My research spans data science, self-organizing systems, artificial intelligence, cognitive robotics, and philosophy. Below is a list of my publications. See my Google Scholar profile for citations and additional details.
Johnsson, M., Shahbazi, Z., Tarlani, R., and Frisk, F. (2026). Patch-Shared Hierarchical SOM for Unsupervised Image Classification. Accepted to the International Conference on Big Data, AI, and Analytics 2026 (ICBDAIA'26), Valencia, Spain.
Zahid, N., Sodhro, A.H., Pibhulal, S., Johnsson, M., Hassan, M.A., Djebbar, F., and Granelli, F. (2026). AI-Enabled Adaptive PHY-Layer Authentication for Integrated TN-NTN IoT-5G Healthcare. Accepted to IEEE ICC 2026.
Das, B., Ali, N., Siyal, F., Pirbhulal, S., Sodhro, A.H., and Johnsson, M. (2026). Distributed Federated Generative-AI Field Learning for Synthetic Sensing in 6G Vehicular Networks. 2026 IEEE Wireless Communications and Networking Conference Workshops (WCNCW).
Mughal, M.I.Y., Sodhro, A.H., and Johnsson, M. (2025). A Systematic Review of Experimentally Validated Authentication Schemes for 5G/6G Smart Healthcare Edge Devices. SUNRISE 2025 at NIKT 2025, Halden, Norway.
Ali, N., Aloi, G., Gravina, R., Johnsson, M., Sodhro, A.H., and Fortino G. (2025). Communication-Efficient Federated Learning via Feature-Aware Task Offloading for Heterogeneous Edge Networks. In the proceedings of IEEE Globecom 2025, Taipei, Taiwan.
Sarkheyli-Hägele, A., Sarkheyli, A., Sarkheyli, E., Shahbazi, Z., and Johnsson, M. (2025). An Interactive and Adaptive AI-based Decision Support System for Dynamic Risk Management in Megaprojects. In the proceedings of FLTA 2025, Dubrovnik, Croatia.
Shahbazi, Z., and Johnsson, M. (2025). Incentive Mechanism Design Based on Blockchain and Federated Learning for Honest Participation. In the proceedings of the 7th International Conference on Blockchain Computing and Applications (BCCA 2025), Dubrovnik, Croatia.
Soulaimani, A., Schwaiger, C., Khoshkangini, R., Johnsson, M., and Ebner, T. (2025). Transformers to Predict Embryo Quality Using Images and External Factors. In the proceedings of SAIS 2025, Halmstad, Sweden.
Sandelius, C., Pappas, A., Sarkheyli-Hägele, A., Heuer, A., and Johnsson, M. (2024). Leveraging Deep Learning for Approaching Automated Pre-Clinical Rodent Models. In Proceedings of the 16th International Conference on Computational Intelligence - NCTA, ISBN 978-989-758-721-4, ISSN 2184 - 3236, SciTePress, 613-620. DOI: 10.5220/0013065600003837.
Khoshkangini, R., Mangrio, E., and Johnsson, M. (2024). Enhancing In Vitro Fertilization with Environment Optimization Utilizing Artificial Intelligence (EIVF-AI). In the proceedings of EAI Pervasive Health 2024, Heraklion, Crete, Greece.
González-Lama, J., Montoro, A., Espinilla, M., Valera, J.C., Gil, D., Peral, J., and Johnsson, M. (2023). New trends in machine learning techniques for human activity recognition using multimodal sensors. International Conference on Ubiquitous Computing and Ambient Intelligence 2023, 94-99.
Valera, J.C., Gil, D., Peral, J., and Johnsson, M. (2023). New Trends in Machine Learning Techniques for Human Activity Recognition Using Multimodal Sensors. Proceedings of the 15th International Conference on Ubiquitous Computing 2023.
Surie D., and Johnsson, M. (2023). The Design of Personalised, Experiential Learning Infrastructure Centred On Human Cognition and Emerging Pedagogical Trends. 6th World Conference on Future of Education, Milan, Italy, 19-21 May 2023.
Johnsson, M. (2023). Artificiell intelligens & mänsklig hjärna. In Neurologi i Sverige, 4 - 2023.
Johnsson, M. (2022). Perceptions, Imagery, Memory and Consciousness. In the Polish Journal of Science and Philosophy. Philosophical and Interdisciplinary Studies.
