Professor Chatziantoniou Damianos holds a position at the Athens University of Economics and Business (AUEB) within the Department of Management Science and Technology (DMST), School of Business. He earned a B.Sc. in Applied Mathematics from the National & Kapodistrian University of Athens (1991), M.Sc. from New York University's Courant Institute of Mathematical Sciences, and a Ph.D. from Columbia University. His research focuses on big data systems, business intelligence, query processing, and real-time data analysis, with contributions influencing commercial database systems like Microsoft SQL Server and Oracle. As Director of AUEB's Master’s program in Business Analytics and Big Data, he previously served as an Assistant Professor at Stevens Institute of Technology (1997–1999). His industry collaborations include co-founding Panakea Software and VoiceWeb SA, and consulting roles at Aster Data Systems (now Teradata). He leads big data projects for companies like Cosmote, Piraeus Bank, and HEDNO. His research has been published in top venues including VLDB, ICDE, and SIGMOD, emphasizing practical applications in large-scale analytics and OLAP systems. He advises on strategic partnerships for the MSc program and maintains an active role in academic administration, including steering committees and quality assurance initiatives.
Tsichlas Kostas serves as an Associate Professor in the Department of Computer Engineering and Informatics at the University of Patras, Greece, within the Division of Applications and Foundations of Computer Science. His research spans fundamental and applied computing domains with active involvement in the ML@Cloud laboratory. His expertise centers on algorithmic innovation across multiple dimensions: Memory-optimized algorithms for primary/secondary storage systems Distributed environment data structures and computational geometry Physics-informed computing and complex network analysis Specialized domains including alphanumeric and graph algorithms Recent publication trends (2022-2025) demonstrate concentrated research in historical graph management systems, temporal network analysis, and physics-computing intersections. Key contributions include vertex-centric partitioning strategies, temporal community detection frameworks, and machine learning applications for energy data motif discovery. He maintains active laboratory affiliations with the LARGE-SCALE CLOUD DATA MACHINE LEARNING WORKSHOP (ML@Cloud lab), Combinatorial Algorithms Laboratory, and Distributed Systems and Telematics Laboratory, contributing to Greece's computational research infrastructure.
Nikolaos Pelekis is a Professor at the Department of Statistics and Actuarial Science, School of Finance and Statistics, University of Piraeus, where he teaches courses in Data Science, Data Management, Information Systems, and Computer Programming. He has been actively involved in both undergraduate and postgraduate education, offering specialized courses such as "Statistical Data Mining Methods" in the Applied Statistics Master's program and "Big Data Management" in the Cybersecurity and Data Science postgraduate program. Born in 1975, Professor Pelekis earned his Bachelor's degree in Computer Science from the University of Crete (1998), followed by an MSc in Information Systems Engineering (1999) and a PhD in Moving Object Databases (2002) from UMIST University in the United Kingdom. His educational background laid the foundation for his distinguished career in data science and database management. Professor Pelekis' research spans multiple domains within data science and database management, with particular emphasis on mobility data analytics. His work focuses on data mining, big data management and analytics, with special attention to location and motion data including trajectories of moving objects. He has made significant contributions to spatial and spatiotemporal database management, moving object database systems, privacy-preserving data mining, and OLAP analysis. His research bridges theoretical foundations with practical applications, particularly in maritime and transportation domains. An analysis of Professor Pelekis' recent publications reveals a strong trend toward maritime data analytics and vessel traffic prediction. His work increasingly focuses on applying machine learning techniques to maritime trajectory data, developing systems for collision risk assessment, vessel location forecasting, and maritime route prediction. The research demonstrates a progression from foundational database management techniques to sophisticated analytics for time-critical mobility forecasting, with applications in aviation and maritime domains. Five best research paper awards 1st & 3rd place in the SemEval-2017 competition 3rd place in the ACM SIGSPATIAL Cup 2016 competition Best paper award at ACM SIGSPATIAL'14 (Path-based Queries on Trajectory Data) Best paper award at ER'13 (Baquara: A Holistic Ontological Framework for Movement Analysis with Linked Data) Best application paper award at ICDM'09 (Clustering Trajectories of Moving Objects in an Uncertain World) Ralf H. Güting best research paper award at SSTD'21 (A Novel Indexing Method for Spatial-Keyword Range Queries) Best Demo Paper award at SSTD'21 (MaSEC: Discovering Anchorages and Co-movement Patterns on Streaming Vessel Trajectories) Professor Pelekis has been actively involved in advising and research funding acquisition. He has participated in over 10 European and National Research and Development projects as principal investigator or key researcher. His leadership extends to directing research laboratories and coordinating large-scale collaborative projects. As co-founder of the Data Science Lab - DataStories at the University of Piraeus, he has mentored numerous researchers and students. His research has been supported by prestigious funding programs including Horizon Europe, Horizon 2020, and national research initiatives. Professor Pelekis co-founded and leads the Data Science Lab - DataStories at the University of Piraeus, which comprises 9 faculty members from 4 different Departments along with experienced and young researchers. He previously served as Head of Research for the Information Management Lab (InfoLab) at the Department of Informatics, University of Piraeus (2005-2014). His current research team is actively engaged in multiple European projects including "DAT.AI – Energy-efficient AI-ready Data Spaces" and "EMERALDS – Extreme-scale Urban Mobility Data Analytics as a Service," focusing on cutting-edge applications of data science in maritime and urban mobility contexts.
