Research in the "Artificial Intelligence and machine learning" and related fields focuses on the following: (a) novel algorithms, methodologies, and theoretical results in the foundations of these areas (b) novel engineering solutions, platforms, and applications of AI and machine learning to specific domains of interest, and (c) the construction of related systems, libraries, and software to support the community. Indicative research problems fall in the areas of feature selection, causal discovery, automated machine learning, self-supervised/unsupervised learning, few-shot and annotation-efficient learning, large scale optimization, foundations of deep learning, inference and learning of graphical model etc. Our faculty members continuously update and adjust their research directions and list of research problems to focus on the most current and novel topics.

• Αντώνης Αργυρός
• Νικόλαος Κομοντάκης
• Δημήτρης Πλεξουσάκης
• Ιωάννης Στυλιανού
• Πάνος Τραχανιάς
• Γρηγόριος Τσαγκατάκης
• Παναγιώτης Τσακαλίδης
• Ιωάννης Τσαμαρδίνος