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鈥檚 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 福利姬 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, 福利姬 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.

Latest publications

2025

Krzysztof Bartoszek, Ying Luo (2025) Mathematica Applicanda, Vol. 52 (Article in journal)

Filip Ekström Kelvinius, Oskar Andersson, Abhijith S. Parackal, Dong Qian, Rickard Armiento, Fredrik Lindsten (2025) Proceedings of the 42nd International Conference on Machine Learning, p. 15130-15147 (Conference paper)

Filip Ekström Kelvinius, Zheng Zhao, Fredrik Lindsten (2025) 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) IMAGE ANALYSIS, SCIA 2025, PT II, p. 166-179 (Conference paper)

Robert Thornberg, Linda Wänström, Björn Sjögren, Jun Sung Hong, Ylva Bjereld, Silvia Edling, Peter Edward Gill (2025) Social Psychology of Education, Vol. 28, Article 158 (Article in journal)

Amirhossein Ahmadian, Fredrik Lindsten (2025) Pattern Recognition Letters, Vol. 197, p. 132-138 (Article in journal)

Linda Wänström, Robert Thornberg (2025) Psychology of Violence (Article in journal)

Andreas Lindholm, Fredrik Lindsten (2025) FOUNDATIONS OF DATA SCIENCE (Article in journal)

Louis Ohl, Fredrik Lindsten (2025) Proceedings of the 41st Conference on Uncertainty in Artificial Intelligence, p. 3252-3271 (Conference paper)

Jonas Bjermo, Ellinor Fackle鈥怓ornius, Frank Miller (2025) British Journal of Mathematical & Statistical Psychology (Article in journal)

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

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鈥檚 chosen area of specialisation.

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

Head of Unit Statistics (STAT)

Head of Unit Machine Learning (ML)

Director of Undergraduate Studies

Staff at STIMA

All staff

Senior Associate Professor

Filip Ekström Kelvinius

PhD student

Hariprasath Govindarajan

Anders Grimvall

Professor Emeritus

Ann-Charlotte Hallberg

Woodrow Hao Chi Kiang

Erik Larsson

PhD student

Fredrik Lindsten

Professor, Head of Division

Professor, Head of Unit

Senior Associate Professor, Head of Unit

Jolanta Pielaszkiewicz

Senior Associate Professor

Associate Professor, Docent

Zheng Zhao

Assistant Professor

About the department

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.

福利姬