Vassilios V. Dimakopoulos is a Professor of Parallel Processing at the Department of Computer Science and Engineering, University of Ioannina, Greece. He has been affiliated with the university since 1998, initially as an adjunct professor and later as a regular faculty member. Currently, he serves as the Dean of the School of Engineering and Chairman of the Technical Council of the University of Ioannina. His academic journey includes a Diploma in Computer Engineering from the University of Patras (1990), and M.A.Sc. and Ph.D. degrees in Electrical and Computer Engineering from the University of Victoria, Canada (1992 and 1996, respectively). His research focuses on parallel and distributed systems, parallel programming models, systems software, computer architecture, embedded systems, and performance analysis. He has held administrative roles such as Deputy Chairman of the Department (2014–2017) and Director of Graduate Studies (2016–2020). His contributions include pioneering work on OpenMP runtime systems, adaptive scheduling for embedded multicore architectures, and probabilistic search protocols in dynamic networks. Dimakopoulos is a member of the IEEE and the Technical Chamber of Greece. His work emphasizes bridging compiler design, runtime systems, and hardware constraints to optimize parallel computing efficiency. Recent research trends include hybrid OpenMP-MPI offloading strategies, adaptive task scheduling in heterogeneous environments, and fog computing cost modeling. His administrative leadership spans multiple institutional committees, reflecting his dual role as an academic leader and researcher. His research group collaborates on projects involving high-performance numerical optimization, task-based global optimization for protein folding, and embedded systems integration.
Isambo Karali is an Assistant Professor in the Department of Informatics and Telecommunications at the National and Kapodistrian University of Athens, a position she has held since November 2007. Prior to this, she served as a Lecturer at the same department from September 1999 to November 2007. Her academic career spans over three decades with significant contributions to knowledge representation, uncertainty reasoning, and semantic web technologies. Dr. Karali's educational background includes: PhD in Informatics (1995) from the University of Athens MSc in Computer Science (1988) from University College, University of London Bachelor of Mathematics (1986) from the Department of Mathematics, University of Athens Dr. Karali's research focuses on Knowledge Representation and Reasoning with Uncertainty, Artificial Intelligence, Logic Programming, and Object-Oriented Programming. She has made significant contributions to applying Dempster-Shafer theory for handling uncertainty in Semantic Web applications. Her work bridges theoretical foundations of logic programming with practical applications in knowledge representation, particularly in distributed and heterogeneous environments. She has supervised numerous PhD and master's theses in these areas. Her recent publications demonstrate a strong trend toward integrating uncertainty reasoning with Semantic Web technologies, particularly using Dempster-Shafer theory and fuzzy logic. Her work addresses challenges in managing imprecise and uncertain information in large-scale knowledge systems, with applications in recommendation systems, news analysis, and semantic search. The interdisciplinary nature of her research connects artificial intelligence, knowledge representation, and web technologies to solve complex information management problems. Dr. Karali has been actively involved in research funding and collaboration: Principal Investigator for "Handling uncertainty in data intensive applications on a distributed computing environment (cloud computing)" under the "Thalis" Program Scientific Responsible for "Artificial Intelligence and Logic Programming Techniques for Knowledge on the World Wide Web" at the National and Kapodistrian University of Athens Scientific Responsible for "Semantic Web and Logic Programming - Application to Guided Search" at the National and Kapodistrian University of Athens Participant in multiple EU research projects including MISSION, COSMOS, ADDSIA, PARACHUTE, APPLAUSE, and EDS As an educator, Dr. Karali has taught core undergraduate courses including Object-Oriented Programming and Logic Programming, as well as graduate courses on Knowledge Technologies and Artificial Intelligence. She has supervised numerous PhD and master's students, with a focus on uncertainty reasoning, semantic web technologies, and logic programming applications. Her mentorship extends to student competitions, including guiding the Department's team in the Microsoft ImagineCup 2009. Dr. Karali has also contributed to the academic community through service activities, including membership on program committees for conferences like IEEE ICTAI, reviewer for prestigious journals, and organizational roles in academic events. From 2000 to 2012, she was responsible for the Department's website, contributing to its architecture design and system development.
