Ioannis Panageas is an Assistant Professor in Computer Science at UC Irvine's Donald Bren School, directing the GOALLab. His research develops theory for learning in multi-agent systems, game dynamics, and optimization. Funded by NSF and NRF, he focuses on last-iterate convergence guarantees in games, efficient equilibrium computation, and multi-agent reinforcement learning. Recent Work: Provides first exponential lower bounds for fictitious play in potential games (NeurIPS 2023), efficient Nash equilibrium computation methods (ICLR 2023), and semi-bandit learning dynamics with no-regret guarantees (ICML 2023). Teaching: Offers courses in Algorithmic Game Theory and Optimization for Machine Learning. Currently advising 3 PhD students and 2 MS students.
Theodora Varvarigou is a Professor in the Department of Electrical and Computer Engineering at the National Technical University of Athens (NTUA). She holds a B.Eng. from NTUA and M.Eng. and Ph.D. degrees from Stanford University. Her career includes research at AT&T Bell Labs and roles at the Technical University of Crete. From 2008-2012, she served as director of NTUA's 'Technoeconomic Systems' postgraduate program. Her research focuses on Cloud Computing, Multimedia Content Processing, Social Networking Technologies, and emerging areas like blockchain, edge computing, and cybersecurity. She has published over 200 papers and led numerous European research projects, emphasizing scalable systems, data management, and smart infrastructure applications. Her work spans technical innovations such as intrusion detection systems, edge resource optimization, and blockchain-based solutions for IoT, healthcare, and smart cities. Recent publications highlight advancements in AI-driven resource allocation, privacy-preserving blockchain designs, and predictive analytics for edge computing environments. Professor Varvarigou has contributed to interdisciplinary initiatives, including cohort data harmonization in biomedical research and social media analytics for urban planning. Her teaching includes courses on digital systems, network programming, and fault-tolerant systems.
Leong Hou U, Ryan is an Associate Professor at the Faculty of Science and Technology, University of Macau, where he also serves as Head of the Centre for Data Science under the Institute of Collaborative Innovation. His work focuses on advancing data science methodologies and applications in large-scale and complex data environments. Education: Ph.D. in Computer Science, The University of Hong Kong, Hong Kong (2010) M.Sc. in E-Commerce Technology, University of Macau, Macau (2005) B.Sc. in Computer Science and Information Engineering, National Chi Nan University, Taiwan (2003) Dr. Leong's research interests center on large-scale data processing , spatial and spatio-temporal data analysis , graph data and graph neural networks , data visualization , crowdsourcing , reinforcement learning , and information retrieval . His work bridges theoretical advances with practical systems for handling modern data challenges across domains. The absence of listed publications prevents detailed analysis of article trends, but his research domains suggest strong engagement with artificial intelligence, data engineering, and human-in-the-loop systems. No scientific awards were listed in the provided text. Dr. Leong advises students and likely oversees research projects through his leadership at the Centre for Data Science, though no specific advisees or grants are mentioned. He plays a key role in shaping data science research direction at the University of Macau. He leads the Centre for Data Science at the Institute of Collaborative Innovation, which likely involves interdisciplinary teams working on data-driven innovation, possibly involving collaborations across faculties and industry partners.
Pavlos S. Georgilakis is a Professor at the School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), specializing in modern techniques for power system analysis, optimization, and renewable energy integration. He holds a Diploma (1990) and PhD (2000) in Electrical Engineering from NTUA. His career includes roles as Lecturer (2009) and Associate Professor (2018–2023) at NTUA, and Assistant Professor at the Technical University of Crete (2004–2009). Research focuses on power transmission/distribution systems, transformer design, and applying AI/optimization for grid efficiency. He led 10 research projects, including Horizon 2020 initiatives SHAR-Q, WiseGRID, and NobelGrid. He authored 3 books and over 230 publications (SCOPUS citations: >5,500). Editor of IET Smart Grid, Energies, and Electricity journals; senior IEEE member. He supervised 4 doctoral, 9 master’s, and 76 diploma theses. Awards include the 2013 Best Reviewer Award from Electric Power Systems Research. Active in energy storage, smart grids, and decentralized energy resource integration.
