جستجوی استاد راهنمای دانشگاهی

George Kousiouris is an Associate Professor at the Department of Informatics and Telematics , Harokopio University of Athens . He holds a Ph.D. in Cloud Computing from the National Technical University of Athens (2012) and a Dipl. Eng. in Electrical and Computer Engineering from the University of Patras (2005). His research focuses on Cloud Platforms , Serverless Computing (FaaS) , IoT Infrastructure , and Performance Engineering . He has led major EU-funded projects such as H2020 PHYSICS (lead architect), BigDataStack , and CloudPerfect , contributing to cloud service benchmarking, FaaS frameworks, and edge-cloud collaboration. His work emphasizes practical applications in healthcare, smart agriculture, and urban network analysis. Over 70 publications highlight his expertise in cloud resource optimization , service-level agreements , and data-driven infrastructure management . His recent work explores sustainable computing , human-AI collaboration , and conversational AI for MLOps . Key Projects: PHYSICS, BigDataStack, CloudPerfect, SLALOM, COSMOS Research Highlights: FaaS performance benchmarking, IoT event processing, hybrid-cloud workflows Awards/Grants: Multiple EU H2020 and FP7 project leadership roles He advises on cloud migration methodologies (e.g., ARTIST framework) and contributes to regulatory compliance frameworks like GDPR via semantic ontologies.

• Cloud Computing
• IoT Platforms
• Performance Engineering
• +۵ مورد دیگر

Dr. Yiannis Verginadis is an Assistant Professor in Management Information Systems at the Department of Business Administration, Athens University of Economics and Business (AUEB). With over 15 years of experience in ICT projects, his research focuses on management of information systems workflow management complex event processing cloud computing and security adaptive systems context-aware access control He holds a Diploma and Ph.D. in Electrical and Computer Engineering from the National Technical University of Athens, specializing in inter-organizational workflow systems for e-Government. His career includes adjunct lecturer roles at the University of Thessaly and Technological Educational Institute of Kalamata. Research trends from his publications include: Cloud continuum brokerage and decentralized data management (2023-2025) Attribute-based access control for healthcare data (2021-2024) Workflow optimization in multi-cloud environments (2016-2023) Federated learning applications (2022-2024) Event-driven architectures and ontological modeling (2009-2021) Security-by-design frameworks (2013-2021) Dr. Verginadis has authored a book on Information Management Systems and contributed to works on e-Participation, adaptive web services, and ambient assisted living systems. He has served on over 25 journal and conference review committees and published 60+ peer-reviewed papers.

• Management Information Systems
• Workflow Management
• Complex Event Processing
• +۷ مورد دیگر

Efstratiadis Andreas serves as an Assistant Professor in the Department of Water Resources and Environmental Engineering at the School of Civil Engineering, National Technical University of Athens (NTUA), based at the Laboratory of Hydrology and Water Resources Development. His research spans water resources systems, hydropower infrastructure, and the water-energy nexus, with emphasis on stochastic modeling and uncertainty quantification. His primary research interests include stochastic hydrology, flood risk assessment, multipurpose reservoir optimization, and renewable energy integration. He investigates cascading infrastructure failures, spatial reliability in solar PV systems, and climate-energy market uncertainties, often employing advanced simulation-optimization frameworks to address complex water-energy challenges under environmental variability. Recent publications (2023–2025) reveal a strong focus on hydropower dam safety, flood control infrastructure design, and the operational trade-offs in multipurpose reservoirs. His work increasingly integrates Earth Observation data for hydrologic modeling and examines socio-technical dimensions of the water-energy nexus, reflecting a shift toward interdisciplinary systems analysis. Dr. Efstratiadis contributes to NTUA's Laboratory of Hydrology and Water Resources Development, which develops decision support systems like Hydronomeas 2020 and national monitoring infrastructure (OpenHi.net) for Greek surface waters. His lab emphasizes computational tools for water resources management under climate uncertainty.

