Dr. George Tzagkarakis
Research Scientist | Scientific Data Analysis; Computational Finance

Title: AI, Data, and Decision Intelligence for Resilient Critical Systems

Abstract: Modern societies increasingly depend on complex and interconnected critical systems, such as energy networks, water infrastructures, mobility, and defense platforms, whose reliable operation under uncertainty is vital to economic and societal stability. As these systems become more data-rich and cyber-physical, they also become more exposed to disruptions, requiring a new generation of Decision Intelligence Systems (DIS) capable of transforming heterogeneous data into actionable insight and resilient decisions. This talk will outline an emerging architectural paradigm that integrates AI, data fusion, and digital-twin technologies to support adaptive and trustworthy decision-making in critical environments. By combining time series analytics, machine learning, optimization, and simulation, such systems can anticipate failures, optimize resource allocation, and support human operators through interpretable recommendations. Examples will be drawn from ongoing initiatives such as our TwinODIS EU project, which leverages distributed AI for operational decision support across energy and water domains, to enable predictive risk assessment and autonomous control. Beyond showcasing current advances, the talk will discuss the architectural, ethical, and governance challenges that must be addressed for AI-driven decision ecosystems to be deployed safely at scale, including data quality, model robustness, explainability, and human-in-the-loop integration. Ultimately, achieving resilience in critical infrastructures is not only a technical goal but a strategic imperative, requiring the convergence of data, algorithms, and human judgment into unified, intelligent decision frameworks.

BIO: George is a Research Scientist with more than 15 years of R&D experience in Quantitative Research and Scientific Data Analysis, with a main focus on multimodal data learning and analysis, distributed information processing, mathematical modeling, risk analytics, and computational finance. He holds a PhD and MSc in Computer Science (1st in class, highest honors) - with a major in Statistical Signal Processing - from the Computer Science Department, University of Crete (UOC), Greece, a PhD in Finance - with a major in Risk Quantification - from the Economics, Business and Society Doctoral School, Research Institute for the Management of Organizations, University of Bordeaux, France, and a BSc in Mathematics (1st in class, highest honors) - with a major in Applied and Computational Mathematics - from the Department of Mathematics, University of Crete, Greece.

In the period 2002-2010, he was a Research Associate at the Foundation for Research and Technology- Hellas (FORTH), Institute of Computer Science (ICS), Crete, Greece, as a member of the Telecommunications & Networks Laboratory and the Signal Processing Laboratory. A number of academic distinctions have been awarded to him both as an undergraduate and a post-graduate student from UOC, FORTH-ICS, as well as from external state foundations. From 2010 to 2012, he was a Marie Curie Postdoctoral Researcher at the Cosmology and Statistics Laboratory, CEA/Saclay, France, working on the design and implementation of compressive sensing algorithms for remote imaging in areal and terrestrial surveillance systems. In the period from 2012 to 2018, he was a Senior Researcher and Scientific Director at EONOS Investment Technologies, Paris, France, being responsible for developing and managing scientific research projects strategically aligned with the state-of-the-art in quantitative analysis, econometrics, and computational finance using advanced signal and data processing methodologies. Since 2018, he has been at FORTH-ICS, where he currently holds a Principal Researcher position, affiliated with the Signal Processing Laboratory.

His research interests primarily focus on Statistical Signal Processing, Nonlinear Time Series Analysis, Non-Gaussian Heavy-Tailed Models, Compressive Sensing, Distributed Signal Processing for Smart Sensor Networks, Computational Finance, and Machine Learning in Operations Research. He has (co)authored more than 100 technical publications in international peer-reviewed journals and conferences, and he has an extended experience in transferring research and interacting with industry through his involvement in European and national Research and Innovation projects. Since 2022, he is a member of the Scientific Council of FORTH-ICS, contributing to the R&D strategic planning of the Institute.