Dr. George Stamou is a Professor at the School of Electrical and Computer Engineering of the National Technical University of Athens (NTUA), serving as Director of the Artificial Intelligence and Learning Systems Laboratory (AILS). His expertise spans knowledge representation, machine learning, neural networks, and semantic technologies. He leads interdisciplinary initiatives such as the postgraduate program 'Data Science and Machine Learning' (2018–2022). Research Interests: Focuses on knowledge graphs, interpretable AI, semantic web applications, and multimodal learning. His work integrates formal logic systems (e.g., description logics) with modern deep learning techniques, addressing challenges in explainability, bias detection, and ethical AI applications. Publications: Over 150 articles in AI journals/conferences with an h-index of 34 (Google Scholar). Notable contributions include datasets like CHORDONOMICON (music analysis), GOSt-MT (gender bias in MT), and methodologies for counterfactual explanations in machine learning. Awards & Committees: Active in W3C and RuleML standardization bodies. Co-organized major AI conferences. Recognized for contributions to semantic interoperability and knowledge-based systems. Labs & Teams: Directs AILS-NTUA lab and collaborates with CISRI (Computer & Information Systems Research Institute). Engages in EU projects like CultureLabs (cultural heritage digitalization) andsmarty4covid (health data analysis).
John Psarras is a Professor at the National Technical University of Athens (NTUA) in the School of Electrical and Computer Engineering, specifically within the Division of Industrial Electric Devices and Decision Systems. He serves as the Director of the Decision Support Systems Laboratory (DSSlab) and the University Research Institute of Communication and Computer Systems. He holds a Diploma in Mechanical Engineering (1982) and a Ph.D. in Electrical and Computer Engineering (1989), both from NTUA. His research specializes in decision support systems with applications in energy management, environmental analysis, and information systems. Key areas include: Multi-criteria analysis for energy policy and renewable integration AI-driven optimization of smart grids and building efficiency Sustainable finance mechanisms for green projects Blockchain applications in education and data security His recent publications (2023–2025) demonstrate a strong focus on AI-enhanced decision tools for energy transitions, smart infrastructure, healthcare diagnostics, and cross-border renewable cooperation, reflecting interdisciplinary innovation. He has supervised 22 PhD theses and coordinates EU-funded projects in energy policy, clean technology, and capacity building. No scientific awards are listed in available sources. He leads the Decision Support Systems Laboratory (DSSlab), advancing research in energy analytics, and directs the University Research Institute of Communication and Computer Systems, facilitating large-scale interdisciplinary collaborations.
Chasalevris Athanasios is an Assistant Professor at the School of Mechanical Engineering, National Technical University of Athens (NTUA), specializing in Rotordynamics and Tribology. His research focuses on nonlinear dynamics of machines, active bearings, and turbomachinery design. He holds a Ph.D. in Rotordynamics from the University of Patras (2009) and a Diploma in Mechanical & Aeronautical Engineering (2004). Research Interests: Machine Dynamics, Turbomachinery, Active Bearings, Bifurcation Analysis, Crack Detection. Teaching: Dynamics of Rotating Machines, Kinematics and Dynamics of Mechanisms, Machine Elements I. Collaborations: KIT (Germany), RPI (USA), MTU Aero Engines (Germany), and Cleveland State University (USA). Awards include the Humboldt Foundation Fellowship (2010), GE's 'Beyond and Ahead' Award (2017), and recognition as a Top 2% Scientist (2023). He has authored over 40 publications and supervised numerous graduate students. Current roles include Academic Advisor at DOATAP and Associate Editor for journals like ASME Journal of Tribology.
