Stefanos Vrochidis

Centre for Research and Technology Hellas, Thessaloniki

Dr. Stefanos Vrochidis received the Diploma degree in Electrical Engineering from Aristotle University of Thessaloniki, Greece, the MSc degree in Radio Frequency Communication Systems from University of Southampton and the PhD degree in Electronic Engineering from Queen Mary University of London.  Currently, he is a Principle Researcher with the Information Technologies Institute of the Centre for Research and Technology Hellas (ITI-CERTH), the Head of the Multimodal Data Fusion and Analytics (M4D) Group and co-founder of Infalia and CDXi Solutions. His research interests include multimedia understanding and retrieval, multimodal fusion, computer vision, multimodal analytics, artificial intelligence, as well as industrial, media & arts, health, environmental and security applications. Dr.  Vrochidis has participated in more than 100 European and National projects (in more than 20 as project coordinator or Scientific/Technical Manager) and has been member of the organization team of several conferences and workshops. He has edited 3 books and authored more than 400 related scientific journal, conference and book chapter publications. He has served as a reviewer in several international Journals and as part of the Organizational and Technical program committee in well reputed conferences and workshops.
 

Title: AI-based Multimodal Analytics

Abstract: The rapid proliferation of heterogeneous data sources, from multimedia streams and social media to IoT sensor networks and satellite imagery, has driven the emergence of Artificial Intelligence-based multimodal analytics as a key paradigm for extracting knowledge across multiple domains and for diverse applications. This keynote presents recent advances in AI-based multimodal analytics, highlighting methods for integrating diverse data modalities to enable high-level understanding, event characterization, and predictive analytics. It will demonstrate how multimodal AI technologies leverage deep learning and foundation models to deliver robust, interpretable, and scalable solutions with social and environmental impact. The presentation will showcase applications across several domains including manufacturing and space, security, culture and arts, environmental monitoring and health.