Johnsson, M. (2022). Perceptions, Imagery, Memory and Consciousness in Man and Machine. In the Proceedings of The 2021 Summit of the International Society for the Study of Information.
Gil, D., Johnsson, M., Szymanski, J., Peral, J., and Tanniru, M. (2021). Architecture Based on Machine Learning Techniques and Data Mining for Prediction of Indicators in the Diagnosis and Intervention of Autistic Spectrum Disorder. The International Research & Innovation Forum, 133-140.
Polo-Rodriguez, A., Medina-Quero, J., Johnsson, M., Gil, D.,and Navarro I. (2021). A Mobile Application with Geolocation and Virtual Rewards for Promoting Social Skills in People with Social Disorders. The International Research and Innovation Forum, 79-87.
Kock, E., Sarwari, Y., Russo, N., and Johnsson, M. (2021). Identifying cheating behaviour with machine learning. In the proceedings of SAIS 2021, Luleå, Sweden.
Johnsson, M. (2019). Conscious Machine Perception. APA Newsletter on Philosophy and Computers, 18, 2, 10-15.
Gil, D., Johnsson, M., Mora, H. and Szymanski, J. (2019). Advances in Architectures, Big Data, and Machine Learning Techniques for Complex Internet of Things Systems. Complexity, vol 2019.
Gil, D., Johnsson, M., Mora, H. and Szymanski, J. (2019). Review of the Complexity of Managing Big Data of the Internet of Things. Complexity, vol 2019.
Buonamente, M., Dindo, H., Chella, A. and Johnsson, M. (2018). Simulating Music with Associative Self-Organizing Maps. Journal of Biologically Inspired Cognitive Architectures.
Buonamente, M., Dindo, H., Chella, A. and Johnsson, M. (2018). Simulating Music with Associative Self-Organizing Maps. In the proceedings of BICA 2018, Prague, Czech Republic.
Mora, H., Signes-Pont, M.T., Gil, D. and Johnsson, M. (2018). Collaborative working architecture for IoT-based applications. Sensors, 18, 6: 1676.
Gharaee, Z., Gärdenfors, P. and Johnsson, M. (2017). Online Recognition of Actions Involving Objects. Journal of Biologically Inspired Cognitive Architectures, 22, 10-19.
Gharaee, Z., Gärdenfors, P. and Johnsson, M. (2017). Online Recognition of Actions Involving Objects. In the proceedings of BICA 2017, Moscow, Russian Federation.
Gharaee, Z., Gärdenfors, P. and Johnsson, M. (2017). First and Second Order Dynamics in a Hierarchical SOM system for Action Recognition. Applied Soft Computing, 59, 574-585.
Gharaee, Z., Gärdenfors, P. and Johnsson, M. (2017). Hierarchical Self-Organizing Maps System for Action Classification. In the proceedings of the 9th International Conference on Agents and Artificial Intelligence (ICAART 2017), Porto, Portugal.
Gharaee, Z., Gärdenfors, P. and Johnsson, M. (2016). Action Recognition Online with Hierarchical Self-Organizing Maps. In the proceedings of the 12th International Conference on Signal-Image Technology and Internet-Based Systems (SITIS 2016), Naples, Italy, 538-544.
Buonamente, M., Dindo, H. and Johnsson, M. (2016). Hierarchies of Self-Organizing Maps for Action Recognition. Cognitive Systems Research.
Buonamente, M., Dindo, H. and Johnsson, M. (2015). Discriminating and Simulating Actions with the Associative Self-Organizing Map. Connection Science.
Gil, D., Garcia, J., Cazorla, M. and Johnsson, M. (2014). SARASOM - A Supervised Architecture based on the Recurrent Associative SOM. Neural Computing and Applications.
Buonamente, M., Dindo, H. and Johnsson, M. (2014). Action Recognition based on Hierarchical Self-Organizing Maps. In the proceedings of the International Workshop on Artificial Intelligence and Cognition (AIC 2014), Turin, Italy.
Buonamente, M., Dindo, H. and Johnsson, M. (2013). Simulating Actions with the Associative Self-Organizing Map. In the proceedings of the International Workshop on Artificial Intelligence and Cognition (AIC 2013), Turin, Italy.
