جست‌وجوی استاد و پژوهشگر

Theodoridis Ioannisمشاهده پروفایل

استاد

• 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.

Zhenman Fangمشاهده پروفایل

دانشیار

• Hardware Acceleration
• Computer Architecture
• Big Data Computing
• +۷ مورد دیگر

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.

Anastasios Gounarisمشاهده پروفایل

استاد

• Distributed Databases
• Autonomous data processing
• Big Data Management
• +۷ مورد دیگر

Anastasios Gounaris is a Professor at the Department of Informatics, Aristotle University of Thessaloniki, where he has been a faculty member since April 2008. He previously served as a Visiting Lecturer at the University of Cyprus (2007-2008) and held research positions at the University of Manchester and CERTH. His academic journey includes a PhD from the University of Manchester (2005), an MPhil from UMIST (2002), and a degree in Electrical and Computer Engineering from Aristotle University of Thessaloniki (1999). His research spans Distributed Databases, Autonomous Data Processing, Big Data Management, Workflow Optimization, and Data Mining . He has made significant contributions to large-scale data management systems, massive parallelism techniques, and business process analytics. His work bridges theoretical computer science with practical industrial applications, particularly in predictive maintenance and edge computing environments. His recent publications (2024-2025) demonstrate a strong focus on process mining, anomaly detection, predictive maintenance systems, and edge analytics . These works address critical challenges in handling evolving data streams, optimizing task allocation in resource-constrained environments, and developing parameter-free algorithms for real-world applications. His research shows consistent progression from foundational database systems work to cutting-edge applications in industrial IoT and healthcare analytics. Dr. Gounaris has successfully supervised numerous PhD students to completion, including Athanasios Naskos (2017), Georgia Kougka (2017), Christos Bellas (2022), Theodoros Toliopoulos (2022), Anna-Valentini Michailidou (2023), Ioannis Mavroudopoulos (2024), and Konstantinos Varvoutas (2025). His research has been supported by multiple national and European projects including DataflowOpt, PRECognition, NavGreen, CUREX, Rainbow, Lifechamps, and Trineflex. He is an active member of Datalab (formerly Delab) and has contributed to industry applications through collaborations with companies such as Comidor, Gnomon, Istognosis, Atlantis, AFS, Follow-Apps, Sboing, and Upcom. His work demonstrates a strong commitment to transferring research results to real-world applications while maintaining academic rigor.

Papadopoulos Apostolosمشاهده پروفایل

دانشیار

• Databases
• Data Mining
• Spatial Databases
• +۷ مورد دیگر

Apostolos Papadopoulos is an Associate Professor at the Department of Informatics , Aristotle University of Thessaloniki , Greece. His research focuses on databases, data mining, and big data analytics. Born in Eleftheroupolis, Greece Diploma in Computer Engineering and Informatics (University of Patras) PhD in Informatics (Aristotle University of Thessaloniki) Research Interests: Spanning DATABASES and DATA MINING , his work includes: Efficient query processing in multidimensional and spatio-temporal databases Graph mining algorithms (dense subgraphs, frequent patterns, probabilistic graphs) Parallel/distributed systems (Spark, Hadoop) for massive datasets Real-time data stream analysis Scientific Recognition: Best Paper at EDBT 2014 (selected for ACM Transactions on Database Systems) Best Knowledge Discovery Paper at ECML/PKDD 2008 Google Scholar h-index: 25 PhD Supervision: Mentoring 4 ongoing PhD students and one graduated candidate (Eleftherios Tiakas).

Vasilis Efthymiouمشاهده پروفایل

استادیار

• Big Data
• Database Systems
• Entity Resolution
• +۷ مورد دیگر

Vasilis Efthymiou is an Assistant Professor at the Department of Informatics and Telematics at Harokopio University of Athens (HUA), Greece. His research focuses on Big Data database systems, entity resolution, knowledge graphs, and machine learning applications. He has held postdoctoral positions at IBM Research and FORTH-ICS, and contributed to initiatives like the SemTab challenges and TaDA workshops. Education: Diploma in Computer Science (2010), University of Crete. Masters in Information Systems and Bioinformatics (2012), University of Crete. PhD in Entity Resolution in the Web of Data (2017), University of Crete. Research Interests: Efthymiou’s work emphasizes scalable entity resolution techniques, fairness-aware AI systems, and knowledge graph integration. He explores applications in cybersecurity, natural language interfaces, and privacy-preserving data analytics. Recent projects include automated entity resolution pipelines (e.g., TREATS) and hybrid graph neural networks for entity alignment (HybEA). Publications: His 60+ papers span venues like VLDB, SIGMOD, and AAAI. He co-authored two books and holds four US patents in data systems. Notable works include surveys on end-to-end entity resolution and fairness-aware entity resolution tools. Grants & Labs: He co-organized international workshops (e.g., TaDA) and contributed to benchmarking systems like SemTab. His team develops tools like FairER and pyJedAI, emphasizing open-source solutions for data integration challenges.