• Water Resources Engineering
• Hydropower Systems
• Flood Risk Management
• +۳ مورد دیگر

Nikolaos E. Panagiotou is a Research Engineer at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, where he has been working since March 2014. He is also a Ph.D. candidate in Real-time Data Analysis in Massive Streams and Social Media at the same institution under the supervision of Prof. D. Gunopulos. He is an active member of the KDDLAB research group at the University of Athens, participating in EU research projects including INSIGHT and VaVeL. His educational background includes: MSc. with Distinction in Artificial Intelligence, Learning from Data from the School of Informatics, University of Edinburgh (2012-2013) BSc. in Informatics and Telecommunications from the Department of Informatics and Telecommunications, University of Athens (2007-2011) Dr. Panagiotou's research focuses on real-time analysis of high-volume data streams with particular emphasis on text and sensor streams, including news and social media content. His current research interests include: Text Mining: event detection, first story detection, open information extraction IoT/Smart-Cities: sensor analysis, heterogeneous sensor aggregation, real-time visualization Spatio-temporal Analysis: congested road-segments, travel time estimation, OSM His work bridges theoretical research with practical applications in smart city technologies and real-time data processing systems. His publication record demonstrates a strong focus on smart city applications, real-time data processing, and information extraction from diverse data sources. The research shows progression from foundational work on stream mining and event detection to sophisticated applications in urban mobility and news monitoring systems. His most recent work continues to advance techniques for handling sparse data environments and real-time analytics, with particular emphasis on travel time estimation and hybrid analytical approaches. Dr. Panagiotou has been involved in significant EU-funded projects: INSIGHT project: Implementation of real-time analysis modules and visualization engine for the smart city of Dublin VaVeL project: Design of integration schemes and development of real-time analysis modules using spatio-temporal data He has developed multiple demonstration systems including the News Monitor for real-time news analysis and various smart city monitoring dashboards. His technical expertise spans real-time data processing, stream mining, spatio-temporal analysis, and visualization systems, with applications in urban mobility and news monitoring. His collaborative work with researchers across Europe demonstrates his integration into the international research community in data science and smart city applications.

• Text Mining
• IoT/Smart-Cities
• Spatio-temporal Analysis
• +۳ مورد دیگر

Demetrios Cantzos is a Professor at the Department of Industrial Design and Production Engineering, University of West Attica. He teaches courses in signal processing, pattern recognition, and machine learning. He holds a Ph.D. (2008) from the University of Southern California (USC) and a B.S. (2002) in Physics from the University of Athens. His research focuses on signal processing applications in seismology, environmental science, and engineering systems. He has participated in US Army/NASA-funded projects (2002-2008) and EU/National programs (2009-present) addressing biomedical, energy, and agricultural challenges. Key research interests include fractal analysis of seismic and environmental signals, electromagnetic precursors, and machine learning for signal interpretation. His work combines geophysics, electrical engineering, and data science to improve earthquake prediction and environmental monitoring systems. Recent publications (2020-2025) emphasize long-memory trends in electromagnetic and radon data, multifractal analysis of seismic activity, and backprojection techniques for rupture modeling. These studies contribute to understanding earthquake dynamics and developing early warning systems. No scientific awards are explicitly listed. He advises students in signal processing and AI-related disciplines through postgraduate programs like the MSc in Artificial Intelligence and Deep Learning.

• Signal Processing
• Pattern Recognition
• Machine Learning
• +۳ مورد دیگر

Cleopatra Bardaki is an Assistant Professor of Pervasive Information Systems and Supply Chain Management at the Department of Informatics and Telematics, Harokopio University of Athens (HUA). She leads the Technology Transfer Office of HUA and has extensive experience in research coordination and project management of EU-funded initiatives. Her academic background includes a PhD in Information Systems from Athens University of Economics and Business (AUEB), an MSc in IS (AUEB), and a BSc in Informatics and Telecommunications (University of Athens). Education: PhD (AUEB), MSc (AUEB), BSc (University of Athens) Leadership: Director of HUA Technology Transfer Office Her research focuses on IoT-enabled digital transformation, supply chain optimization, data analytics, and business process improvement. She has published over 60 peer-reviewed articles and co-edited a Greek-language volume on strategic governance post-pandemic challenges. Recent work explores energy-efficient logistics, gamification for sustainability, and smart farming applications. Her research outputs emphasize practical implementations in retail, healthcare, and environmental sustainability, with a strong emphasis on IoT integration and decision support systems. Projects often combine empirical evaluation with innovative platform design, such as hybrid simulation frameworks for IoT environments and FaaS performance analysis in cloud-edge systems. Awards: None explicitly mentioned Grants: Extensive EU-funded project involvement She advises on organizational energy conservation strategies through IoT-enabled gamified interventions and collaborates on precision medicine supply chain frameworks. Her TTO leadership role facilitates tech transfer between academia and industry.