Buonamente, M., Dindo, H. and Johnsson, M. (2013). Recognizing Actions with the Associative Self-Organizing Map. In the proceedings of the 24th International Conference on Information, Communication and Automation Technologies (ICAT 2013), Sarajevo, Bosnia and Herzegovina.
Girela, J.L., Gil, D., Johnsson, M., Gomez-Torres, M.J., and De Juan, J. (2013). Semen Parameters Can Be Predicted from Environmental Factors and Lifestyle Using Artificial Intelligence Methods. Biology of Reproduction.
Johnsson, M. (2012). (Ed.) Applications of Self-Organizing Maps, InTech. ISBN: 978-953-51-0862-7.
Johnsson, M., and Buonamente, M. (2012). Internal Simulation of an Agent`s Intentions. Proceedings of the Biologically Inspired Cognitive Architectures 2012, Palermo, Italy. 175-176, Springer, ISBN: 978-3-642-34273-8.
Buonamente, M., and Johnsson, M. (2012). Architecture to Serve Disabled and Elderly. Proceedings of the Biologically Inspired Cognitive Architectures 2012, Palermo, Italy. 365-366, Springer, ISBN: 978-3-642-34273-8.
Gil, D., Girela, J.L., De Juan, J., Gomez-Torres, M.J., and Johnsson, M. (2012). Predicting seminal quality with Artificial Intelligence methods. Journal of Expert Systems With Applications, 39, 16, 12564 - 12573, ISSN 0957 - 4174.
Viejo, D., Garcia, J., Cazorla, M., Gil, D. and Johnsson, M. (2012). Using GNG to improve 3D features extraction - Application to 6DoF Egomotion. Neural Networks, 32, 138-146, ISSN 0893 - 6080.
Johnsson, M. and Gil, D. (2011). Internal Simulation of Perceptions and Actions. In From Brains to Systems: Brain-Inspired Cognitive Systems 2010, 87-100, Springer, ISBN 978-1-4614-0163-6.
Viejo, D., Garcia, J., Cazorla, M., Gil, D. and Johnsson, M. (2011). Using 3D GNG-Based Reconstruction for 6DoF Egomotion. Proceedings of the International Joint Conference on Neural Networks (IJCNN) 2011, San Jose, California, USA. 1207-1213. ISBN: 978-1-4244-9636-5.
Gil, D., Garcia, J., Cazorla, M. and Johnsson, M. (2011). Predictions Tasks with Words and Sequences: Comparing a Novel Recurrent Architecture with the Elman Network. Proceedings of the International Joint Conference on Neural Networks (IJCNN) 2011, San Jose, California, USA. 1042-1048. ISBN: 978-1-4244-9636-5.
Gil, D. and Johnsson, M. (2011). Support vector machines in medical classification tasks. In Brandon H. Boyle (ed), Support Vector Machines: Data Analysis, Machine Learning and Applications, Nova Science Publishers, Inc., ISBN 978-1-61209-342-0.
Gil Mendez, D., Johnsson, M., Garcia Chamizo, J.M., Soriano Paya, A., and Ruiz Fernandez, D. (2011). Modelling of urological dysfunctions with neurological etiology by means of their centres involved. Applied Soft Computing, 11, 4448 - 4457.
Johnsson, M. and Balkenius, C. (2011). Sense of Touch in Robots with Self-Organizing Maps. IEEE Transactions on Robotics, 27, 3, 498-507.
Johnsson, M., Balkenius, C. and Hesslow, G. (2011). Multimodal System Based on Self-Organizing Maps. In Madani, K., Correia, A.D., Rosa, R., and Filipe, J. (Eds.) Studies in Computational Intelligence, 343, 251-263, Springer, ISBN 978-3-642-20205-6.
Johnsson, M., Gil, D., Hesslow, G. and Balkenius C. (2011). Internal Simulation in a Bimodal System. In Kofod-Petersen, A., Heintz, F., and Langseth, H. (Eds.) Proceedings of the Scandinavian Conference on Artificial Intelligence (SCAI) 2011, Trondheim, Norway, IOS Press, 173-182. ISBN: 978-1-60750-753-6.
