for office worker in open-ended responses on occupation in Swedish questionnaires Data in Brief, Vol. 63, Article 112105 (Article in journal) Continue to DOI
Krzysztof Bartoszek, Ying Luo (2025) Fuzzy clustering in Czekanowski's diagram Mathematica Applicanda, Vol. 52 (Article in journal) Continue to DOI
Filip Ekström Kelvinius, Oskar Andersson, Abhijith S. Parackal, Dong Qian, Rickard Armiento, Fredrik Lindsten (2025) WyckoffDiff- A Generative Diffusion Model for Crystal Symmetry Proceedings of the 42nd International Conference on Machine Learning, p. 15130-15147 (Conference paper)
Filip Ekström Kelvinius, Zheng Zhao, Fredrik Lindsten (2025) Solving Linear-Gaussian Bayesian Inverse Problems with Decoupled Diffusion Sequential Monte Carlo Proceedings of the 42nd International Conference on Machine Learning, p. 15148-15181 (Conference paper)
Yifan Ding, Arturas Aleksandrauskas, Amirhossein Ahmadian, Jonas Unger, Fredrik Lindsten, Gabriel Eilertsen (2025) Revisiting Likelihood-Based Out-of-Distribution Detection by Modeling Representations IMAGE ANALYSIS, SCIA 2025, PT II, p. 166-179 (Conference paper) Continue to DOI

Teaching - Bachelor and Master's programme

Bachelor's Programme in Statistics and Data Analysis, 180 credits

An illustration of a stream of ones and zeroes.

Statistics and Machine Learning, Master's Programme, 120 credits

The intersection of statistics, artificial intelligence and database management, providing students a unique competence. Meets the demand for specialists able to exploit a wealth of information to improve analysis, prediction and decision making.

PhD studies

students seated at a round table

Graduate Studies in Statistics

The doctoral program is intended to provide graduate students with a deep, foundational education in statistics, along with further in-depth knowledge in the student’s chosen area of specialisation.
Spot, the robot dog

Doctoral studies in Computer Science

Computer Science is an interdisciplinary subject area, covering everything from basic studies of algorithms, computational processes, and knowledge representation to informatics and computer linguistics.

Contact us

Management

Head of Division

Photo of Fredrik Lindsten

Fredrik Lindsten

Professor, Head of Division

Head of Unit Statistics (STAT)

Photo of Frank Miller

Frank Miller

Professor, Head of Unit

Head of Unit Machine Learning (ML)

Photo of Jose M Pena

Jose M Pena

Senior Associate Professor, Head of Unit

Director of Undergraduate Studies

Photo of Jolanta Pielaszkiewicz

Jolanta Pielaszkiewicz

Associate Professor

Staff at STIMA

All staff

Photo of Johan Alenlöv
Johan Alenlöv
Lecturer
Photo of Martin Andrae
Martin Andrae
PhD student
Photo of Sourabh Balgi
Sourabh Balgi
Photo of Krzysztof Bartoszek
Krzysztof Bartoszek
Senior Associate Professor
Photo of Jonas Bjermo
Jonas Bjermo
Postdoc
Photo of Bayu Brahmantio
Bayu Brahmantio
PhD student
Photo of Marc Braun
Marc Braun
PhD student
Photo of Gabriel Ducrocq
Gabriel Ducrocq
Photo of Filip Ekström Kelvinius
Filip Ekström Kelvinius
PhD student
Photo of Hariprasath Govindarajan
Hariprasath Govindarajan
Placeholder for missing image of Anders Grimvall
Anders Grimvall
Professor Emeritus
Photo of Ann-Charlotte Hallberg
Ann-Charlotte Hallberg
Lecturer
Photo of Isak Hietala
Isak Hietala
Lecturer
Photo of Adhithyan Kalaivanan
Adhithyan Kalaivanan
PhD student
Placeholder for missing image of Woodrow Hao Chi Kiang
Woodrow Hao Chi Kiang
Photo of Erik Larsson
Erik Larsson
PhD student
Photo of Fredrik Lindsten
Fredrik Lindsten
Professor, Head of Division
Photo of Sebastian Mair
Sebastian Mair
Assistant Professor
Photo of Lisa Menacher
Lisa Menacher
PhD student
Placeholder for missing image of Andrew Millard
Andrew Millard
Research Engineer
Photo of Frank Miller
Frank Miller
Professor, Head of Unit
Photo of Shashi Nagarajan
Shashi Nagarajan
Photo of Edward Ngailo
Edward Ngailo
Photo of Louis Ohl
Louis Ohl
Postdoc
Photo of Jose M Pena
Jose M Pena
Senior Associate Professor, Head of Unit
Photo of Jolanta Pielaszkiewicz
Jolanta Pielaszkiewicz
Associate Professor
Placeholder for missing image of Dong Qian
Dong Qian
Postdoc
Photo of Oleg Sysoev
Oleg Sysoev
Senior Associate Professor
Photo of Annika Tillander
Annika Tillander
Associate Professor
Photo of Bertil Wegmann
Bertil Wegmann
Associate Professor
Photo of Josef Wilzén
Josef Wilzén
Lecturer
Photo of Linda Wänström
Linda Wänström
Associate Professor, Docent
Photo of Zheng Zhao
Zheng Zhao
Assistant Professor

About the department

Image of Building E, Campus Valla.

Department of Computer and Information Science (IDA)

The Department of Computer and Information Science is one of the largest departments in northern Europe in its field. Research activity covers artificial intelligence, human-computer interaction, software and computer systems, and data science.

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