• Pervasive Information Systems
• IoT-enabled Digital Transformation
• Supply Chain Management
• +۳ مورد دیگر

Kavvadias Dimitris is an Assistant Professor in the Department of Mathematics at the University of Patras, specializing in Computational Mathematics and Informatics. His academic journey includes a B.Sc. in Electrical and Computer Engineering from the National Technical University of Athens (1983), M.Sc. in Computer Science from Columbia University (1984), and a Ph.D. in Computer Engineering & Informatics from the University of Patras (1989). He has been affiliated with the University of Patras since 1992, initially as a Lecturer and then as an Assistant Professor since 1997. His research focuses on Algorithms and Complexity, Graph Theory and Applications, Computer Networks, and Scientific Computing. He has contributed to numerous research projects, including studies on parallel algorithms, network reliability, and data mining. His work spans theoretical computer science and practical applications, with a strong emphasis on algorithm design and computational methods. Kavvadias has taught extensively at both undergraduate and postgraduate levels, covering courses such as Discrete Mathematics, Operating Systems, and Algorithm Analysis. He has supervised doctoral theses and diploma projects, including those of H. Staurovoulos and Angeliki Panagopoulou. His involvement in academic organizations includes roles in the ACM, EATCS, and the Hellenic Open University. His publications reflect expertise in hypergraph algorithms, transversal generation, and numerical root finding, with contributions to journals like SIAM and theoretical computer science forums. He has also participated in international conferences and served as a referee for prominent journals and events.

• Algorithms and Complexity
• Graph Theory and Applications
• Computer Networks and Internet
• +۳ مورد دیگر

Michael Taroudakis is a Professor at the University of Crete, holding a Ph.D. from the National Technical University of Athens (1988). His research focuses on mathematical modeling of physical phenomena with emphasis in wave propagation, particularly as applied to acoustical oceanography and inverse problems. Professor Taroudakis's research interests span several interconnected fields including wave propagation, mathematical modeling, acoustical oceanography, inverse problems, seismic signal analysis, and geoacoustic inversion. His work demonstrates a consistent focus on applying advanced mathematical techniques to solve complex problems in underwater acoustics and oceanographic research. He has made significant contributions to statistical characterization of acoustic and seismic signals, development of inversion techniques, and applications of machine learning in acoustical oceanography. Analysis of his publication record reveals a strong emphasis on statistical methods for signal characterization, particularly using wavelet transforms and hidden Markov models. His research has evolved from fundamental mathematical approaches to more applied problems in ocean monitoring and environmental assessment, with recent work expanding into socioeconomic analysis related to labor markets in Crete. This interdisciplinary approach demonstrates his ability to apply mathematical expertise to diverse real-world problems. Professor Taroudakis has maintained an active research program with publications spanning over three decades, showing continued productivity through 2025. His work has contributed significantly to the field of acoustical oceanography, particularly in the Mediterranean region, and has helped advance methodologies for geoacoustic inversion and ocean acoustic tomography.

• Wave Propagation
• Mathematical Modeling
• Acoustical Oceanography
• +۴ مورد دیگر

Yannis Kotidis is a Professor at the Department of Informatics of the Athens University of Economics and Business (AUEB). He holds a Diploma in Electrical Engineering and Computer Science from the National Technical University of Athens (1995), and an M.Sc. (1997) and Ph.D. (2000) in Computer Science from the University of Maryland. Prior to joining AUEB, he worked as a Senior Technical Specialist at AT&T Labs-Research (1995–2006). Research Interests: Data Management, Sensor Networks, Complex Event Processing, Blockchain Technology, Time Series Analysis, and Distributed Systems. Projects: Led initiatives like DBSENSE (sensor network data management), RECOST (real-time stream processing), and INFORE (cross-platform analytics). Collaborated on Smart-Views (blockchain-based OLAP systems) and EasyFlinkCEP (streaming analytics). Recent publications focus on HPC resource allocation (RATS), time-series compression (Chimp/Sim-Piece), and decentralized data management using blockchain. His work emphasizes scalable solutions for big data challenges in distributed and sensor environments. Collaborations include teams at Siemens and Statoil, and academic partnerships addressing semantic data integration. He contributes to open-source tools like FlinkCEP, enhancing accessibility of big data analytics.