Manolis G.H. Katevenis is a Professor at the Department of Computer Science, University of Crete, and the founder and Head of the Computer Architecture and VLSI Systems (CARV) Laboratory at the Institute of Computer Science (ICS), Foundation for Research and Technology – Hellas (FORTH) in Heraklion, Crete, Greece. He has held academic positions since 1986 and played a pivotal role in establishing the Computer Science Department at the University of Crete. His research spans computer architecture, interconnection networks, VLSI systems, and high-performance computing, with a strong focus on scalable, low-power, manycore systems and RISC-V. He has led numerous European R&D initiatives, including serving as Coordinator of the ExaNeSt project. PhD in Computer Science, University of California, Berkeley (1983) MSc in Electrical Engineering and Computer Science, University of California, Berkeley (1980) Diploma of Electrical Engineering, National Technical University of Athens (1978) Manolis Katevenis's research focuses on advancing scalable system architectures for high-performance and big data computing. His work in computer architecture includes RISC-V, exascale computing, and manycore systems. He has made foundational contributions to interprocessor communication, particularly through remote-write, remote-DMA, and remote-enqueue mechanisms, and has pioneered innovations in interconnection networks and low-latency network interfaces. His research integrates hardware and software co-design to optimize performance, energy efficiency, and scalability in large-scale computing systems. The recent publications highlight a strong trend in exascale computing, interconnection networks, and FPGA-based prototyping of manycore systems. His work emphasizes scalable, low-power architectures, with recurring themes in congestion management, fair scheduling, crossbar design, and hardware-software integration for HPC. The articles span high-impact journals such as IEEE/ACM Transactions on Networking, IEEE Micro, and Computer Networks, reflecting sustained contributions to computer architecture and networking. ACM Doctoral Dissertation Award (1984) David J. Sakrison Memorial Prize (1983) IBM PhD Fellowship (1981–1983) Greek State Fellowship (1973–1978) Stelios Pichoridis Award for Outstanding University Teaching (2015) Member of Academia Europaea (elected 2012) Award by the Secretary General of the Region of Crete (2003) IEEE Milestone recognition for the RISC Project (2015) Manolis Katevenis has supervised over 50 graduate theses and mentored many prominent Greek computer architects, including recipients of the ACM Maurice Wilkes Award. He has served as Principal Investigator or co-PI in over 30 R&D projects with a total budget exceeding 18 million euros, including major European initiatives such as ExaNeSt (which he coordinated), EuroEXA, EcoScale, SARC, ENCORE, and multiple HiPEAC Network of Excellence projects. His leadership extends to project coordination, architectural design, FPGA prototyping, and systems software development. Katevenis founded and leads the CARV Laboratory at FORTH-ICS, a major research team with 80–100 members focused on computer architecture and VLSI systems. The lab has spun off the Distributed Computing Systems (DCS) Laboratory and is central to European exascale computing efforts, including participation in the European Processor Initiative. CARV has developed large-scale prototypes such as the 768-core ExaNeSt system and the Formic FPGA platform for manycore research.
Georgios Kargas serves as a Professor in the Department of Water Resources Management within the School of Environment and Agricultural Engineering at the Agricultural University of Athens (AUA). His academic profile centers on advanced irrigation engineering, soil physics, and hydrodynamics of porous media, with particular expertise in drainage system design, soil salinity assessment, and sensor-based soil moisture monitoring. His research interests focus on hydrodynamic characteristics of porous media , precision irrigation systems , and soil-water-electrical conductivity relationships . Current work emphasizes developing novel infiltration equations for furrow irrigation, validating low-cost sensor platforms for soil monitoring, and creating EU-wide soil salinity mapping frameworks using machine learning. His experimental approach bridges laboratory measurements with field applications, particularly in Mediterranean agricultural contexts. Analysis of his 15 most recent publications (2023-2025) reveals dominant trends in sensor technology validation (TEROS/WET sensors), advanced infiltration modeling consistent with Philip theory, and large-scale soil salinity mapping using EU databases. Key subfields include subsurface drainage equation development, LoRa-based monitoring systems, and electrical conductivity compensation methods for dielectric sensors. Professional contributions include editorial review work for Sensors (2021), Water (2016), and Sustainability (2017) journals, though no specific scientific awards are documented in available sources. Teaching responsibilities encompass core undergraduate and postgraduate courses including Hydrodynamic Characteristics of Porous Media , Special Topics in Soil Physics , and Irrigation-Drainage Systems Design , with consistent focus on Water Resources Management specialization. His instructional approach integrates theoretical principles with practical system design applications across 8th-9th semester curricula.
