
Designed primarily for students and early-career researchers, SFLA 2025 offered an immersive learning experience through a rich schedule mixing lectures, discussions, and interactive student talks (https://sfla2025.eu/programme.html). The environment fostered collaboration and lively exchanges among participants and expert lecturers.
The week’s lectures spanned foundational concepts to advanced topics, delivered by leading experts in the field:
Juan José Miñana opened the school with “Introduction to Fuzzy Set Theory”, followed later by “Fuzzy Metrics I & II” across Thursday and Friday sessions.
Bernard De Baets presented a three-part series on relational calculus:
“Fuzzy Relations”
“Reciprocal Relations”
“Ternary Relations”.
Dmitry Gromov introduced participants to “Clustering and Classification in Data Science”.
Irina Perfiljeva offered two sessions:
“Neural Networks Enhanced by Fuzzy Modeling”
“Data-Driven Numerical Methods: Fuzzy Transforms Meet Physics-Informed Neural Networks”.
Gabriella Casalino discussed “Explainable Artificial Intelligence (with a focus on fuzzy logic)” and “Explaining Evolving Systems”.
Igor Rodin wrapped up with a two-part lecture on “From Algorithms to Impact: The Applied Landscape of AI”.
Beyond lectures, the summer school emphasized peer engagement—students from diverse backgrounds delivered short talks each afternoon. The week peaked with a round table and gala dinner on Wednesday, July 30, blending academic dialogue and social connection.
SFLA 2025 provided a comprehensive, well-rounded learning journey—balancing theoretical rigor, applied insights, and a vibrant community spirit. For the 18 participants—especially those from the University of Latvia—it was a rich opportunity to explore fuzzy logic frontiers and forge international academic bonds.