Keynote Speakers
Keynote Speakers
TBA
Professor Marios M. Polycarpou
Professor, Department of Electrical and Computer Engineering, University of Cyprus
Advisory Board Chair, KIOS Research and Innovation Center of Excellence
Honorary Professor of Imperial College London, U.K.
Member of the Cyprus Academy of Sciences, Letters, and Arts
Member of Academia Europaea (The Academy of Europe)
Title: Connecting AI to the Cyber-Physical World
Abstract: The development of cyber-physical systems with multiple sensor/actuator components and feedback loops has given rise to advanced automation applications, including energy and power, intelligent transportation, water systems, manufacturing, etc. Traditionally, feedback control has focused on enhancing the tracking and robustness performance of the closed-loop system; however, as cyber-physical systems become more complex and interconnected and more interdependent, there is a need to refocus our attention not only on performance but also on the resilience of cyber-physical systems. In situations of unexpected events and faults, computational intelligence can play a key role in improving the fault tolerance of cyber-physical systems and preventing serious degradation or a catastrophic system failure. The goal of this presentation is to provide insight into the design and analysis of intelligent monitoring methods for cyber-physical systems, which will ultimately lead to more resilient societies.
Short Bio: Marios Polycarpou is a Professor of Electrical and Computer Engineering and the President of the Advisory Board of the KIOS Research and Innovation Center of Excellence at the University of Cyprus. He is also a Founding Member of the Cyprus Academy of Sciences, Letters, and Arts, an Honorary Professor of Imperial College London, and a Member of Academia Europaea (The Academy of Europe). He received the B.A degree in Computer Science and the B.Sc. in Electrical Engineering, both from Rice University, USA in 1987, and the M.S. and Ph.D. degrees in Electrical Engineering from the University of Southern California, in 1989 and 1992 respectively. His teaching and research interests are in intelligent systems and networks, adaptive and learning control systems, fault diagnosis, machine learning, and critical infrastructure systems.
Prof. Polycarpou is the recipient of the 2023 IEEE Frank Rosenblatt Technical Field Award and the 2016 IEEE Neural Networks Pioneer Award. He is a Fellow of IEEE and IFAC. He served as the President of the IEEE Computational Intelligence Society (2012-2013), as the President of the European Control Association (2017-2019), and as the Editor-in-Chief of the IEEE Transactions on Neural Networks and Learning Systems (2004-2010). Prof. Polycarpou currently serves on the Editorial Boards of the Proceedings of the IEEE and the Annual Reviews in Control. His research work has been funded by several agencies and industry in Europe and the United States, including the prestigious European Research Council (ERC) Advanced Grant, the ERC Synergy Grant and the EU-Widening Teaming program.
Professor Massimo Mecella
School of Information Engineering, Computer Science and Statistics of Sapienza Universita di Roma, in the Department of Computer, Control and Management Sciences & Engineering ANTONIO RUBERTI (DIAG, formerly DIS – Department of Computer and Systems Sciences)
Title: Engineering Information Systems and Smart Applications with LLMs
Abstract: The current evolution of AI, and of Generative AI in particular, namely Large Language Models (LLMs), makes it possible to adopt them as supporting tools for the engineering of information systems, in particular for their design and development based on service-based approaches and business-process orientation. In this keynote we will present, with an IS engineering attitude, recent approaches and applications for LLMs’ usage during the design of information systems. Very recent works (in the last year) are emerging on how to use ChatGPT (one of the most widespread applications of LLMs) for the conceptual design, the software development, and extraction of business process specification from documents. But all of them are quite fragmented, and a unifying framework and pipeline is missing. We will also provide such a unifying principled view. Case studies, based on the presenters’ research activities, will be presented, and a systematic analysis of the literature and practice will be presented as well.
Short Bio: Massimo Mecella, PhD in Engineering in Computer Science, is a full professor at Sapienza, where he is conducting research in the fields of information systems engineering, software architectures, distributed middleware and service oriented computing, mobile and pervasive computing, process management, data and process mining, big data analytics, advanced interfaces and human-computer interaction, focusing on smart applications, environments and communities. He is author of about 250 papers (h-index 42, cf. https://scholar.google.com/citations?user=x844E6sAAAAJ). He has been/is currently involved in several European and Italian research projects, and has been the technical manager of the projects WORKPAD and SM4All, coordinated by Sapienza.
