Johan Hagelbäck

Senior Lecturer in Computer Science with a specialty in artificial intelligence and machine learning. My research is about applying AI, mainly machine learning, on different application areas in academia and industry.

Teaching

Program manager for Högskoleingenjör i Mjukvaruteknik. Examiner for degree projects at bachelor level in computer science.

Publications

Article in journal (Refereed)

Golub, K., Hagelbäck, J., Ardö, A. (2020). Automatic Classification of Swedish Metadata Using Dewey Decimal Classification : A Comparison of Approaches. Journal of Data and Information Science. 5. 18-38.
Jercic, P., Hagelbäck, J., Lindley, C. (2019). An affective serious game for collaboration between humans and robots. Entertainment Computing. 32. 1-10.
Jercic, P., Wen, W., Hagelbäck, J., Sundstedt, V. (2018). The Effect of Emotions and Social Behavior on Performance in a Collaborative Serious Game Between Humans and Autonomous Robots. International Journal of Social Robotics. 10. 115-129.
Hagelbäck, J. (2016). Hybrid pathfinding in StarCraft. IEEE Transactions on Computational Intelligence and AI in Games. 8. 319-324.
Togelius, J., Preuss, M., Beume, N., Wessing, S., Hagelbäck, J., et al. (2013). Controllable procedural map generation via multiobjective evolution. Genetic Programming and Evolvable Machines. 14. 245-277.
Hagelbäck, J., Johansson, S.J. (2009). A Multiagent Potential Field-Based Bot for Real-Time Strategy Games. International Journal of Computer Games Technology. 2009.

Conference paper (Refereed)