Athanasios Liavas is a Professor at the Technical University of Crete in the School of Electrical and Computer Engineering , specializing in Signal Processing for Telecommunications and Information Theory . He has held administrative roles as Department Chair (2009-2011), Vice Chair (2011-2013), and Dean of the ECE School (2017-2021). Education: Diploma (1989) and PhD (1993) in Computer Engineering and Informatics from the University of Patras. Professional Background: Postdoctoral Marie Curie Fellow at INT, Evry (1996-1998); Lecturer at University of Ioannina (1999-2001); Assistant/Associate Professor at University of the Aegean (2001-2004) and Technical University of Crete (2004-present). His research focuses on Signal Processing for Telecommunications , Information Theory , and Tensor Decomposition . Recent work involves nonnegative tensor factorization , parallel algorithms , and fMRI data analysis , with applications in wireless communications and medical imaging . Articles show trends in optimization algorithms , LDPC code design , and MIMO system robustness . Scientific Awards include: Marie Curie Fellowship (1996-1998) Associate Editor, IEEE Transactions on Signal Processing (2005-2009) Elected Member, IEEE Signal Processing for Communications and Networking Technical Committee (2006-2011) He has taught courses like Telecommunications Systems II , Wireless Communications , and Information Theory , and supervised students such as Despoina Tsipouridou (PhD) and Alex Balatsoukas-Stimming (Graduate). He leads projects like Partensor (Parallel Tensor Toolbox) and COOPCOM (Cooperative Communications), and contributes to labs including the Telecommunications Laboratory .
Efthimios S. Skordas is an Associate Professor of Experimental Solid State Physics at the Department of Physics, National and Kapodistrian University of Athens. Born in Lefkada, Greece in 1960, he holds a Mathematics degree (1984) from the University of Crete and a Doctorate (1992) from Uppsala University, Sweden. His research focuses on seismicity analysis through the lens of natural time analysis, complex systems, and non-extensive statistical mechanics. University of Crete (1984, Mathematics) Uppsala University (1992, Doctorate) His work demonstrates deep expertise in earthquake prediction, detection of pre-seismic anomalies through geoelectric/magnetic field variations, and entropy dynamics under time reversal. Recent publications highlight applications of natural time analysis to diverse domains including cardiovascular health monitoring. He has authored over 120 peer-reviewed publications and two monographs, with an h-index of 32. Skordas' research bridges geophysics with interdisciplinary applications, showing particular emphasis on entropy fluctuations, order parameter analysis, and multi-scale seismicity patterns. His laboratory contributes to understanding the physical interconnection of seismic electric signals with earthquake dynamics.
Laxman Dhulipala serves as an Assistant Professor in the Department of Computer Science at the University of Maryland, College Park, while also working as a research scientist at Google Research with the Graph Mining team. Dr. Dhulipala earned his Ph.D. from Carnegie Mellon University under Guy Blelloch's supervision and completed a postdoctoral fellowship at MIT with Julian Shun. His research centers on efficient parallel algorithms, particularly for parallel clustering and graph processing, along with developing computational models for emerging hardware technologies. His scholarly output demonstrates significant expertise across parallel computing domains, with particular emphasis on scalable graph algorithms, dynamic data structures, and computational geometry. Dr. Dhulipala's work bridges theoretical computer science with practical systems implementation, producing algorithms that achieve both theoretical optimality and real-world performance. His research group has made substantial contributions to benchmarking frameworks including the Graph Based Benchmark Suite (GBBS) and ParClusterers Benchmark Suite, establishing standardized evaluation methods for graph processing systems. The collective work shows progression from theoretical foundations to practical implementations that handle massive-scale datasets. Best Paper Award at SPAA 2022 Best Paper Runner Up at VLDB 2022 Distinguished Paper Award at PLDI 2019 Memorable Paper Award Finalist at NVMW'20 CMU's SCS Dissertation Award Honorable Mention As an educator, Dr. Dhulipala mentors numerous graduate students while teaching advanced courses in algorithm design and parallel computing. His research collaborations span multiple institutions including Carnegie Mellon University, MIT, and Google Research, reflecting his position at the intersection of academia and industry research.