• Data Management
• Sensor Networks
• Complex Event Processing
• +۴ مورد دیگر

Georgios Atsalakis is an Assistant Professor at the School of Production Engineering and Management, Technical University of Crete. He holds an office at Δ5.007 in the DPEM Building, Ground Floor. His academic work focuses on applying neuro-fuzzy systems to diverse forecasting challenges in economics, finance, and engineering. His research integrates computational intelligence with real-world applications such as stock market trends, energy prices, and commodity demand, emphasizing predictive modeling and decision-making frameworks. Education details are not explicitly listed, but his academic affiliation and publications suggest expertise in computational methods and applied economics. His work often bridges theoretical models with practical industry needs, such as optimizing tourism services or analyzing cryptocurrency markets. Research Interests: Development of neuro-fuzzy models for economic forecasting Computational intelligence in financial markets Energy and environmental policy analysis Supply chain dynamics and demand prediction Algorithmic trading and market volatility analysis His articles span over two decades, showcasing a consistent focus on predictive systems for complex systems. Recent trends include integrating neuro-fuzzy techniques with macroeconomic cycles and policy impact analysis. Notable contributions include frameworks for Baltic Dry Index forecasting and Bitcoin price modeling. No academic awards are listed in the provided materials. He advises no students explicitly mentioned, though his affiliations suggest involvement in academic supervision through the School's programs. He is likely associated with the university's Production Systems and Decision Sciences laboratories, contributing to interdisciplinary research initiatives.

• Computational Intelligence
• Economic Forecasting
• Neuro-Fuzzy Systems
• +۵ مورد دیگر

Nikos Giatrakos is an Assistant Professor at the School of Electrical and Computer Engineering (ECE) of the Technical University of Crete. His primary research focuses on Big Data Management, Real-Time Analytics, and distributed systems. He holds a PhD in Computer Science from the University of Piraeus (2012), an MSc from Athens University of Economics and Business (2007), and a Diploma in Computer Science from the University of Piraeus (2006). His research interests include Big streaming Data & Real-Time Analytics , Distributed/Decentralized Big Data Processing , Federated Machine Learning , Edge-to-Cloud Data Management , and Complex Event Processing . He has contributed to EU projects as a key investigator and received the Best Demo Award in ACM CIKM 2020 for innovative work in streaming analytics. Notable research trends in his articles emphasize real-time resource optimization (e.g., tumor simulations over HPC), adaptive event forecasting , and distributed systems for large-scale data processing. His work bridges theoretical algorithms with practical implementations, such as the SuBiTO framework for neural learning and the FERARI system for multi-cloud event processing. Awards : Best Demo Award (ACM CIKM 2020) Key Projects : EU-funded initiatives on extreme-scale analytics and federated learning Grants : Contributions to multi-site and cross-platform analytics research He leads efforts in extreme-scale analytics-as-a-service (e.g., the INFORE approach) and has developed tools like SheerMP for scalable streaming services. His work often addresses challenges in edge computing , IoT workflows , and geospatial event detection over maritime or movement data.

• Big Data Management
• Real-Time Analytics
• Distributed/Decentralized Big Data Processing
• +۴ مورد دیگر

Venetis Ioannis is an Assistant Professor at the Department of Informatics, School of Information and Communication Technologies, University of Piraeus. His research focuses on operating systems, parallel computing, and high-performance computing applications in seismology and computational neuroscience. His research interests include: Operating Systems Parallel Computing Models Scheduling in Parallel Systems Real-Time Parallel Applications Seismology and Computational Neuroscience GPU and Many-Core Optimization Recent publications highlight his work on heterogeneous cluster scheduling, GPU-based neuronal modeling, and seismic event detection using grid search algorithms. Venetis has participated in European and national research programs related to parallel computing and high-performance applications. He teaches courses such as Operating Systems, Parallel Processing, and Assembly Language Programming, with a focus on practical implementations in high-performance environments.

• Operating Systems
• Parallel Computing
• Scheduling in Parallel Systems
• +۳ مورد دیگر

Kostopoulos Konstantinos is a Professor in the Department of Industrial Management & Technology at the University of Piraeus. His academic affiliation includes the School of Maritime and Industrial Studies. He holds a full-time position and specializes in strategic management, organizational behavior, and innovation management. His research focuses on organizational ambidexterity, performance feedback mechanisms, team dynamics, and leadership roles in fostering innovation and effectiveness. Research Interests: Professor Kostopoulos’ work examines the interplay between managerial decision-making, organizational structures, and performance outcomes. Key areas include: Strategic decision-making under multiple goals Ceo leadership orientations and innovation Team performance in complex environments Feedback systems in product development Human resource practices in SMEs Key Themes in Articles: His publications consistently explore how organizational units adapt to dynamic environments through paradoxical thinking, absorptive capacity, and social integration. Recent work emphasizes the role of ceo exploration orientation and high-performance work systems in driving ambidextrous innovation. Advising & Grants: No formal student advising records are listed in the provided texts. His research has been supported through institutional funding channels at the University of Piraeus. Labs/Teams: Affiliated with the Department’s research groups focusing on strategic management and organizational effectiveness. Collaborates with international scholars on innovation and leadership topics.

