Following the great successes of all the editions in Helsinki 2018, Annecy 2019, Rüdesheim 2021, Cadaques 2022, Porquerolles 2024 of the Statistical Learning for Signal and Image Processing (SLSIP) Workshop, we have decided to organize a new edition in the beautiful aera of Hanko, Finland (Travel informations are available here). This workshop is dedicated both to methodological aspects and application challenges. 

New statistical learning approaches, methods, theory and tools are urgently required to account for modern complex, dynamic and large-scale settings. For example, the transformation of our energy and communication networks necessitate the reliable extraction of information from large-scale dynamic sensor network settings. Further, biomedical signal processing and analysis, image reconstruction, detection and classification require advanced learning methods that provide reliable results with statistical guarantees and high robustness requirements. 

The main topics of this workshop concern statistical learning for robust signal processing and control, biomedical signal and image processing, statistical modelling of sparse, complex and multi-sensor data, graph theory for signal processing in dynamic and large-scale networks, and distributed optimization for smart systems with applications, such as, neuroscience, electric systems, array signal processing.