Eleni Stai is an Assistant Professor at the School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), affiliated with the Division of Communication, Electronic and Information Engineering. She holds advanced degrees in Electrical Engineering, Mathematics, and Applied Mathematical Sciences from NTUA and the National and Kapodistrian University of Athens. Her academic credentials include: Diploma in Electrical and Computer Engineering, NTUA (2009) B.Sc. in Mathematics, National and Kapodistrian University of Athens (2013) M.Sc. in Applied Mathematical Sciences, NTUA (2014) Ph.D. in Electrical Engineering, NTUA (2015) Dr. Stai's research integrates advanced optimization techniques with communications networks and energy systems. She develops stochastic and deterministic optimization frameworks for network resource allocation, data analytics on complex topologies, and smart-grid control applications. Her work bridges theoretical foundations with practical implementations in energy-harvesting networks, network slicing, and reinforcement learning for distributed systems. Analysis of her recent publications reveals dominant research thrusts in AI-driven network management (particularly O-RAN and network slicing), energy-integrated communications, and optimization of energy communities. A significant portion of her work addresses the convergence of 5G/6G networking with power systems, emphasizing real-time control and sustainability. Her scientific contributions have been recognized through prestigious awards: Chorafas Foundation Best Ph.D. Thesis award Thomaidis Foundation Best M.Sc. Thesis award Best Paper Award at ICT 2016 Best Presenter Award at IEEE ENERGYCON 2022 Dr. Stai serves on technical program committees for major international conferences and has co-authored the book "Evolutionary Dynamics of Complex Communications Networks". She teaches undergraduate courses in Queuing Systems, Computer Networks, and Social Network Analysis, reflecting her expertise in network theory and applications. Her research trajectory demonstrates continuous evolution from fundamental network optimization to AI-enhanced solutions for next-generation communication-energy systems. Her work builds upon her postdoctoral experience at EPFL (2016-2020) and ETH Zurich (2020-2023), where she developed advanced frameworks for communications networks and energy systems.
Badogiannis Efstratios is a Professor at the Department of Structural Engineering , National Technical University of Athens. He serves as Deputy Dean and works in the Reinforced Concrete Laboratory, Zografou Campus, Athens, Greece. Email: badstrat@central.ntua.gr Phone: +30 210 772 1266 Research Interests: Focus on sustainable concrete technology, pozzolanic materials (metakaolin, palygorskite clay), durability of lightweight and self-compacting concrete, seismic isolation systems for bridges, application of artificial neural networks in civil engineering, and mechanical/thermal activation of clays. Publication Trends: Recent work emphasizes AI-driven rheological modeling, seismic resilience of precast bridge systems, durability of concretes incorporating industrial by-products (e.g., by-pass filter dust, rice husk ash), and nano-materials for structural health monitoring. Laboratory Affiliation: Actively contributes to research at the Reinforced Concrete Laboratory, focusing on sustainability, corrosion resistance, and innovative construction techniques.
Professor Gregoris Mentzas is a faculty member at the National Technical University of Athens, School of Electrical and Computer Engineering, where he directs the Division of Industrial Electric Devices and Decision Systems. His research focuses on AI-enabled decision systems, knowledge management, and semantic technologies applied to digital enterprises and e-government. With over 350 publications, he ranks among the top 2% most cited scientists globally. Research Interests: Artificial intelligence for decision augmentation, big data analytics in personalized health and smart mobility, semantic web technologies, and industrial internet of things. Current projects investigate trustworthy AI frameworks and hybrid intelligence systems for Industry 5.0. Teaching: Leads courses in Digital Enterprise Management, Strategic Information Systems, and Project Management at undergraduate and postgraduate levels, incorporating industry case studies and experiential learning approaches. Awards & Leadership: Top 2% Highly Cited Scientist (PLOS Biology 2021) 5 Best Paper Awards in international conferences Director of Information Management Unit (1997-present) Board Member of Institute of Communication and Computer Systems (2006-2009) Projects & Funding: Secured over €18 million in research grants through 60+ European projects with industry partners including SAP, IBM, and Siemens. Research outcomes led to three technology spin-offs.
George Vouros is a Professor in the Department of Digital Systems at the University of Piraeus, Greece. He is the head of the AI Lab (http://ai-group.ds.unipi.gr/ai-group/) and director of the MSc in Artificial Intelligence program in collaboration with the Institute of Informatics and Telecommunications at NCSR Demokritos. He completed his BSc in Mathematics (1986) and PhD in Artificial Intelligence (1992) at the University of Athens. His research focuses on Expert Systems, Knowledge Management, Multi-Agent Systems, Reinforcement Learning, and Mobility Analytics. He has served as program chair and committee member for major conferences (AAMAS, AAAI, IJCAI) and editorial roles in journals like Discover Artificial Intelligence (Springer Nature) and Information (MDPI). He has supervised 13 PhD students and currently oversees 4. His work spans EU-funded projects and national initiatives, emphasizing scalable mobility analytics, air traffic management automation, and ontology engineering. He is also President of the Hellenic A.I. Society and actively promotes interdisciplinary applications of AI in healthcare, transportation, and environmental monitoring. Recent research highlights include deep reinforcement learning for tactical air traffic conflict resolution, LLM-integrated ontology engineering, and multimodal generative adversarial imitation learning for flight trajectory modeling. His work bridges theoretical advancements with real-world applications in critical infrastructure systems.