Johnsson, M., Martinsson, M., Gil, D. and Hesslow, G. (2011). Associative Self-Organizing Map. In Mwasiagi, J.I. (Ed), Self Organising Maps - Applications and Novel Algorithm Design, InTech, 603-626. ISBN: 978-953-307-546-4.
Gil Mendez, D., Johnsson, M., Garcia Chamizo, J.M., Soriano Paya, A., and Ruiz Fernandez, D. (2010). Decision support system for the diagnosis of urological dysfunctions based on fuzzy logic. In Ponce de Leon F. de Carvalho, A., Rodriguez-Gonzalez, S., De Paz, J.F., Corchado, J.M. (Eds.), Proceedings of the International Symposium on Distributed Computing and Artificial Intelligence 2010 (DCAI 2010), Springer-Verlag, 425-433. ISBN: 978-3-642-14882-8.
Johnsson, M., Gil, D., Balkenius, C. and Hesslow, G. (2010). Supervised Architectures for Internal Simulation of Perceptions and Actions. In Hernandez, C., Gomez, J., and Sanz, R. (Eds.) Proceedings of Brain Inspired Cognitive Systems (BICS) 2010, Madrid, Spain. ISBN 978-84-614-1870-1 / 978-84-614-1869-5.
Gil, D., and Johnsson, M. (2010). Supervised SOM Based Architecture versus Multilayer Perceptron and RBF Networks. In Bol, R. (Ed.) Proceedings of SAIS 2010, Uppsala, Sweden. 15-24.
Johnsson, M., and Balkenius, C. (2010). Haptic Perception with Self-Organizing ANNs and an Anthropomorphic Robot Hand. Journal of Robotics, vol. 2010, Article ID 860790, 9 pages.
Gil Mendez, D., and Johnsson, M. (2010). Using Support Vector Machines in Diagnoses of Urological Dysfunctions. Journal of Expert Systems With Applications, 37, 6, 4713 - 4718.
Balkenius, C., Morén, J., Johansson, B and Johnsson, M. (2010). Ikaros: Building Cognitive Models for Robots. Advanced Engineering Informatics, 24, 1, 40-48. ISSN: 1474 - 0346.
Johnsson, M., Balkenius, C., and Hesslow, G. (2009). Neural Network Architecture for Crossmodal Activation and Perceptual Sequences. Papers from the AAAI Fall Symposium (Biologically Inspired Cognitive Architectures) 2009, Arlington, Virginia, USA. 85-86.
Johnsson, M., Balkenius, C., and Hesslow, G. (2009). Associative Self-Organizing Map. In the proceedings of the International Joint Conference on Computational Intelligence (IJCCI) 2009, Funchal, Madeira, Portugal, 363-370.
Gil Mendez, D., and Johnsson, M. (2009). Diagnosing Parkinson by using artificial neural networks and support vector machines. Global Journal of Computer Science and Technology, 1.2, 63-71.
Johnsson, M., and Balkenius, C. (2009). Experiments with Self-Organizing Systems for Texture and Hardness Perception. Global Journal of Computer Science and Technology, 1.2, 53-62.
Gil Mendez, D., Johnsson, M., Garcia Chamizo, J.M., Soriano Paya, A., and Ruiz Fernandez, D. (2009). Application of artificial neural networks in the diagnosis of urological dysfunctions. Journal of Expert Systems With Applications, 36, 5754 - 5760.
Johnsson, M. (2009). Sense of Touch in Robots. An investigation into how a sense of touch could be implemented in robots. PhD thesis from the Dept. of Cognitive Science, Lund University.
Balkenius, C., Johnsson, M. and Johansson, B. (2008). Understanding Cognition by Building Robots. In Gärdenfors, P. and Wallin, A. (Eds). A Smorgasbord of Cognitive Science, Nya Doxa, 99-112. ISBN: 978-91-578-0532-4.
Balkenius, C., Morén, J., Johansson, B. and Johnsson, M. (2008). Ikaros: Building Cognitive Models for Robots. In Hülse, M. and Hild, M. (Eds). Workshop on current software frameworks in cognitive robotics integrating different computational paradigms (in conjunction with IROS 2008), Nice, France, 47-54.
Johnsson, M., and Balkenius, C. (2008). Recognizing Texture and Hardness by Touch. In Proceedings of the 2008 IEEE International Conference on Intelligent Robots and Systems (IROS 2008), Nice, France, 482-487.