• Management
• Organizational Behavior
• Strategic Management
• +۳ مورد دیگر

Stelios M POTIRAKIS is a Professor at the Department of Electrical and Electronics Engineering at the University of West Attica in Athens, Greece. He has held this position since September 2018, following an Associate Professor role at the same institution from March to September 2018, and previously at Piraeus University of Applied Sciences from November 2015 to February 2018. His research focuses on complex systems time-series analysis with applications spanning geophysical phenomena, space weather, biological signals, financial markets, and audio processing. He leads the Electronics and Computer Technologies Laboratory (ECTLab) at the University of West Attica. Dr. POTIRAKIS specializes in digital signal processing, nonlinear dynamics, and mathematical modeling of complex physical systems. His expertise bridges electrical engineering with geophysics, particularly in studying earthquake precursors through electromagnetic emissions, ionospheric disturbances, and atmospheric anomalies. He has developed methodologies to analyze critical phenomena across diverse systems, from phase transitions in physics to market dynamics in finance. His recent publication record demonstrates a strong focus on the intersection of space weather, ionospheric monitoring, and seismic activity. He has pioneered approaches using Very Low Frequency (VLF) signals to detect pre-seismic ionospheric anomalies, contributing to earthquake prediction research. His work also extends to financial markets, where he applies complexity measures to forecast volatility, and to biological signals, where he investigates neural dynamics and spike generation mechanisms. 246 scientific publications with 54,289 reads and 2,419 citations Director of ECTLab (Electronics and Computer Technologies Laboratory) Key contributor to hELlenic Seismo-ElectroMagnetics Network (ELSEM-Net) Active researcher in Swarm mission data analysis for geophysical monitoring Dr. POTIRAKIS maintains an extensive international collaboration network, particularly with Japanese researchers like Masashi Hayakawa, reflecting the global impact of his interdisciplinary research in complex systems analysis and earthquake precursor studies.

• Complex Systems
• Time-Series Analysis
• Geophysical Signal Processing
• +۶ مورد دیگر

Michael V. Boutsikas is an Associate Professor in the Department of Statistics and Insurance Science at the University of Piraeus , Greece. Since 2000 he has held progressively senior academic posts, beginning as Lecturer and becoming tenured Assistant Professor before his promotion to Associate Professor in 2016. He earned his Diploma (1995), M.Sc. (1998) and Ph.D. (2000) in Mathematics from the University of Athens, all awarded with distinction. His research lies at the intersection of applied probability, actuarial science and reliability theory . Core interests include risk models, stochastic dependence, probability metrics, extreme value theory, scan statistics, urn models and compound Poisson approximation . These themes are unified by the aim of quantifying and bounding the behaviour of complex stochastic systems. Across more than twenty-five peer-reviewed articles published in leading journals such as The Annals of Applied Probability , Journal of Applied Probability , Bernoulli , Insurance: Mathematics and Economics and Naval Research Logistics , a clear trajectory emerges: developing sharp approximations and limit theorems for rare events, system reliability, and aggregate claims in risk processes. While the text does not list formal awards, it notes that his work has attracted at least 150 citations from international journals and monographs and that he maintains an h-index of 9 . He is an active referee for more than twenty journals and a reviewer for Mathematical Reviews . Teaching duties span undergraduate courses ( Risk Management, Stochastic Processes, Simulation ) and postgraduate offerings ( Simulation Methods, Extreme Price Theory, Stochastic Financial Models ). He has also authored sixteen sets of detailed teaching notes and lecture notes covering reliability, risk management and statistical software. No specific doctoral students or grant details are provided, but his long-standing presence and prolific output indicate sustained supervisory and research funding activity within the Department of Statistics and Insurance Science.

• Applied Probability
• Risk Models
• Stochastic Arrangements and Dependence
• +۷ مورد دیگر