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      University of Skövde, link to startpage

      Göran Falkman

      Associate Professor of Computer Science
      School of Informatics
      Room PA520S

      PhD in Computing Science, Docent in Computer Science, Interactive Knowledge Systems
      Associate Professor (Biträdande professor) of Computer Science
      Senior researcher at the Informatics Research Centre and
      Skövde Artificial Intelligence Lab

      Issues

      Research projects

      Research students

      • Main supervisor of research student Niclas Ståhl.
      • Main supervisor of research student Rakesh Rana (associated from University of Limerick).
      • Main supervisor of industrial research student Ulrika Ohlander (Saab AB, Linköping).
      • Main supervisor of research students Rikard Laxhammar (Saab AB, Järfälla) and Tove Helldin.
      • Co-supervisor of research student Tina Erlandsson (Saab AB, Linköping).
      • Former main supervisor of research students Maria Riveiro, Ph.D. March 17, 2011, Fredrik Johansson, Ph.D. December 1, 2010, and Marie Gustafsson, Ph.D. June 15, 2009.
        Former co-supervisor of research students Christoffer Brax, Ph.D. September 19, 2011, Hajar Kashfi (Chalmers University of Technology), Ph. licentiate June 9, 2011, and Anders Dahlbom, Ph.D. February 7, 2011.

      Recent publications

      Bae, J., Helldin, T., Riveiro, M., Ventocilla, E. and Falkman, G. (2017) Evaluating Multi-Attributes on Cause and Effect Relationship Visualization. Accepted for oral presentation and full paper publication at the 8th International Conference on Information Visualization Theory and Applications (IVAPP 2017), Porto, Portugal, 27 February–1 March, 2017.

      Ohlander, U., Alfredson, J., Riveiro, M. and Falkman, G. (2016) A Teamwork Model For Fighter Pilots. In Harris, D. (Ed.) Engineering Psychology and Cognitive Ergonomics. Applications and Services, Lecture Notes in Computer Science 9736, pp 221–230. Springer International Publishing.

      Ohlander, U., Alfredson, J., Riveiro, M. and Falkman, G. (2016) Elements of Team Effectiveness: A Qualitative Study with Pilots. In Proceedings of the IEEE 6th International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA 2016), 21–27 March 2016, San Diego, USA, pp 14–20. IEEE Computer Society.

      Helldin, T., Riveiro, R., Pashami, S., Falkman, G., Byttner, S. and Nowaczyk, S. (2016) Supporting Analytical Reasoning: A study from the automotive industry. In Yamamoto, S. (Ed.) Human Interface and the Management of Information: Applications and Services, Lecture Notes in Computer Science 9735, pp 20–31. Springer International Publishing.

      Ohlander, U., Alfredson, J., Riveiro, M. and Falkman, G. (2016) User Participation in the Design of Cockpit Interfaces. In Advances in Ergonomics Modeling, Usability & Special Populations, Advances in Intelligent Systems and Computing 486, pp 51–58. Springer International Publishing.

      Research

      2024

      Koen Vellenga, H. Joe Steinhauer, Göran Falkman, Tomas Björklund

      Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

      2024. Conference paper. Open Access

      2023

      Koen Vellenga, Alexander Karlsson, H. Joe Steinhauer, Göran Falkman, Anders Sjögren

      ICMLC 2023: Proceedings of 2023 15th International Conference on Machine Learning and Computing, Zhuhai, China, February 17-20, 2023

      2023. Conference paper. https://doi.org/10.1145/3587716.3587758 Open Access

      2022

      Koen Vellenga, H. Joe Steinhauer, Alexander Karlsson, Göran Falkman, Asli Rhodin, Ashok Chaitanya Koppisetty

      IEEE Open Journal of Intelligent Transportation Systems

      2022. Article, review. https://doi.org/10.1109/ojits.2022.3197296 Open Access

      2020

      Juhee Bae, Tove Helldin, Maria Riveiro, Slawomir Nowaczyk, Mohamed-Rafik Bouguelia, Göran Falkman

      ACM Computing Surveys

      2020. Article. https://doi.org/10.1145/3340960 Open Access

      Niclas Ståhl, Göran Falkman, Alexander Karlsson, Gunnar Mathiason

      Information Processing and Management of Uncertainty in Knowledge-Based Systems: 18th International Conference, IPMU 2020, Lisbon, Portugal, June 15–19, 2020, Proceedings, Part I