Kostas Magoutis is Professor and Chair of the Computer Science Department at the University of Crete , and a collaborating researcher at FORTH-ICS . His research focuses on scalable distributed systems, cloud computing, IoT, and quantum-enhanced control. Education and Career: Ph.D. in Computer Science, Harvard University (2003) Research Staff Member, IBM T. J. Watson Research Center (2003-2009) Assistant Professor (2014-2019, tenured 2017) and Associate Professor (2020-2024), University of Crete Professor and Chair, University of Crete (2024-present) Research Interests: His work spans distributed computer systems , cloud computing , scalable data stores and stream-processing engines , Internet of Things , and the emerging area of quantum-enhanced control . Representative projects include the H.F.R.I.-funded QUADS (2025-2028) on quantum-enhanced adaptive systems, STREAMSTORE (2020-2023) on elastic stream processing, SmartCityBus on IoT-driven public transport, and the EU FP7 PaaSage project on model-based cloud lifecycle management. Awards and Honors: Best Paper Awards: USENIX ATC 2002, USENIX BSDCon 2002, IEEE SRDS 2014 (Best Student Paper), IoT 2024 (Runner-up) Grand Challenge Audience Award, ACM DEBS 2022 Best Poster Award, ACM EuroSys 2022 EU Marie Curie IEF Fellow (2009-2011) Alexander S. Onassis Fellow (1994-1995) and J. William Fulbright Scholar (1993-1994) Students and Mentoring: He has supervised or co-supervised more than 30 Ph.D., M.Sc. and undergraduate students, including Antonis Papaioannou (Ph.D. 2021), Efthimios Papageorgiou (current Ph.D.), and numerous M.Sc. graduates now in industry and academia. Labs and Teams: At FORTH-ICS he leads activities within the Distributed Systems and Storage Laboratory, coordinating research on scalable storage, stream processing, and IoT data management. The lab collaborates closely with European and national initiatives, hosting visiting researchers and industry partners.
Kostas Magoutis is Professor and Chair of the Computer Science Department at the University of Crete and collaborating researcher with FORTH-ICS. His research focuses on distributed systems, scalable data processing, IoT, and cloud computing, with projects including GreenInCities for urban regeneration and STREAMSTORE for stateful stream processing systems. Research interests include: Distributed computer systems architecture Elastic stream processing platforms Quantum-enhanced computing applications Multi-cloud application lifecycle management Recent publications demonstrate strong focus on federated data systems, quantum computing applications, and IoT-enhanced infrastructure, with consistent output in high-impact conferences and journals. Awards and distinctions: Multiple best paper awards from USENIX conferences Grand Challenge Audience Award at DEBS 2022 Marie Curie Fellowship and IBM Research awards Advises over 20 PhD and MSc students in distributed systems research. Leads multiple EU-funded projects and serves on program committees for top conferences including SOSP, EuroSys, and IEEE BigData. Directs research groups in distributed systems and cloud computing at FORTH-ICS.
Antonios Deligiannakis is a Professor at the School of Electronic and Computer Engineering of the Technical University of Crete, specializing in database systems and distributed data processing. His academic career includes a postdoctoral position at the National and Kapodistrian University of Athens (2006-2007) and a visiting researcher role at AT&T Labs-Research (2003). His educational background includes: PhD in Computer Science, University of Maryland, USA (2005) Master's Degree in Computer Science, University of Maryland, USA (2001) Diploma in Electrical and Computer Engineering, National Technical University of Athens (1999) Professor Deligiannakis's research spans Databases , Stream Processing , and Sensor Networks , with pioneering work in Approximate Query Evaluation for massive datasets and Complex Event Processing in distributed environments. His contributions enable efficient analytics in resource-constrained settings through techniques like synopses-based engines and windowed outlier detection. His 15 most recent publications (2020-2025) reveal a dominant focus on distributed streaming analytics, with recurring themes of cross-platform integration, federated learning, and extreme-scale interactive systems. Key innovations include the INFORE framework for interactive analytics, DAG* for IoT workflow optimization, and communication-efficient federated learning techniques—demonstrating consistent translation of theoretical advances into production-ready platforms. Scientific Awards: No specific awards were listed in the provided material. Information about advisees and research grants was not provided in available documentation, though his leadership in the Distributed Information Systems and Applications laboratory suggests active mentorship and project direction. He directs research in the Distributed Information Systems and Applications laboratory, developing systems for real-time analytics across domains including maritime surveillance, financial technology, and IoT platforms, with emphasis on scalability and fault tolerance in geo-distributed environments.
Nectarios Koziris is a Professor at the Department of Computer Science , National Technical University of Athens (NTUA) , and former Dean of the School of Electrical and Computer Engineering . His research focuses on Parallel and Distributed Systems , Computer Architecture , and Cloud Computing . Key Research Themes: Compiler-OS-Architecture Interaction, Datacenter Hyperconvergence, Sparse Matrix Optimization, Quantum Computing, FPGA Virtualization Leadership: Founder of ~okeanos (Europe's largest public Cloud IaaS), Co-founder of GFOSS , Member of IEEE Computer Society Greece, Advisor to Arrikto Inc. His work has led to over 180 publications with 5800+ citations (h-index 33) , including two Best Paper Awards (IPDPS 2001, CCGRID 2013) and Intel Recognition (2015). He has supervised 12 PhD students and participated in 15+ EU projects as coordinator or consortium partner. Scientific Leadership: Program Co-Chair for Europar 2012 , Organizer for IPDPS , ICPP , SC conferences, and active member in Cloud Computing Expert Groups for the European Commission.