• Software Engineering
• IT Security
• Cloud Systems Engineering
• +۳ مورد دیگر

Diomidis Spinellis is a Professor at the Department of Management Science and Technology, Athens University of Economics and Business. He is a leading researcher in software engineering, IT security, and cloud systems engineering, with over 300 publications and 10,000 citations. He has authored award-winning books including Code Reading , Code Quality: The Open Source Perspective , and Effective Debugging: 66 Specific Ways to Debug Software and Systems (2016). As a Senior Member of ACM and IEEE, he served as Editor-in-Chief of IEEE Software (2015–2018) and contributed to open-source tools like CScout, UMLGraph, and dgsh. Award-winning author in software engineering Developer of critical open-source tools Editorial leadership in IEEE Software Contributor to macOS and BSD Unix His research spans code quality, software evolution, security, and developer productivity. Articles highlight Unix modernization, AI-assisted coding, dependency analysis, and incident management. He has served on the IEEE Computer Society Board of Governors and holds degrees from Imperial College London (MEng, PhD). Scientific contributions include open-source datasets (e.g., VulinOSS, Alexandria3k) and innovative tools for software analysis. His work bridges academic research and industrial practice, with case studies on Eclipse, Android APIs, and ING’s incident management.

Panagiotis Liakosمشاهده پروفایل

پژوهشگر

• Graph Mining
• Large-scale Networks
• Data Compression
• +۳ مورد دیگر

Panagiotis Liakos is a Researcher at the University of Athens (Department of Informatics and Telecommunications), specializing in graph mining for large-scale networks. He holds a Ph.D. in Distributed and Streaming Graph Processing (2015-2018), an M.Sc. in Computer Systems Technology (2008-2011), and a Ptychion in Informatics and Telecommunications (2004-2008), all from the University of Athens. His research focuses on developing scalable algorithms for graph processing, compression, and community detection in dynamic networks. Research interests include: Graph mining : Community detection, temporal graph analysis Large-scale systems : Distributed processing, cloud-based solutions Data optimization : Lossless compression, storage efficiency Stream processing : Real-time network analysis, dynamic algorithms His publications demonstrate strong focus on graph algorithms and data efficiency, with recent work on time-series compression (Chimp, Sim-Piece) and temporal graph processing. He has received multiple awards including: IEEE Big Data Travel Grants (2016, 2017) SIGIR Travel Grant (2016) WSDM Data Challenge 1st Place (2013) Greek State Scholarship (2006-2007) He has supervised 9 Master's students on topics spanning recommendation systems, MongoDB optimization, sports analytics, and traffic modeling. Contributed to European projects including GALENA, Interact, EarthServer, iMarine, and PERNASVIP. Leads the Hive Server project for distributed services and teaches Large Scale Data Management .

Stathes P. Hadjiefthymiadesمشاهده پروفایل

استاد

• Distributed computing
• Mobile and pervasive computing
• Networked multimedia
• +۳ مورد دیگر