Johnsson, M., and Balkenius, C. (2008). Associating SOM Representations of Haptic Submodalities. In Ramamoorthy, S. and Hayes, G. M. (Eds.) Towards Autonomous Robotic Systems 2008, The University of Edinburgh, Edinburgh, UK, 124-129.
Johnsson, M., Gil Mendez, D., and Balkenius, C. (2008). Touch Perception with SOM, Growing Cell Structures and Growing Grids. In Ramamoorthy, S. and Hayes, G. M. (Eds.) Towards Autonomous Robotic Systems 2008, The University of Edinburgh, Edinburgh, UK, 79-85.
Gil Mendez, D., Johnsson, M., Soriano Paya, A., and Ruiz Fernandez, D. (2008). Artificial Neural Networks for Diagnoses of Dysfunctions in Urology. Proceedings of Healthinf 2008, Madeira, Portugal, 191-196.
Johnsson, M., & Balkenius, C. (2007). Experiments with Proprioception in a Self-Organizing System for Haptic Perception. In Wilson, M., S., Labrosse, F., Nehmzow, U., Melhuish, C., Witkowski, M. (Eds.) Towards Autonomous Robotic Systems 2007, University of Wales, Aberystwyth, UK, 239-245.
Balkenius, C., Johnsson, M., & Johansson, B. (2007). Explorations in Cognitive Robotics. In Löfström, T., Johansson, U., Sönströd, C., König, R. and Niklasson, L. (Eds.) Proceedings of SAIS 2007, University College of Borås, Borås, Sweden, 189-192.
Johnsson, M., & Balkenius, C. (2007). LUCS Haptic Hand III - An Anthropomorphic Robot Hand with Proprioception. LUCS Minor 13.
Johnsson, M., & Balkenius, C. (2007). Neural Network Models of Haptic Shape Perception. Journal of Robotics and Autonomous Systems, 55, 720-727.
Johnsson, M., & Balkenius, C. (2006). Haptic Perception with a Robotic Hand. In Honkela, T., Raiko, T., Kortela, J. and Valpola, H. (Eds.) Proceedings of the Ninth Scandinavian Conference on Artificial Intelligence (SCAI 2006), Helsinki University of Technology, Espoo, Finland, 127-134.
Johnsson, M., & Balkenius, C. (2006). A Robot Hand with T-MPSOM Neural Networks in a Model of the Human Haptic System. In Witkowski, M., Nehmzow, U., Melhuish, C., Moxey, E. and Ellery, A. (Eds.) Towards Autonomous Robotic Systems 2006, Surrey University, Guildford, UK, 80-87.
Johnsson, M., & Balkenius, C. (2006). LUCS Haptic Hand II. LUCS Minor, 9.
Johnsson, M., & Balkenius, C. (2006). Experiments with Artificial Haptic Perception in a Robotic Hand. Journal of Intelligent and Fuzzy Systems, 17, 4, 377-385.
Johnsson, M., Pallbo, R., & Balkenius, C. (2005). A Haptic System for the LUCS Haptic Hand I. In Mira, J., and Alvarez, J.R. (Eds.), Mechanisms, Symbols, and Models Underlying Cognition: First International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2005, Las Palmas, Canary Islands, Spain, June 15-18, 2005, Proceedings, Part I, 386-395. Springer-Verlag.
Johnsson, M., Pallbo, R., & Balkenius, C. (2005). Experiments with Haptic Perception in a Robotic Hand. In Funk, P., Rognvaldsson, T., and Xiong, N. (Eds.) Advances in Artificial Intelligence in Sweden, Västerås, Sweden: Mälardalen University, 81-86.
Johnsson, M. (2005). LUCS Haptic Hand I – Technical Report. LUCS Minor, 8.
Johnsson, M. (2004). Cortical Plasticity – A Model of Somatosensory Cortex. A study of cortical reorganization, after nerve injuries between the hand and the brain, with the aid of computational models. MSc thesis from the Dept. of Cognitive Science, Lund University.
Johnsson, M. (2003). Force feedback and cyber sickness in virtual reality. Examinations of force feedback usability in virtual reality, and cyber sickness in virtual environments. MSc thesis from the Dept. of Computer Science, Lund University. (Swedish with English summary).