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.
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Charalampos (Haris) Psillakis is an Assistant Professor at the Division of Signals, Control, and Robotics within the School of Electrical and Computer Engineering at the National Technical University of Athens (NTUA). He holds a Ph.D. and Diploma in Electrical & Computer Engineering from the University of Patras. Previously, he served as an Adjunct Lecturer at multiple institutions and worked at Hellenic Electricity Distribution Network Operator (HEDNO) S.A. His research focuses on adaptive control, nonlinear control, robotics, multi-agent systems, power systems, and distributed control. Education: Ph.D., Electrical & Computer Engineering, University of Patras, 2006 Diploma in Electrical Engineering, University of Patras, 2000 Research Interests: Adaptive Control Nonlinear Control Intelligent Control Robotics and Automation Power Systems Control Multi-Agent Systems Stochastic Systems Uncalibrated Visual Servoing Publications: His work emphasizes distributed control algorithms for multi-agent systems, nonlinear control methodologies, and applications in robotics and power systems. Recent trends include consensus protocols under communication delays, adaptive neural network control, and robustness in dynamic network topologies. Teaching: He teaches courses on automatic control, nonlinear control systems, and advanced control methods at both undergraduate and graduate levels. Labs/Teams: His research is associated with the Signals, Control, and Robotics division at NTUA, focusing on robotics, power systems, and distributed control systems.
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 Manisمشاهده پروفایل
دانشیار
Georgios Manis is an Associate Professor in the Department of Computer Science and Engineering at the School of Engineering, University of Ioannina, Greece. He holds a PhD from the National Technical University of Athens and has been a faculty member at the University of Ioannina since 2002, progressing from Lecturer to Associate Professor in 2018. He has also served as temporary teaching staff at the University of Patras, University of Crete, and University of Ioannina in the late 1990s and early 2000s. Education: B.Sc. in Computer Engineering (Diploma), National Technical University of Athens (NTUA), 1987–1992 MSc in Advanced Methods in Computer Science (Distributed and Parallel Systems), Queen Mary, University of London, 1992–1993 PhD in Computer Engineering, NTUA, School of Electrical and Computer Engineering, 1993–1997 His research interests lie at the intersection of Biomedical Engineering and Computing Systems , with a strong emphasis on Biomedical Signal Processing , Entropy Analysis , and Machine Learning . He has pioneered work in Bubble Entropy —a parameter-free entropy measure—and developed fast algorithms for entropy computation. His work also extends to compiler design and parallel computing, particularly in the automatic parallelization of recursive functions and loops. The trends in his recent publications reflect a dual focus: (1) biomedical applications involving entropy, heart rate analysis, and disease diagnosis using machine learning (especially Random Forests and SVMs), and (2) high-performance computing, including parallelization techniques and compiler optimizations for multi-core and SVP architectures. His research is highly interdisciplinary, combining signal processing, algorithm design, and clinical applications. Scientific Leadership and Recognition: Guest Editor, Special Issue on “Entropy in Biomedical Engineering”, Entropy (MDPI) Member of the IPAN Laboratory, University of Ioannina Active contributor to IEEE, Elsevier, and MDPI journals He has supervised several graduate students and is involved in funded research projects such as Palimpsest and Homore , focusing on smart systems for cultural interaction and elderly monitoring. His advising contributions are evident in co-authored papers with students like Evanthia Tripoliti and Aristeidis Mastoras. He teaches both undergraduate and postgraduate courses, including Compilers I/II and Biomedical Data Analysis . Laboratories and Teams: He is a member of the IPAN lab at the University of Ioannina, which supports interdisciplinary research in informatics and biomedical applications. His collaborative network includes researchers from Greece and abroad, particularly in the fields of biomedical signal analysis and entropy-based methods.
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.