Stathes P. Hadjiefthymiades is Professor at the Department of Informatics and Telecommunications of the National and Kapodistrian University of Athens, where he leads research on large-scale software systems and heads the M.Sc. programme “Management and Economics of Telecommunication Networks and Information Systems”. Since 2002 he has held continuous faculty appointments, previously serving as Assistant Professor at the Hellenic Open University and as Visiting Assistant Professor at the University of the Aegean. Education: B.Sc. (honours) in Computer Science, University of Athens, 1993 M.Sc. (honours) in Computer Science (Advanced Information Systems), University of Athens, 1996 Ph.D. in Computer Science and Telecommunications, University of Athens, 1999 M.Sc. in Engineering-Economics, National Technical University of Athens, 2002 Research interests span distributed/mobile/pervasive computing , networked multimedia , context-aware systems , wireless sensor networks , and Internet experimentation involving road, air and water vehicles. His work combines algorithmic design, system architectures, and techno-economic analysis to enable scalable, adaptive services in next-generation networks. He has authored more than 200 peer-reviewed publications and leads the H2020 RAWFIE project on large-scale IoT experimentation. Recent articles reveal a strong focus on trust and security in ad-hoc networks , content-delivery optimization , augmented-reality monitoring systems , and intelligent analytics for smart-city and healthcare applications . Scientific awards & distinctions: While individual prizes are not explicitly listed, sustained funding from EU Framework Programmes (ACTS, IST, H2020) and repeated keynote invitations attest to international recognition. Advising & grants: Prof. Hadjiefthymiades directs the M.Sc. programme on Telecommunication Network Management and Economics, supervising numerous graduate researchers. He has coordinated or participated in over 20 EU and national projects, securing multi-million-euro funding for experimentation infrastructures and doctoral training. Laboratories & teams: He heads the Pervasive Computing Research Group and is a long-standing member of the Communication Networks Laboratory at the University of Athens, where he steers a team of post-docs, doctoral and master students advancing mobile and pervasive systems.

Katia Papakonstantinopoulouمشاهده پروفایل

استاد آموزشی

• Network Analysis
• Game Theory
• Algorithms
• +۴ مورد دیگر

Katia Papakonstantinopoulou serves as a Teaching Professor and Researcher in the Department of Informatics at Athens University of Economics & Business (AUEB). She is an active member of the network analysis group and the Theory, Economics and Systems Laboratory (Main Building, Antoniadou wing, 4th floor), and contributes to the 5G-VINNI research project. Her academic credentials include: B.S. in Informatics and Telecommunications (University of Athens) M.Sc. in Advanced Information Systems (University of Athens) Ph.D. in Computer Science (University of Athens, supervised by Prof. Elias Koutsoupias) Her research integrates Game Theory for modeling selfish network behavior and Information Theory for compact network representations. Current work spans social network analysis, epidemic spread prediction using graph ML, and time series/graph compression techniques. She has significantly advanced lossless floating-point compression (CHimp/Chimp systems) and temporal graph compression. Recent publications (2022-2024) reveal strong focus on data compression efficiency for time-series databases and epidemic modeling, while earlier work (2016-2020) established foundations in community detection and distributed graph processing. Her research consistently bridges theoretical algorithms with practical network applications. Her scientific recognition includes: Doctoral Scholarship from the Greek State Scholarships Foundation She mentors students through research projects in algorithms and network analysis, particularly in the Master of Science in Data Science program (ranked 14th globally in Big Data Management by Eduniversal 2019). Her teaching portfolio includes graduate courses in Social Network Analysis and Algorithms, plus undergraduate instruction in core CS subjects. Her research operations center on the Theory, Economics and Systems Laboratory where she develops compression algorithms and network models, with recent work supporting 5G network slicing economics through the 5G-VINNI project.

Yannis Kotidisمشاهده پروفایل

استاد

• Data Management
• Sensor Networks
• Complex Event Processing
• +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.

Giatrakos Nikosمشاهده پروفایل

استادیار

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

Konstantinos Vergidisمشاهده پروفایل

استاد

• Business Process Management
• Enterprise Architecture
• BPMN Modeling
• +۷ مورد دیگر

Konstantinos Vergidis is a Professor at the Department of Applied Informatics, School of Information Sciences, University of Macedonia. With a PhD in Business Process Optimisation from Cranfield University (2008), he has established himself as a leading expert in business process management, enterprise architecture, and process modeling. His academic career spans over a decade at the University of Macedonia, where he has held various administrative roles including Director of the Doctoral Studies Coordination Committee and member of the University's Research Committee. PhD in Business Process Optimisation (2008), Cranfield University MSc in IT for Product Realisation (2005), Cranfield University Degree in Applied Informatics (2003), University of Macedonia Professor Vergidis' research focuses on Business Process Intelligence (BPI), with particular expertise in BPMN modeling, process optimization, and decision modeling with DMN. His work bridges theoretical frameworks with practical applications in both public and private sectors, examining process quality metrics, resilience, and the integration of emerging technologies like low-code platforms and AI. He has pioneered research on process modeling in the public sector and the impact of Large Language Models on BPMN-based process modeling. His publication record includes 21 scientific journal articles, 22 conference papers, and 8 books, demonstrating consistent scholarly output across multiple venues. Recent work shows a clear trajectory toward integrating AI technologies with traditional business process management, particularly examining how LLMs can transform process modeling practices and exploring low-code development platforms for process-driven application development. Teaching Excellence Award (2022-2023) Research Award 2022 (14th cycle) Research Award 2021 (13th cycle) Teaching Excellence Award (2020-2021) Thatcher Bros Prize (2008/09) Professor Vergidis has secured multiple research grants, including projects with Expertise France/European Commission on digital public services and with the National Research Foundation on process modeling for public administration. He leads the Business Process Intelligence research group and has coordinated significant projects including MODA (Multi-Omics Data Analysis) and Science Data and Analytics Platform. His administrative contributions include directing doctoral studies and serving on numerous university committees related to research, curriculum development, and digital transformation initiatives. His work with the National Process Registry (mitos.gov.gr) demonstrates his commitment to applying academic research to real-world public sector challenges, developing tools and methodologies that enhance process transparency and service delivery for Greek citizens.