He has a large experience in organizing scientific events. He was the General Chair of CAiSE 2019, BPM 2021, and ICSOC 2023 in Rome (just to name the last ones). He sits in the Steering Committees of the conference series CAiSE, ICSOC, Intelligent Environments (IE), AVI (Advanced Visual Interfaces), and SummerSOC. Currently, he is the vice-director of the the BSc in Engineering in Computer and Control Sciences, the MSc in Engineering in Computer Science and Artificial Intelligence, and the MSc in Artificial Intelligence and Robotics offered by Sapienza. He was director of the above degrees for the period 2020 – 2023.
Professor Marco Gori
Siena Artificial Intelligence Lab, University of Siena, Italy
Title: Collectionless AI and Nature-Inspied Learning
Abstract: AI is revolutionizing not only the entire field of Computer Science, but nearly all fields of Science. However, while application contexts explode and LLMs display embarrassing cognitive qualities, the entire AI research field seems headed toward saturation of the fundamental ideas that have enabled today’s spectacular results of large companies. Is the infamous “AI winter” perhaps creeping into research? In this talk I argue that the time is ripe for a fundamental rethinking of AI methodologies with the purpose to migrate intelligence from the cloud to the growing global population of devices with on-board CPUs.
To support learning schemes inspired by mechanisms found in nature, I propose developing intelligent systems within NARNIAN, a platform that enables social mechanisms and fosters learning processes over time, without the need for data storage.
Short Bio: Marco Gori received the Ph.D. degree in 1990 from Università di Bologna, Italy, working partly at the School of Computer Science (McGill University, Montreal). He is currently full professor computer science at the University of Siena, where he is leading the Siena Artificial Intelligence Lab. He is mostly interested in Machine Learning with emphasis on Neural Computation.Since, the end of 2019, He has also been collaborating with the Interdisciplinary Institutes for Artificial Intelligence, 3IA Côte d’Azur.
The impact of his research on neural networks emerged mainly from the growing interest in Graph Neural Networks. He introduced the first ideas in the paper “A New Model for Learning in Graph Domains”, by M. Gori, M. Monfardini and F. Scarselli (IJCNN2005) where the keyword Graph Neural Network was coined. A few years later, an extended paper “Graph Neural Networks,” IEEE-TNN, 2009 provided a more robust analysis and an accurate experimental evaluation. To date, the paper has received more than 10,000 citations (about 6-7 citations/day in the last months).
Professor Gori has been the chair of the Italian Chapter of the IEEE Computation Intelligence Society and the President of the Italian Association for Artificial Intelligence. He is a Fellow of IEEE, EurAI, IAPR, and ELLIS
Professor John Soldatos
TBA
Title: From Language Models to Autonomous Agents: Evolutionary Trajectories and Industrial Transformations in AI-Driven Systems
Abstract: The rapid evolution of Large Language Models (LLMs) and AI agents is currently redefining the boundaries of AI: It enables unprecedented automation and decision-making capabilities in complex domains. This talk examines the architectural and algorithmic milestones in LLM development, from transformer-based foundations to today’s multi-agent frameworks which are capable of collaborative reasoning.
Drawing on case studies in finance (e.g., real-time risk assessment, stock selection) and industrial automation (e.g., asset maintenance, industrial training, and human-robot collaboration), the talk highlights how LLMs transition from passive tools to proactive, context-aware agents. The practical contributions of the talk include novel architectures for solving complex problems with LLMs and AI agents, while considering the need for ethical governance frameworks to address bias, transparency, and accountability.
The presentation concludes with a presentation of emerging challenges—such as energy efficiency, domain adaptability, and trust calibration—while proposing interdisciplinary pathways to bridge theoretical AI advancements with industrial scalability.Overall, this keynote will synthesize empirical results from EU-funded projects (e.g., XR5.0, HumAIne, MOSAICO) and industry partnerships in order to introduce ideas for engineering robust, ethically grounded AI systems for the next decade.
Short Bio: TBA