      2020. Conference paper. https://doi.org/10.1007/978-3-030-50146-4_41

      2019

      Juhee Bae, Göran Falkman, Tove Helldin, Maria Riveiro

      Data science in Practice

      2019. Chapter in book. https://doi.org/10.1007/978-3-319-97556-6_8

      Anders Holst, Mohamed-Rafik Bouguelia, Olof Görnerup, Sepideh Pashami, Ahmad Al-Shishtawy, Göran Falkman, Alexander Karlsson, Alan Said, Juhee Bae, Šarunas Girdzijauskas, Sławomir Nowaczyk, Amira Soliman

      CEUR Workshop Proceedings

      2019. Conference paper. Open Access

      Ulrika Ohlander, Jens Alfredson, Maria Riveiro, Göran Falkman

      Ulrika Ohlander, Jens Alfredson, Maria Riveiro, Göran Falkman

      Advances in Human Aspects of Transportation: Proceedings of the AHFE 2018 International Conference on Human Factors in Transportation, July 21–25, 2018, Loews Sapphire Falls Resort at Universal Studios, Orlando, Florida, USA

      2019. Conference paper. https://doi.org/10.1007/978-3-319-93885-1_1

      Niclas Ståhl, Göran Falkman, Alexander Karlsson, Gunnar Mathiason, Jonas Boström

      Journal of Chemical Information and Modeling

      2019. Article. https://doi.org/10.1021/acs.jcim.9b00325

      Ongoing projects

      BIO-AID - Biomedical AI-driven data analytics

      Artificial intelligence (AI) is an important driving force that is rapidly transforming health care and pharmaceutical industries in several ways. The vast amount of biomedical data available today poses unique opportunities to develop a repertoire of AI-based models. Although the results from studies using AI for solving biomedical problems are encouraging, there are numerous scientific challenges associated with AI for life science applications that need to be addressed.

      October 2020 - September 2024 Systems Biology

      Finished projects

      Intention recognition for real-time automotive 3D situation awareness

      Intention recognition is the task of inferring an agent´s intention based on its previous actions. It is crucial for human social intelligence which in turn enables understanding of, and for the ability to predict, other humans´ behaviours, such as for example other drivers´ intent to overtake, stop, turn, or switch lanes. For making situation-based decisions, both autonomous and human drivers need to take the intentions of surrounding vehicles into account. This is especially true in a mix of autonomous and human drivers.

      January 2019 - December 2022 Informatics

      Teamwork through Interaction with Air Systems

      The project will study design elements of future air systems that offer cognitive support for increased team effectiveness. The project will investigate how the design of complex systems can benefit from taking the teamwork perspective.

      November 2019 - February 2022 Informatics

      Swedish Metal

      The project will create new values for the Swedish metal industry. This will be done through the use and development of recent data analysis techniques. By doing so, one will find currently hidden relationships between known and unknown process parameters and the resulting product quality.

      October 2018 - October 2021 Informatics

      Decision support system warns of elevated levels in cereals

      Fusarium attacks on Swedish cereals in recent years have attracted increasing attention. While these attacks can lead to reduced harvests, the most serious effect is that this fungus can produce toxins. EU legislation has defined limit values for the content of Fusarium toxins because they are harmful to both humans and animals. Our project aims to develop a farm-based decision support system that will assess the risk of Fusarium attacks and elevated levels of deoxynivalenol (DON) in cereals. It can be used by both advisers/consultancies and farmers.

      January 2018 - June 2020 Informatics

      A smarter society through Big Data analytics

      An unprecedented growth of data, fed by novel technologies, user behaviour and business models, is one of the most dramatic and important developments in both ICT and society at large. Most of this is Big Data, characterised by vast volume, high velocity, large variety and unknown veracity. These properties pose significant challenges when collecting, managing and processing data.

      January 2015 - January 2020 Informatics

      BISON: Better decisions through Big Data

      Big data has gained much interesting in recent years due to the rapid expansion of the massive amount of data that is available for solving different types of tasks within many different application domains. However, today's big data is still on a fairly low level of abstraction when it comes to complex decision support tasks, subject to e.g. high dimensionality and significant portions of uncertainty regarding which patterns to look for in the data.

      October 2015 - September 2019 Informatics
      Published: 1/9/2020
      Edited: 1/9/2020
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