Christos Masouros is a Professor of Signal Processing and Wireless Communications at University College London (UCL), affiliated with the Institute for Communications and Connected Systems. He holds a Ph.D. from the University of Manchester (2009) and has held research positions at Philips Research Labs, Queen’s University Belfast, and UCL. His expertise spans wireless communications, signal processing, and integrated sensing and communications (ISAC). Key roles include coordinating the EU-funded PAINLESS (2018–2022) and ISLANDS (2024–2028) projects, which focus on energy-autonomous networks and next-generation vehicular networks, respectively. Education: Diploma in Electrical and Computer Engineering, University of Patras (2004) MSc by Research, University of Manchester (2006) PhD in Electrical and Electronic Engineering, University of Manchester (2009) Research Interests: Green Communications Large-Scale Antenna Systems ISAC (Integrated Sensing and Communications) Interference Mitigation in MIMO and Multicarrier Systems Awards: 2024 IEEE SPS Best Paper Award 2023 IEEE ComSoc Stephen O. Rice Prize Fellow of IEEE, AIIA, and AAIA Leadership Roles: Vice-Chair, IEEE Emerging Technologies Initiative on ISAC Chair, IEEE SPS ISAC Technical Working Group Editorial roles in IEEE Transactions on Wireless Communications, IEEE Open Journal of the Communications Society, and others Labs/Teams: Active in UCL’s Information and Communication Engineering Research Group, contributing to standards development via IEEE and ETSI working groups.
Nikos Spanoudakis is an Assistant Professor at the Department of Electronic Engineering of Hellenic Mediterranean University , with concurrent research collaboration at Technical University of Crete . He holds a PhD in Computer Science (Artificial Intelligence) from Paris Descartes University (2009, "Très Honorable"), an MSc in Organization and Administration from Technical University of Crete, and a Diploma in Computer Engineering and Informatics from University of Patras. Research Focus: Multi-Agent Systems (AOSE, Computational Argumentation), Model-Driven Engineering , Smart Buildings , IoT , and Artificial Intelligence Applications in Ambient Intelligence, Finance, and Education Key Contributions: Created ASEME Methodology and AMOLA Language for agent modeling, developed Gorgias-B argumentation framework, and designed Kouretes Statechart Editor for robotic behavior specification His recent publications reveal a strong trend in Explainable AI (2023: Explainable Argumentation as a Service ), Smart Energy Systems (2025: Engineering IoT-Based Open MAS for Large-Scale V2G/G2V ), and EdTech Innovations (2024: Role Assignment in Programming Courses ). He has received prestigious ACM Senior Member (2023) and IEEE Senior Member (2012) distinctions, along with teaching recognition (2021) from Technical University of Crete. Academic Leadership: Serves as Editor for Springer Nature's Computer Science journal and has reviewed for 15+ top-tier publications including IEEE Intelligent Systems and Journal of Web Semantics Conference Involvement: Program Committee Member for 20+ international conferences (IJCAI, ECAI, AAMAS, AAAI) and organizer of multiple European Agent Systems Summer Schools
Papamichail Ioannis is a Professor at the School of Production Engineering and Management, Technical University of Crete. His research focuses on advanced traffic control systems, automated vehicle navigation, and intelligent transportation systems. He specializes in macroscopic/microscopic traffic modeling, reinforcement learning applications, and optimization-based control strategies for lane-free and conventional traffic environments. Key research areas include automated vehicle trajectory planning, variable speed limit algorithms, cooperative adaptive cruise control, and intersection control for connected vehicles. His work integrates numerical methods, partial differential equations, and multiagent decision-making frameworks to address traffic congestion, safety, and efficiency challenges. Recent investigations emphasize lane-free traffic systems, exploring optimal path planning, vehicle nudging strategies, and boundary control mechanisms through microscopic simulations. He has also developed novel controllers for highway work zones and urban networks, leveraging data fusion and real-time state estimation techniques. Ioannis collaborates on EU-funded projects and actively contributes to SUMO-based simulation tools for automated vehicle testing. His research bridges theoretical control systems with practical traffic management solutions, aiming for zero congestion/accidents in future transportation networks.