Christina (Tanya) Politi is an Associate Professor at the Department of Electrical and Computer Engineering, University of Peloponnese. She specializes in optical networking, high-speed communications, and IoT/smart city technologies. With a PhD in Physics from the University of Essex, she has contributed to over 100 publications and collaborated with the NAM group at the University of Patras on 5G and digital infrastructure projects. Her work bridges optical systems, wireless technologies, and modern digital frameworks for smart urban environments. She is also an associated member of Patras Science Park. Education: B.Sc. in Physics, University of Athens (1998) M.Sc. in Physics of Laser Communications, University of Essex (2000) PhD in Optical Communications, University of Essex (2005) Research Focus: Optical packet switching and fiber-optic networks High-speed data center interconnections 5G/6G technologies and IoT applications Smart city infrastructure and digital twins Laser-based security and entropy generation Recent Research Trends: Her articles explore cutting-edge areas like quantum-dot spin-VCSELs for neuromorphic computing, laser-fabricated security systems, and metaverse-driven smart city frameworks. These reflect her dual focus on optical fundamentals and applied digital technologies. Collaborations and Labs: Active in the NAM group (University of Patras) for 5G experimentation and affiliated with Patras Science Park. Her work integrates theoretical research with industrial applications in telecommunications and smart infrastructure.
Professor Angeliki Alexiou is a faculty member at the Department of Digital Systems, ICT School, University of Piraeus. She holds a PhD in Electrical Engineering from Imperial College London (2000) and a Diploma from the National Technical University of Athens (1994). Prior to academia, she worked at Bell Labs (2000–2009), where she contributed to projects like BLAST and FITNESS, earning a Bell Labs President’s Gold Award (2002). She leads the Wireless World Research Forum’s Radio Communication Technologies and High Frequencies groups. Her research focuses on 6G systems, MIMO, mmWave/THz communication, ultra-dense networks, RIS technologies, and machine learning applications. She coordinates EU projects like H2020 TERRANOVA and manages ARIADNE. Recent work emphasizes beamforming innovations, RIS-driven networks, and THz security challenges. Education: PhD in Electrical Engineering, Imperial College London, 2000 Electrical & Computer Engineering Diploma, NTUA, 1994 Affiliations: IEEE Member Technical Chamber of Greece Publications span 20+ years with over 100 articles on THz systems, RIS performance, and 6G architectures. Her work bridges theoretical models and practical implementations in high-frequency wireless communication.
Irene Koilanioti serves as a Research Assistant (equivalent to Lecturer) at the School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), within the Department of Communications, Electronics and Information Systems. She teaches core courses including Communications Networks (4th semester), Social Network Analysis laboratory (postgraduate/9th semester), and Waiting Systems laboratory (6th semester). Her academic credentials include: PhD in Informatics (2016) from the University of Cyprus on 'Improving content delivery infrastructures by utilizing information from social networks' Top-ranked graduate of the Postgraduate Program 'Advanced Information Systems' (University of Cyprus) Postdoctoral research at Ludwig-Maximilians-Universität Munich (2018-2019) Computer science teaching license from Friedrich-Alexander-Universität Erlangen Translation degree from the Institute of Linguists, London Her research integrates Social Network Analysis with Distributed Systems to optimize content delivery infrastructure, while pioneering Knowledge Graph applications for Sustainable Development Goals data management. Current work extends into IoT interoperability standards and digital civic engagement frameworks. Publication trends reveal a strategic focus on scalable data architectures for social multimedia and SDG implementation, evidenced by her IEEE award-winning work on distributed knowledge graphs and contributions to Clinical IoT standards. Key recognitions include: Best Paper Award at IEEE International Conference on Knowledge Graph (2022) She coordinates EU COST action cHiPSet's 'Delivering Social Multimedia Content with Scalability' use case and serves as national coordinator for RELINK² on digital democracy. Additional grants include State Scholarship Foundation of Greece funding for doctoral research and LMU Munich mentoring program participation. She edits for Frontiers in Digital Education. Her technical leadership spans EU COST actions cHiPSet and RELINK², developing high-performance simulation frameworks for big data applications in civic technology and IoT ecosystems.
Chronopoulos Antonis is a Professor at the University of Patras, specializing in distributed computing, grid and cloud computing, numerical algorithms, high performance computing, and scientific computing. His research spans both theoretical numerical methods and practical applications in distributed systems. His primary research interests focus on Distributed Computing , Grid and Cloud Computing , Numerical Algorithms , High Performance Computing , and Scientific Computing . His work bridges theoretical numerical methods with practical distributed systems implementations, particularly in the areas of load balancing, parallel iterative methods, and computational efficiency. Analysis of his publication record reveals a career trajectory that began with foundational work in numerical linear algebra and iterative methods in the late 1980s and 1990s, then evolved toward distributed and cloud computing applications in the 2000s and 2010s. His recent work shows increasing focus on healthcare applications of AI and machine learning, particularly in medical diagnostics and decision support systems. His research demonstrates consistent contributions to both theoretical numerical methods and practical distributed computing systems, with recent work expanding into healthcare applications of artificial intelligence.