Dr. Aris Dimeas is a Researcher at the National Technical University of Athens in the Department of Electric Power and Industrial Applications . He holds a diploma and PhD in Electrical and Computer Engineering from NTUA and has extensive experience in power systems operations, renewable energy integration, and smart grid technologies. Specialized in AI applications for power systems Developed control software for demand side management Consultant for PPC (2007-2012) Research Focus : Smart grids and digital twin implementations Renewable energy market dynamics Microgrid optimization and control algorithms Collaborations : Active participant in EU research projects, collaborating with HEDNO and other energy grid operators on electronic meters and intelligent network deployments. Teaching : Instructs courses on electric energy systems, power system analysis, and energy management.
Vlahogianni Eleni is a Professor and Dean of the Department of Transportation Planning and Engineering at the National Technical University of Athens (NTUA). Her research focuses on integrating machine learning , quantum computing , and reinforcement learning with urban mobility and traffic engineering , addressing challenges in eco-routing , congestion pricing , and autonomous vehicle interactions . Her work emphasizes data-driven approaches to traffic forecasting, including quantum neural networks and theory-aware unsupervised learning . Recent publications explore mixed traffic environments , shared space modeling , and parking occupancy prediction , highlighting her commitment to advancing intelligent transportation systems . Professor Vlahogianni leads the Traffic Engineering Laboratory at NTUA and contributes to policy frameworks for connected and automated transport , wildfire resilience , and dynamic mobility solutions . She is actively involved in the LEVITATE project and advocates for explainable AI in transportation applications.
Anastasios Zafeiropoulos serves as Assistant Professor at Harokopio University of Athens, specializing in Spatial Data Management and Analysis within the Postgraduate Studies Program for “Applied Geography and Spatial Management” (Direction C: Geoinformatics). His academic role encompasses teaching “Spatial Databases” and advancing research at the intersection of geospatial technologies and distributed computing systems. His research program focuses on Spatial Databases, Internet of Things (IoT), Cloud/Edge Computing, and 6G Network Orchestration, with significant extensions into Knowledge Graph applications for Sustainable Development Goals (SDGs) and socio-emotional learning in education. Key innovations include the EduCardia methodology for student competency assessment and frameworks for climate vulnerability analysis using knowledge graphs. Analysis of his 2024-2025 publications reveals three dominant thrusts: (1) AI-driven orchestration of 6G services across the computing continuum using reinforcement learning; (2) Knowledge Graph applications for SDG interlinkage analysis and materials science; (3) EU-funded IoT/Edge Computing project ecosystems. His work consistently bridges theoretical networking concepts with practical sustainability and educational applications. Dr. Zafeiropoulos actively contributes to EU-funded initiatives in IoT and Edge Computing standardization, particularly through AIOTI WG Standardisation. His project portfolio includes NEPHELE multi-cloud ecosystem development and O-RAN slice admission control research, demonstrating strong industry-academia collaboration in next-generation networking. He leads the development of innovative tools including Palindrome.js for distributed system visualization and the EmoSocio open-access emotional intelligence model, reflecting his commitment to translating research into practical educational and environmental solutions.