Αλεξανδρόπουλος Γεώργιος is an Assistant Professor at the Department of Informatics and Telecommunications, School of Electrical and Computer Engineering, National and Kapodistrian University of Athens (NKUA). His academic career includes roles as Senior Research Engineer at Huawei Technologies France, Senior Researcher at Athens Information Technology R&D Center, and Adjunct Lecturer at the University of Peloponnese. He holds a PhD in Wireless Communications from the University of Patras (2010) and a Diploma in Computer Engineering and Informatics (2003). His research focuses on advanced wireless communication systems, including cognitive radio, millimeter-wave communication, MIMO systems, energy harvesting, and machine learning applications in telecommunications. He has contributed to projects involving smart antenna arrays, interference management, and channel modeling. His work bridges theoretical analysis and practical implementations in next-generation communication networks. Prior to academia, he served as a Research Assistant at institutions like the National Observatory of Athens and NCSR 'Demokritos', and consulted on patents at Pappas IP Law Office. His expertise spans both academic research and industry-driven innovation.
Professor Efstratios Gallopoulos is a faculty member at the Department of Computer Engineering & Informatics , University of Patras, where he holds the Division of Computer Software . He currently serves as Deputy Department Chair and Director of the High Performance Information Systems Laboratory (HPCLab) . His academic career spans multiple institutions including the University of Illinois at Urbana-Champaign, University of California Santa Barbara, and collaborations with INRIA Rennes and NASA Goddard Space Flight Center. Education : B.Sc. in Mathematics (First Class Honours) from Imperial College London (1979) Ph.D. in Computer Science from University of Illinois at Urbana-Champaign (1985) Research Focus : His work centers on Large-scale Scientific Computing with emphasis on Computational Linear Algebra , Parallel/Distributed Processing , and Data Mining . Recent publications highlight innovations in Randomized Numerical Linear Algebra , Heterogeneous Cluster Scheduling , and GPU-Accelerated Inversion Techniques . Article Trends : His research bridges High-Performance Computing with Data Science , focusing on scalable algorithms for Matrix Computations , Recommender Systems , and Biomarker Analysis . The work spans theoretical advancements (e.g., Givens Rotations ) and practical implementations (e.g., pylspack library). Scientific Awards : NASA Group Achievement Award for Massively Parallel Processor (MPP) development ACM SIGWEB Hypertext Ted Nelson Newcomer Award (2012) Advising and Grants : He has advised numerous research projects funded by European Research Council , Hellenic Foundation for Research and Innovation (HFRI) , and international bodies like the US National Science Foundation. Notably, he co-organized the 2015 Gene Golub SIAM Summer School and served as Chair of the SIAM Gene Golub Summer School Committee (2020-24). Labs and Teams : He leads the High Performance Information Systems Laboratory (HPCLab) and co-directs the interdisciplinary graduate program Data Driven Computing and Decision Making . His teams have contributed to the Cedar vector multiprocessor project at UIUC and Text-to-Matrix Generator (TMG) tools for data mining.
Sotirios Xydis is an Assistant Professor in the Division of Computer Science at the School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), with prior faculty appointment at Harokopion University of Athens (2020-2023). He maintains ongoing collaboration with the Institute of Communication and Computer Systems (ICCS) since 2014 and previously served as an engineer at HEDNO (2015-2018) and postdoctoral researcher at Politecnico di Milano (2011-2013). His academic credentials include: BSc in Electrical and Computer Engineering, NTUA (2005) MSc in Techno-Economic Systems, NTUA (2011) PhD in Electrical and Computer Engineering, NTUA (2011) Dr. Xydis specializes in hardware/software co-design , energy-efficient hardware acceleration , and memory management for embedded and cloud-edge systems. His research bridges low-power circuit design , heterogeneous architecture optimization , and resource management frameworks , with particular emphasis on AI workloads and serverless infrastructures. Current projects target Edge AI accelerators (CONVOLVE), disaggregated memory systems, and LLM inference optimization through hardware-aware algorithms. Analysis of his 2023-2025 publications reveals three dominant trends: (1) Energy-efficient hardware accelerators for Edge AI using approximate computing techniques, (2) Memory/resource management innovations for disaggregated serverless environments, and (3) GPU/FPGA optimization for LLM inference through dynamic frequency scaling and predictive throttling. These works consistently address the power-performance tradeoffs in heterogeneous computing systems. His scientific recognition includes: Best Paper Award, IEEE/NASA/ESA AHS (2007) Best Paper Award, ACM PARMA (2013) Best Paper Award, ACM Computing Frontiers (2020) Hipeac Award at DAC (2019, 2020) Dr. Xydis has secured over 15 European/national research grants as Principal Investigator and Technical Coordinator, focusing on hardware acceleration frameworks and energy-efficient computing. His advising encompasses graduate research in hardware design and optimization, though specific student names aren't publicly listed. Current projects include CONVOLVE for Edge AI and CollectiveHLS for collaborative hardware synthesis. He is a core member of NTUA's Microelectronics Laboratory (Microlab) and collaborates with ICCS on hardware acceleration projects. His team develops frameworks like CollectiveHLS and throttLL'eM, with active participation in DATE, DAC, and ISCA conference communities.