- Data Science
- Databases
- Big Data Management
- +۳ مورد دیگر
Professor Theodoridis Ioannis is a distinguished faculty member in the Department of Informatics at the University of Piraeus, where he serves as Director of the Data Science Laboratory within the School of Information and Communication Technologies. With a career spanning over two decades, he has established himself as a leading expert in data management and analysis. His research interests focus on Data Science, particularly in databases, big data management, data mining, and geoinformatics. Professor Theodoridis has made significant contributions to spatial database systems, time series analysis, and distributed data processing. His work bridges theoretical foundations with practical applications in areas such as smart cities, mobility analytics, and scientific data management. His publication record demonstrates consistent research productivity with over 100 peer-reviewed articles in top-tier venues, accumulating more than 10,000 citations. His research output shows a clear evolution from foundational database techniques toward contemporary challenges in big data analytics, machine learning integration, and privacy-preserving methods. Member of editorial board of ACM Computing Surveys (since 2016) Reviewer for numerous international journals and conferences Active participant in data management conference committees Professor Theodoridis has secured significant research funding through Horizon 2020 projects, serving as project coordinator and research team leader since 2001. His work demonstrates strong industry and academic collaboration, with applications spanning multiple domains. He has also co-authored three influential monographs in his field. He leads the Data Science Laboratory, which serves as a hub for interdisciplinary research at the intersection of database systems, machine learning, and domain-specific applications. The laboratory fosters collaboration between computer scientists, domain experts, and industry partners to address real-world data challenges.
Panayiotis D. Tsanakas is a Professor of Computer Engineering at the National Technical University of Athens (NTUA), serving in the School of Electrical and Computer Engineering within the Department of Information Technology and Computers. Since 2023, he has held the position of Dean of the School of Electrical and Computer Engineering at NTUA. His academic career spans several decades with significant contributions to computer engineering and informatics. His educational background includes a Dipl. in Electrical Engineering from Aristotle University of Thessaloniki (1982), an MSc in Computer Engineering from Ohio University (1985), and a PhD in Computer Engineering from National Technical University of Athens (1988). Tsanakas specializes in high-performance computer architectures, cloud-computing systems, Internet-of-Things (IoT), and AI-based applications in medicine and biology. His research spans parallel and distributed processing, computer architecture, supercomputing applications, and biomedical engineering. He has published over 100 research papers in established scientific journals and conferences, with recent work focusing on AI applications in healthcare, cloud computing security, and advanced medical monitoring systems. His recent publications demonstrate a strong trend toward applying artificial intelligence to healthcare challenges, particularly in mental health monitoring, medical imaging, and biomedical diagnostics. His work frequently combines computer architecture expertise with medical applications, creating innovative solutions for healthcare challenges. 2023-now: Dean of the School of Electrical and Computer Engineering at NTUA 2018-2020: Board member of the EuroHPC Joint Undertaking 2004-2019: Chairman of GRNET, the national research and education network 2005-2009: Member of EETT (The Hellenic Electronic Communications and Posts Regulator) Tsanakas has supervised eight doctoral dissertations and more than 50 diploma theses. He has co-authored seven textbooks on computer systems that have been adopted by several higher-education institutions. His professional experience includes significant roles in national infrastructure development, including leading the design and deployment of advanced networking and cloud services for Greek academic institutions and healthcare facilities.
Sotirios Xydisمشاهده پروفایل
استادیار
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.