Nikos Giatrakos is an Assistant Professor at the School of Electronic & Computer Engineering, Technical University of Crete, and a core member of the Software Technology and Network Applications Lab (SoftNet) . His work bridges Big Data systems, IoT, and advanced analytics, with a focus on real-time processing and scalable architectures. Previously, he served as a postdoctoral researcher at the same laboratory. Education PhD in Computer Science, University of Piraeus (2012) Postgraduate Diploma in Information Systems, Athens University of Economics and Business (2008) BSc in Computer Science, University of Piraeus (2006) Research Focus : Nikos specializes in software architectures for Big Data streaming, including Distributed Big Data Processing , Federated Machine Learning , Cloud-to-Edge Data Management , and Approximate Query Processing . His work has also advanced Complex Event Processing and Outlier Detection in decentralized environments. Scientific Contributions : His research has led to the DAG* workflow optimizer for IoT, the SuBiTO framework for real-time neural learning, and the INFORE approach for cross-platform analytics. He received the Best System Demonstration Award at ACM CIKM 2020 for INforE. Academic Leadership : Nikos teaches Object-Oriented Programming, Data Science, and Distributed Systems. He has supervised numerous European and national grants as Principal Investigator and served on program committees for top-tier conferences like SIGMOD, VLDB, and DEBS.
Emmanouil Zachariadis serves as an Associate Professor at the Department of Management Science and Technology (DMST) within the School of Business at Athens University of Economics and Business (AUEB). He specializes in operational research and computational optimization, focusing on transportation logistics, supply chain systems, and environmental impact minimization. Education : BSc in Chemical Engineering from National Technical University of Athens (NTUA) MSc in Computing Science from Imperial College London PhD in Chemical Engineering from NTUA His research integrates mathematical programming with optimization algorithms for operational challenges in transportation and production systems. He has published 26 articles in top-tier journals, accumulating over 1200 Scopus citations by June 2024. Recent scholarly trends emphasize vehicle routing problems with complex constraints (cross-docking, loading, time windows) and optimization methods for logistics sustainability. His work spans production-routing integration, emergency evacuation planning (EVITA project), and hybrid metaheuristics. Scientific Awards : Teaching excellence award for undergraduate course 'Optimization Methods in Management Science', Dept. of Management Science & Technology AUEB (2021-22) Teaching excellence awards for postgraduate course 'Large Scale Optimization', MSc in Business Analytics AUEB (2020-21, 2021-22, 2022-23) He has participated in European and National research projects, applying his expertise in supply chain optimization and sustainability. His teaching portfolio covers quantitative methods, operational research, and supply chain optimization at both undergraduate and postgraduate levels.
Dr. Vivi Tornari is a Research Fellow and head of the Holography laboratory at IESL/FORTH, specializing in optical metrology and cultural heritage preservation. She has held this position since 1996 and has coordinated major EU projects such as E-RIHS and CHARISMA . Her work focuses on developing holographic interferometry techniques for structural diagnosis of artworks, fraud detection, and environmental impact assessment. She holds a PhD in Applied Science from the University of Sunderland and has authored over 70 scientific publications. Education: Postdoctoral Fellow in Optical Holography, Royal College of Art (RCA), London (1990) PhD in Applied Science, University of Sunderland, UK (2009) MSc in Chemical Engineering/Material Science, National Technical University of Athens (1996) Research interests include laser-based structural analysis, speckle interferometry, and the integration of optical methods for heritage preservation. She has pioneered non-invasive diagnostic tools such as the Applied Holography Metrology Laboratory and has advised on EC projects as an evaluator. Funding highlights include: Leadership in EU projects totaling over €20M Coordinator of SYDDARTA (FP7) and CLIMATE FOR CULTURE (FP7) PI for HOLOAUTHENTIC (FP5) and LASERACT (FP6) Her publications emphasize interdisciplinary collaboration, combining optical engineering with conservation science. Key innovations include: Development of DHSPI (Digital Holographic Speckle Pattern Interferometry) Integration of thermography with interferometry for defect analysis Laser ablation studies on polymer substrates Labs/Teams: Lead the Holography Lab at IESL, collaborating with international institutions like the V&A Museum and Imperial College London. Current projects focus on European research infrastructures (E-RIHS) and climate change impacts on heritage materials.