Sriram Krishnamoorthy is a Research Professor at Washington State University's School of Electrical Engineering & Computer Science and a research scientist at Pacific Northwest National Laboratory (PNNL), where he serves as the System Software and Applications Team Leader in PNNL's High Performance Computing group. Dr. Krishnamoorthy earned his B.E. from the College of Engineering, Guindy in Chennai, India, and his M.S. and Ph.D. degrees from The Ohio State University. He is a senior member of the Institute of Electrical and Electronics Engineers. His research focuses on parallel programming models, fault tolerance, and compile-time/runtime optimizations for high-performance computing. He has made significant contributions in areas including: Fault tolerance techniques that minimize rollback during failures Dynamic load balancing for irregular parallel applications Compiler and runtime optimizations for HPC applications GPU programming and heterogeneous computing Quantum chemistry simulations and quantum computing Dr. Krishnamoorthy's publications span computational science, high-performance computing, and quantum chemistry. His recent work shows strong trends toward quantum computing applications, fault tolerance in large-scale systems, and optimization of computational chemistry methods. He has developed techniques for density matrix quantum circuit simulation, floating-point error analysis, and scalable execution of coupled-cluster models. His scientific achievements have been recognized with several prestigious awards: Best Paper Award at International Conference on High Performance Computing (HiPC'03) Best Paper Award at International Parallel and Distributed Processing Symposium (IPDPS'04) U.S. Department of Energy Early Career award (2013) PNNL's Ronald L. Brodzinski Award for Early Career Exceptional Achievement (2013) The Ohio State University's Outstanding Researcher award (2008) Dr. Krishnamoorthy has advised numerous graduate students and collaborated extensively with researchers across computational science domains. His work on the NWChem project demonstrates significant grant funding and large-scale collaborative research efforts in computational chemistry. He leads research efforts in PNNL's High Performance Computing group, focusing on system software and applications development for next-generation supercomputing platforms.
Athanasios Liavas is a Professor at the Technical University of Crete (TUC), School of Electrical and Computer Engineering (ECE), where he has served as Department Chair (2009-2011) and Vice Chair (2011-2013). He holds a Diploma (1989) and PhD (1993) in Computer Engineering and Informatics from the University of Patras. His career includes postdoctoral research at the Institut National des Télécommunications (1996-1998) as a Marie Curie Fellow, and academic roles at the University of Ioannina and the University of the Aegean before joining TUC in 2004 as Associate Professor. He has been a Professor since 2009. His research focuses on Signal Processing for Communications , Information Theory , and Telecommunications , with recent emphasis on tensor decomposition techniques for biomedical signal analysis and machine learning applications. He leads the Telecommunications Laboratory and teaches courses such as Digital Communication Systems II and Wireless Communication Systems. He served as an Associate Editor for the IEEE Transactions on Signal Processing (2005-2009) and was a member of the IEEE SP COM Technical Committee (2006-2011). His recent work includes advancements in nonnegative tensor completion, parallel algorithms for large-scale tensor factorization, and generalized canonical correlation analysis for multi-subject fMRI data. These contributions address challenges in high-dimensional data reconstruction and brain imaging signal processing, leveraging stochastic optimization and distributed computing frameworks. Liavas has authored over 80 peer-reviewed articles, with key contributions in IEEE journals and conferences. His research spans theoretical signal processing, algorithm design, and practical implementations for telecommunications and biomedical engineering.