Hagelbäck, J., Lincke, A., Löwe, W., Rall, E. (2019). On the Agreement of Commodity 3D Cameras. Proceedings of the 2019 International Conference on Image Processing, Computer Vision, & Pattern Recognition. 36-42.
Kastrati, Z., Kurti, A., Hagelbäck, J. (2019). The Effect of a Flipped Classroom in a SPOC : Students' Perceptions and Attitudes. ICETC 2019: Proceedings of the 2019 11th International Conference on Education Technology and Computers. 246-249.
Hagelbäck, J., Liapota, P., Lincke, A., Löwe, W. (2019). Variants of Dynamic Time Warping and their Performance in Human Movement Assessment. 21st International Conference on Artificial Intelligence (ICAI'19: July 29 - August 1, 2019, Las Vegas, USA). 9-15.
Golub, K., Hagelbäck, J., Ardö, A. (2019). Automatic subject classification of Swedish DDC : Impact of tuning and training data set. 19th European NKOS Workshop, 23rd TPDL : Oslo, 12 September 2019.
Hagelbäck, J., Liapota, P., Lincke, A., Löwe, W. (2019). The performance of some machine learning approaches in human movement assessment. 13th Multi Conference on Computer Science and Information Systems (MCCSIS). 35-42.
Qureshi, S., Hagelbäck, J., Iqbal, S.M.Z., Javaid, H., Lindley, C. (2018). Evaluation of Classifiers for Emotion Detection while Performing Physical and Visual Tasks : Tower of Hanoi and IAPS. Intelligent Systems and Applications. IntelliSys 2018 : Proceedings of the 2018 Intelligent Systems Conference (IntelliSys) Volume 1. 347-363.
Golub, K., Hagelbäck, J., Ardö, A. (2018). Automatic classification using DDC on the Swedish Union Catalogue. Proceedings of the 18th European Networked Knowledge Organization Systems (NKOS 2018) Workshop, Porto, Portugal, September 13, 2018. 4-16.
Jerčić, P., Hagelbäck, J., Lindley, C. (2018). Physiological Affect and Performance in a Collaborative Serious Game Between Humans and an Autonomous Robot. Entertainment Computing – ICEC 2018 : 17th IFIP TC 14 International Conference, Held at the 24th IFIP World Computer Congress, WCC 2018, Poznan, Poland, September 17–20, 2018. 127-138.
Sohaib, A.T., Qureshi, S., Hagelbäck, J., Hilborn, O., Jercic, P. (2013). Evaluating classifiers for Emotion Recognition using EEG. Foundations of Augmented Cognition : 7th International Conference, AC 2013, Held as Part of HCI International 2013, Las Vegas, NV, USA, July 21-26, 2013. Proceedings. 492-501.
Preuss, M., Kozakowski, D., Hagelbäck, J., Trautmann, H. (2013). Reactive Strategy Choice in StarCraft by Means of Fuzzy Control. 2013 IEEE Conference on Computational Intelligence in Games (CIG). 1-8.
Hagelbäck, J. (2012). Potential-Field Based navigation in StarCraft. 2012 IEEE Conference on Computational Intelligence and Games (CIG). 388-393.
Togelius, J., Preuss, M., Beume, N., Wessing, S., Hagelbäck, J., et al. (2010). Multiobjective Exploration of the StarCraft Map Space. 2010 IEEE Symposium on Computational Intelligence and Games (CIG). 265-272.
Hagelbäck, J., Johansson, S.J. (2010). A Study on Human like Characteristics in Real Time Strategy Games. 2010 IEEE Symposium on Computational Intelligence and Games (CIG). 139-145.
Hagelbäck, J., Johansson, S.J. (2009). A Multi-agent Potential Field based bot for a Full RTS Game Scenario. .
Hagelbäck, J., Johansson, S.J. (2009). Measuring player experience on runtime dynamic difficulty scaling in an RTS game. IEEE Symposium on Computational Intelligence and Games, 2009 : CIG 2009. 46-52.
Hagelbäck, J., Johansson, S.J. (2008). Dealing with Fog of War in a Real Time Strategy Game Environment. IEEE Symposium On Computational Intelligence and Games, 2008. CIG '08. 55-62.
Hagelbäck, J., Johansson, S.J. (2008). Using Multi-Agent Potential Fields in Real-Time Strategy Games. Seventh International Conference on Autonomous Agents and Multi-agent Systems (AAMAS), 12-16, 2008, Estoril. 631-638.
Hagelbäck, J., Johansson, S.J. (2008). The Rise of Potential Fields in Real Time Strategy bots. Artificial Intelligence and Interactive Digital Entertainment (AIIDE), Stanford.
Davidsson, P., Hagelbäck, J., Svensson, K. (2005). Comparing approaches to predict transmembrane domains in protein sequences. ProceedingSAC '05 Proceedings of the 2005 ACM symposium on Applied computing. 185-189.

Chapter in book (Refereed)

Hagelbäck, J., Hilborn, O., Jercic, P., Johansson, S.J., Lindley, C.A., et al. (2014). Psychophysiological Interaction and Empathic Cognition for Human-robot Cooperative Work (PsyIntEC). Gearing Up and Accelerating Cross‐fertilization between Academic and Industrial Robotics Research in Europe : Technology Transfer Experiments from the ECHORD Project. Springer. 283-299.

Conference paper (Other academic)

Golub, K., Hagelbäck, J., Ardö, A. (2019). Automatic classification Using DDC on the Swedish Union Catalogue. European DDC Users Group, EDUG, Annual Meeting 9-10 May 2019 : National Library of Sweden, Stockholm, Sweden.
Hagelbäck, J., Johansson, S.J. (2008). Demonstration of Multi-agent Potential Fields in Real-time Strategy Game. Seventh International Conference on Autonomous Agents and Multi-agent Systems (AAMAS), May 12-16, 2008, Estoril. 1687-1688.

Doctoral thesis, monograph (Other academic)

Hagelbäck, J. (2012). Multi-Agent Potential Field based Architectures for Real-Time Strategy Game Bots. Doctoral Thesis. Karlskrona, Blekinge Tekniska Högskola.

Doctoral thesis, monograph (Other academic)

Hagelbäck, J. (2009). A Multi-Agent Potential Field Based Approach for Real-Time Strategy Game Bots. Licentiate Thesis. Karlskrona, Blekinge Tekniska Högskola. 81.