John Paparrizos is an Assistant Professor of Computer Science and Engineering at The Ohio State University's College of Engineering, where he directs The DATUM Lab (Data Analytics, Understanding, Mining, and Management Lab). He maintains an adjunct affiliation with the School of Informatics at Aristotle University of Thessaloniki. His research spans databases, data science, machine learning, and artificial intelligence , with focus areas including: Time-series analysis (clustering, anomaly detection) Scalable data mining for structured/unstructured data Adaptive algorithms for resource-constrained environments Foundational technologies for data-intensive applications His work addresses real-world challenges across relational, time-series, multimedia, text, graph, web, and IoT data domains. Notable recognition includes: 2025 ACM SIGMOD Test-of-Time Award for k-Shape time-series clustering 2023 IEEE TCDE Rising Star Award ACM SIGMOD Research Highlight Award NetApp Faculty Award His research has been featured in New York Times (front page), Washington Post , Forbes , and adopted by Fortune 500 companies (Exelon, Nokia) and the European Space Agency. He actively serves on program committees for premier conferences including ACM SIGMOD, VLDB, IEEE ICDE, ACM SIGKDD, and NeurIPS. His open-source tools have exceeded 100,000 downloads and are integrated into academic curricula at Brown, Columbia, Purdue, and University of Chicago.
Ioannis Andreadis is a Professor in the Department of Electrical and Computer Engineering at the School of Engineering, Democritus University of Thrace. He has been a faculty member since 1993, following his appointment as a Visiting Professor at the School of Technological Applications of TEI Kavala (1991-1992). His academic journey began with a Diploma in Electrical Engineering from Democritus University of Thrace (1983), followed by an M.Sc. in Electrical Engineering & Electronics (1985) and a Ph.D. in Instrumentation & Analytical Science (1989), both from the University of Manchester. Professor Andreadis's research spans the Design and Implementation of Electronic Systems with particular emphasis on Intelligent Systems and Machine Vision . His work has resulted in over 230 publications in international journals, book chapters, and conference proceedings. He has made significant contributions to image processing, particularly in mathematical morphology, color image processing, and real-time implementation of image processing algorithms. His research has practical applications in seismic signal processing, crowd management systems, and 3D reconstruction technologies. The analysis of his recent publications reveals a strong focus on advanced image processing techniques, with increasing integration of deep learning approaches. His work spans both theoretical foundations (such as entropy estimation and moment calculations) and practical applications (including image stabilization, multi-focus image fusion, and crowd management systems). The interdisciplinary nature of his research connects electrical engineering, computer vision, and signal processing with applications in safety engineering, structural analysis, and robotics. Among his notable achievements are the IET Image Processing Premium Award (2009) , Best Paper Award at PSVIT 2007 , and Best Paper Award at EUREKA 2009 . He was elected Fellow of the Institute of Engineering & Technology (IET) in 2006 and Fellow of the Institute of Measurement & Control (InstMC) in 2021. He has also served as Subject Editor of the IET Electronics Letters and as Guest Editor for special issues of Pattern Recognition journal. Professor Andreadis has supervised 14 PhD theses , 21 Master's theses , and 88 Diploma works , demonstrating his commitment to academic mentoring. His research has been supported by significant grants including the EDUnet project (€280,000), wireless network implementation (€37,000), laboratory infrastructure development (€120,000), school information systems support (€478,000), the RESCUER project (€350,000 as Deputy P.I.), and the EDUSAFE project (Marie Curie Actions). He leads the Electronics Laboratory at Democritus University of Thrace, which has undergone significant infrastructure development through multiple funding sources. His work on the RESCUER project demonstrates collaboration with European partners on emergency risk management systems, while his EDUSAFE involvement shows commitment to advanced AR/VR safety systems development. His research group applies computational intelligence techniques to diverse challenges from seismic analysis to pedestrian evacuation modeling.