• Software Engineering
• Cloud Computing
• Internet of Things
• +۳ مورد دیگر

Ευριπίδης Γ.Μ Πετράκης is a Professor & Laboratory Director at the School of Electrical and Computer Engineering, Technical University of Crete (TUC) since 1999. He holds a Ph.D. in Computer Science (University of Crete, 1993) and a B.Sc. in Physics (National University of Athens, 1985). His research focuses on Cloud Computing, IoT, Semantic Web, and Image Indexing, with over 175 publications and top international recognition including the 2024 AINA Best Paper Award and Stanford's Top 2% Global Impact ranking (2021-2023). Key projects include leading roles in Horizon 2020-funded BorderUAS (2020-2023), MARS smart farming initiative (2018-2021), and FP7-funded FI-STAR (2013-2016). He has pioneered solutions for IoT security (iBoT), edge-cloud computing (DeFog), and semantic service frameworks (OASL). His academic contributions span advanced distributed systems, including Apache Flink-based real-time video processing (Video2Flink) and Kubernetes optimization strategies. He also actively contributes to standards development for IoT interoperability and semantic web services.

• Data Science
• Machine Learning
• Distributed Systems
• +۵ مورد دیگر

Ntoulas Alexandros is an Assistant Professor at the National and Kapodistrian University of Athens, affiliated with the Department of Informatics and Telecommunications. His research focuses on data science, machine learning, distributed systems, web technologies, and information retrieval. He has contributed to advancements in federated learning frameworks, graph analysis, and privacy-preserving techniques. His work spans both theoretical and applied domains, including optimization of mobile content delivery, real-time data processing, and community detection in network streams. Key research interests include federated deep learning (e.g., DeepReduce), efficient communication protocols for distributed systems, and scalable algorithms for graph stream analysis. He has published widely in conferences like PAKDD and journals focusing on data mining and distributed computing. His research also addresses practical challenges such as server-to-server integration, content similarity detection, and privacy in search logs. Notable contributions include methods for rapid community detection in dynamic networks and innovative approaches to content curation from social activity streams. While no awards are explicitly listed, his active publication record reflects sustained academic engagement in high-impact areas of informatics.

Alexandros Ntoulasمشاهده پروفایل

استادیار

• Big Data Systems
• Web Search
• Social Network Analysis
• +۵ مورد دیگر

Alexandros Ntoulas is an Assistant Professor at the National and Kapodistrian University of Athens, Department of Informatics and Telecommunications. He holds a Ph.D. and M.Sc. from UCLA, and prior industry experience at Microsoft Research, Zynga, Samsung Research, and LinkedIn, focusing on scalable Machine Learning for Big Data applications. He co-founded Infocious (now Piksel) and has served as Program Co-Chair for PAKDD 2020 and Track Chair for IEEE Big Data Congress 2017. Education: Ph.D. and M.Sc. in Computer Science, University of California Los Angeles (UCLA) MSc and Engineering Diploma, Computer Engineering and Informatics Department, University of Patras Research interests span Big Data systems for Web search, social networks, and scalable Machine Learning applications. Notable achievements include 15 patents and awards such as the Best Paper Award at ICDE 2005 and KDD 2017's Best Applied Data Science Reviewer Award. Teaching includes courses like Web Information Systems, Systems Programming, and Big Data Management at the University of Athens. He has also held invited lectureships at UC Berkeley, University of Patras, and the University of Patras' Mathematics Department. Awards highlight contributions to data science and search engine innovation, including recognition from academic foundations and industry peers.