Adrian Sampsonمشاهده پروفایل
دانشیار
Adrian Sampson is an Associate Professor in the Department of Computer Science at Cornell University, where he is part of the Computer Systems Laboratory and the programming languages group. He joined Cornell in 2016 as an Assistant Professor and was promoted to Associate Professor in 2022. Prior to Cornell, he was a Visiting Researcher at Microsoft Research (2015-2016). He received his Ph.D. from the University of Washington in 2015 under advisors Luis Ceze and Dan Grossman, with a dissertation on Hardware and Software for Approximate Computing. His research focuses on breaking down abstraction barriers and rethinking the hardware-software interface. He is particularly known for his work on approximate computing, which explores how computers can be more efficient by allowing them to make controlled mistakes. He leads the Capra research group at Cornell, which investigates programming languages and computer architecture. Sampson's recent publications demonstrate a strong focus on hardware acceleration, FPGA programming, compiler design, and programming language theory. His work often bridges the gap between high-level programming abstractions and low-level hardware implementation, with particular attention to predictability, verification, and energy efficiency. He has made significant contributions to geometry types for graphics programming, timeline types for modular hardware design, and virtual machines for FPGA programming. Among his notable recognitions are the IEEE TCCA Young Computer Architect Award (2021), NSF CAREER award (2019), and multiple Distinguished Artifact Awards at major conferences. He has advised numerous Ph.D. students who have gone on to positions at institutions like Wellesley College, Northwestern University, and Amazon. Sampson is actively involved in academic service, serving on program committees for major conferences including PLDI, ASPLOS, and ISCA. He has also held leadership roles such as ACM SIGARCH Board of Directors (2023-2025) and SIGPLAN Information Director. His teaching at Cornell includes courses on computer systems, programming languages, and advanced compilers.
Zhenman Fangمشاهده پروفایل
دانشیار
Dr. Zhenman Fang is an Associate Professor in the School of Engineering Science (Computer Engineering Option) and Associate Member in the School of Computing Science at Simon Fraser University, Canada. He founded and directs the HiAccel Lab, focusing on accelerator-rich architectures. His PhD (2014) is from Fudan University, China, with 15 months spent at the University of Minnesota. Prior to SFU, he was a Staff Software Engineer at Xilinx (2017-2019) and a postdoc at UCLA (2014-2017). His research spans: Hardware acceleration for ML, big data, genomics, and HPC FPGA-based customizable computing and near-data processing Compiler/runtime systems for heterogeneous platforms Performance/reliability optimization of accelerator-rich systems His recent publications (2024-2025) focus on FPGA acceleration for machine learning (e.g., on-device training, quantization), computational chemistry, image/video compression, database systems, and reconfigurable computing, demonstrating cross-domain applications of specialized hardware. Awards & Honors: Best Paper Awards: FPL 2024, MEMSYS 2017, TCAD 2019 Best Paper Nominations: ICCAD 2025, FCCM 2025, HPCA 2017, ISPASS 2018 SFU Research Excellence Horizon Award (2025) NSERC Alliance, CFI JELF, and Xilinx University Awards He advises 20+ PhD/Master's students in HiAccel Lab, focusing on accelerator design. Major grants include NSERC Alliance (2020) and CFI JELF (2019). The lab operates a 10-node cluster with FPGA/GPU infrastructure.
Konstantinos Parsopoulos is a Professor at the Department of Computer Science & Engineering, University of Ioannina. He holds a Dipl. Mathematics (1998) and M.Sc. in Mathematics of Computers and Decision Making (2000) from the University of Patras, where he also earned his Ph.D. in Intelligent Optimization (2005). Prior to his current role, he served as a Lecturer at the Department of Mathematics, University of Patras (2008–2009). His academic journey includes positions as Assistant Professor (2009–2016), Associate Professor (2016–2022), and Professor (since 2022) at the University of Ioannina. His research focuses on Numerical Optimization, Computational Intelligence (including Evolutionary Computation and Swarm Intelligence), and Computational Operations Research. These areas encompass the development and analysis of metaheuristics, algorithm portfolios, and optimization techniques for real-world applications such as logistics, financial forecasting, and engineering systems. His work emphasizes parallel computing strategies, reinforcement learning for parameter adaptation, and software tools like SOMO-VCB for stochastic optimization. Parsopoulos has contributed to diverse optimization challenges, including crowdshipping models, neural network-based differential equation solvers, and variance counterbalancing in stochastic systems. His publications span topics from theoretical algorithm design to practical implementations in MATLAB and distributed computing environments. Despite his extensive contributions, no scientific awards are explicitly mentioned in the provided texts. In terms of academic leadership, he has advised numerous students (though no names are listed) and has been involved in grants related to optimization software and algorithmic research. His collaborations extend to cross-disciplinary projects in visual sensor networks, traffic light optimization, and bioinformatics, reflecting the broad applicability of his optimization methodologies.