Symeon Papavassiliou is a Professor at the Department of Communications, Electronics and Information Systems, School of Electrical and Computer Engineering, National Technical University of Athens since 2004. Previously held positions include Associate Professor at New Jersey Institute of Technology (1996-2004) and senior researcher at AT&T Labs (1995-1999). He leads the Network Management and Optimal Design Laboratory and has served in various academic leadership roles, including Deputy Director since 2005. His research focuses on computer networks, wireless systems, and AI-driven network management with over 400 publications. Recognized with multiple best paper awards and NSF Career Award (2003). Education: B.A. Electrical Engineering, NTUA (1990) MSc & PhD Electrical Engineering, Polytechnic University, NY (1992/1996) Key Roles: Founder, New Jersey Center for Wireless Networks & Internet Security Member, EETT (National Telecommunications Commission) 2006-2009 Editorial Board Member, multiple journals Research Interests: Specializes in mobile/distributed systems optimization, wireless networks, complex systems, IoT, and AI applications in network management. Active in 6G architecture research, edge computing orchestration, and secure federated learning frameworks. Publications highlight innovations in network resource allocation, game theory models for positioning systems, and symbiotic computing continuum architectures. Recent work emphasizes resilience in critical infrastructure and smart grid optimization. Awards: Over 10 best paper awards from IEEE conferences, AT&T recognition, and Greek Excellence in Research Grant (2012). Grants: Funded by EU Framework Programs, NSF, ESA, and industry partners like Panasonic and Northrop Grumman. Leads interdisciplinary projects like HEROES (UAV-based emergency response) and NEPHELE (multi-cloud ecosystems). Active in digital twin development for cultural heritage preservation and SDG tracking via knowledge graphs.
Michail G. Lagoudakis is a Professor at the Department of Electronic and Computer Engineering, Technical University of Crete. His academic journey includes a Ph.D. in Computer Science from Duke University (2003), an M.Sc. from the University of Louisiana, Lafayette (1998), and a B.Sc. from the University of Patras (1995). He has held prestigious positions such as Postdoctoral Fellow at Georgia Institute of Technology's School of Industrial and Systems Engineering. Research Interests : Spanning machine learning (especially reinforcement learning), decision-making under uncertainty, robotics, algorithm selection, computational biology, and human-computer interaction. Publications : Over 15 recent works, including key contributions to robotics (auction-based multi-robot routing), medical diagnosis (urgent endoscopy prediction), and foundational machine learning (Least-Squares Policy Iteration, RCPI algorithm). Scientific Recognition : Recipient of Duke University's Outstanding Dissertation Award (2002-2003) and two Outstanding Teaching Assistant Awards. Professional Affiliations : Member of AAAI, IEEE, and ACM. Collaborations include industrial applications in disassembly planning, dynamic packet routing, and medical imaging. He advocates for computational biology and interdisciplinary research, aiming to integrate tools from mathematics and control theory into machine learning.
Athanasios D. Panagopoulos is a Full Professor at the School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), specializing in Satellite & Space Communications , Antennas and Propagation , and Quantum Communication . He leads the Division of Information Transmission Systems and Material Technology, with a focus on wireless systems, machine learning, and 5G/6G technologies. Born in Athens (1975), received summa cum laude Diploma and Dr. Engineering from NTUA (1997, 2002). Former roles: part-time Assistant Professor (2003-2007), head of Satellite Division at Hellenic Authority for Information Security (2005-2008). Research Trends emphasize Quantum Key Distribution (QKD) , Reconfigurable Intelligent Surfaces , and Deep Learning Applications in satellite networks. His work bridges atmospheric propagation effects with terrestrial-satellite convergence , including AI-driven excess attenuation prediction and UAV channel modeling. Scientific Awards include URSI General Assembly Young Scientist Award (2002, 2005) Best Paper Awards: IEEE RAWCON 2006, IEEE ISWCS 2015 Grants & Collaborations : Principal Investigator for EU/ESA R&D programs, with editorial roles at IEEE Transactions on Antennas and Propagation, and Elsevier Physical Communication. Member of ITU-R , ETSI Study Groups , and IEEE (Senior) .
National and Kapodistrian University of AthensGreece
George Alexandropoulos is an Associate Professor at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens. His research focuses on telecommunications, signal processing, and reconfigurable intelligent surfaces (RIS) for next-generation wireless networks. He has contributed to advancements in integrated sensing and communications (ISAC), 6G technologies, and holographic beamforming. His work includes experimental validation of RIS prototypes, optimization of RIS-assisted systems, and analysis of secure communication strategies. Research interests include RIS hardware design, channel modeling, and applications in IoT, UAV communications, and disaster recovery networks. He explores topics like energy-efficient RIS operation, multi-RIS coordination, and RIS-enabled localization. His studies often address challenges at sub-THz frequencies, mutual coupling effects, and hardware impairments. Publications emphasize practical implementations of RIS in both indoor and outdoor settings, with a focus on real-world performance evaluation. Awards and grants are not explicitly mentioned, but his extensive publication record indicates significant academic contributions. His research often integrates machine learning for RIS configuration and reinforcement learning for resource optimization in dynamic networks.
