Scope
Abstract: This Special Session continues a series of successful editions devoted to the latest developments and emerging challenges in fuzzy modeling for edge computing. Fuzzy modeling provides a powerful paradigm for representing uncertainty, vagueness, and partial truth, which are intrinsic to real-world data processed at the network edge. Unlike traditional crisp approaches, fuzzy logic-based systems offer flexible reasoning and adaptive decision-making capabilities, enabling efficient, fast, and reliable data analysis directly within edge architectures. Such models enhance robustness against noise and imprecision, facilitate intelligent feature extraction, and can be seamlessly integrated with other computational intelligence techniques. This session aims to emphasize the growing importance of novel fuzzy models and hybrid fuzzy systems designed for data processing on end devices such as sensors, IoT nodes, and smartphones.
Aims and scope: The purpose of this Special Session is to encourage research and innovation in the fields of fuzzy modeling for edge computing. We are particularly interested in works that address both theoretical advances and practical applications, including integration with state-of-the-art edge and IoT technologies. Contributions may highlight novel architectures, hybrid approaches combining fuzzy logic with neural networks or evolutionary algorithms, as well as case studies demonstrating real-world deployments. The call includes, but is not limited to, the following topics:
- Fuzzy models of I, II or III type,
- Data clustering techniques on the end-user side,
- Architectures and models of fuzzy controllers operating on data obtained from IoT system sensors,
- Data visualization and interpretation using fuzzy processing tools,
- Applications of fuzzy models in mobile applications, automation control, federated learning, etc.
- Interoperability and integration of fuzzy controllers,
- Fuzzy models of clustering techniques, feature extractors in processing and analyzing multimodal data,
- Integration of fuzzy decision-making with real-time control in robotics and autonomous systems
- Fuzzy logic in cybersecurity and anomaly detection for IoT,
- Explainability and interpretability of fuzzy models in edge AI,
- Agent operations in edge computing based on fuzzy models.
Author Submission Information
Detailed submission instructions and system information will be provided at a later time.
Important Dates
- Paper submission deadline 31 January 2026: (23:59, anywhere on Earth, i.e. UTC-12)
- Notification: 15 March 2026
- Camera-ready: 15 April 2026
- Conference: 21–26 June 2026
Co-Chairs Biography
Prof. Dawid Połap: (Member, IEEE) received the M.Sc. degree in applied mathematics (with honors) from the Silesian University of Technology, Gliwice, Poland, in 2017, and the Ph.D. degree in 2019 and the D.Sc. (habilitation) degree in 2025, both from the Czestochowa University of Technology, Czestochowa, Poland. He is a Professor and Head of the Department of Artificial Intelligence Modeling at the Faculty of Applied Mathematics, Silesian University of Technology, Gliwice, Poland. He has authored and co-authored more than 150 research papers in international journals and conferences. His main research interests include image processing, intelligent computing, and various aspects of machine learning. Prof. Połap was awarded by the Polish Ministry of Science and Higher Education with a Diamond Grant for the most talented students and a scholarship for exceptional young scientists. He serves as an Editor for Applied Soft Computing, Expert Systems with Applications, Sensors, Evolutionary Intelligence, and several other journals.
Prof. Stefania Tomasiello: (Associate professor of computer science (SSD INF/01 in Italy) at the University of Salerno since October 2023. Responsible for the course Fuzzy Logic and Soft Computing (6 ECTS) at the University of Tartu. She was formerly an Associate Professor of Intelligent Systems at the University of Tartu (Institute of Computer Science, Chair of Data Science, Machine Learning Group) and previously, a permanent researcher with CO.RI.SA. (Research Consortium on Agent Systems), University of Salerno. Work-package leader in several funded projects and expert evaluator (ex-ante and ex-post) of applied research projects for the Italian Ministry of Economic Development and, formerly, the Italian Ministry of University and Research. She has been the principal investigator for the University of Tartu in the ERA-NET project “ConnectFarms”. She serves several indexed journals as an associate editor, such as IEEE Transactions on Neural Networks and Learning Systems, a premier journal in the field. She is Co-Editor in Chief of Evolutionary Intelligence (Springer, WoS, Scopus indexed). Senior IEEE member and senior INNS member. INNS Board of Governors 2025-2027. Currently supervising three PhD students. Italian scientific qualification (ASN) as full professor of computer science.
Prof. Gautam Srivastava: (Senior Member, IEEE) received his M.Sc. and Ph.D. in Computer Science from the University of Victoria, Canada, in 2006 and 2012, respectively. He is a Professor of Computer Science at Brandon University, Canada. In his 10-year academic career, he has published a total of 400 papers in high-impact conferences in many countries and high-status journals (SCI, SCIE). He is an Editor of several international scientific research journals, including IEEE Transactions on Industrial Informatics, IEEE Transactions on Computational Social Systems, and IEEE Internet of Things Journal.