Home

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

Krzysztof Bartoszek, Wojciech Bartoszek (2025) Asymptotic Dynamics of Generalized Kantorovich Operators RESULTS IN MATHEMATICS, Vol. 80, Article 39 (Article in journal) Continue to DOI
Iulian Emil Tampu, Tamara Bianchessi, Ida Blystad, Peter Lundberg, Per Nyman, Anders Eklund, Neda Haj-Hosseini (2025) Pediatric brain tumor classification using deep learning on MR-images with age fusion Neuro-Oncology Advances, Vol. 7, Article vdae205 (Article in journal) Continue to DOI

2024

Hariprasath Govindarajan, Per Sidén, Jacob Roll (2024) On Partial Prototype Collapse in the DINO Family of Self-Supervised Methods The 35th British Machine Vision Conference, 2024 (Conference paper)
Muhammad Usman Akbar, Wuhao Wang, Anders Eklund (2024) Beware of diffusion models for synthesizing medical images - A comparison with GANs in terms of memorizing brain MRI and chest x-ray images Machine Learning: Science and Technology (Article in journal) Continue to DOI
Jose M Pena (2024) Alternative Measures of Direct and Indirect Effects INTERNATIONAL CONFERENCE ON PROBABILISTIC GRAPHICAL MODELS (Conference paper)
Patrick O'Keefe, Graciela Muniz-Terrera, Stacey Voll, Frank D. Mann, Sean Clouston, Linda Wänström, Joseph L. Rodgers, Scott Hofer (2024) Inter-cohort shifts in chronic disease, dementia, and mortality Biodemography and Social Biology, Vol. 69, p. 203-217 (Article in journal) Continue to DOI
Martin Smelik, Yelin Zhao, Dina Mansour Aly, A. K. M. Firoj Mahmud, Oleg Sysoev, Xinxiu Li, Mikael Benson (2024) Multiomics biomarkers were not superior to clinical variables for pan-cancer screening Communications Medicine, Vol. 4, Article 234 (Article in journal) Continue to DOI
Jonas Bjermo (2024) Optimal Test Design for Estimation of Mean Ability Growth Applied psychological measurement (Article in journal) Continue to DOI
Christoforos Spyretos, Iulian Emil Tampu, Nadieh Khalili, Juan Manuel Pardo Ladino, Per Nyman, Ida Blystad, Anders Eklund, Neda Haj-Hosseini (2024) Early fusion of H&E and IHC histology images for pediatric brain tumor classification Proceedings of Machine Learning Research, p. 192-202 (Conference paper)
Yun Zhang, Joseph Lee Rodgers, Patrick O'Keefe, Wei Hou, Stacey Voll, Graciela Muniz-Terrera, Linda Wänström, Frank Mann, Scott M. Hofer, Sean A. P. Clouston (2024) The Flynn Effect and Cognitive Decline Among Americans Aged 65 Years and Older Psychology and Aging, Vol. 39, p. 457-466 (Article in journal) 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

freli29

Fredrik Lindsten

Senior Associate Professor, Head of Division

Head of Unit Statistics (STAT)

frami01

Frank Miller

Professor, Head of Unit

Head of Unit Machine Learning (ML)

jospe50

Jose M Pena

Senior Associate Professor, Head of Unit

Director of Undergraduate Studies

jolpi20

Jolanta Pielaszkiewicz

Associate Professor

Administrator

karhe09

Karin Baardsen

Administrator

Staff at STIMA

All staff

Photo of Amirhossein Ahmadian
Amirhossein Ahmadian
PhD student
Photo of Johan Alenlöv
Johan Alenlöv
Lecturer
Placeholder for missing image 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 Gabriel Ducrocq
Gabriel Ducrocq
Postdoc
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
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
PhD student
Photo of Erik Larsson
Erik Larsson
PhD student
Photo of Fredrik Lindsten
Fredrik Lindsten
Senior Associate Professor, Head of Division
Photo of Sebastian Mair
Sebastian Mair
Assistant Professor
Photo of Lisa Menacher
Lisa Menacher
PhD student
Photo of Frank Miller
Frank Miller
Professor, Head of Unit
Photo of Shashi Nagarajan
Shashi Nagarajan
Placeholder for missing image of Anders Nordgaard
Anders Nordgaard
Adjunct Associate Professor, Docent
Photo of Louis Ohl
Louis Ohl
Postdoc
Photo of Joel Oskarsson
Joel Oskarsson
PhD student
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.

Tags