جست‌وجوی استاد و پژوهشگر

Deligiannakis Antoniosمشاهده پروفایل

استاد

• Databases
• Sensor Networks
• Online Analytical Processing (OLAP)
• +۶ مورد دیگر

Antonios Deligiannakis is a Professor at the Department of Electronic and Computer Engineering, Technical University of Crete. His research focuses on databases, sensor networks, online analytical processing (OLAP), approximate query processing, and distributed systems. He holds a Ph.D. in Computer Science from the University of Maryland (2005), an M.Sc. from the same institution (2001), and a Diploma in Electrical & Computer Engineering from the National Technical University of Athens (1999). His career includes postdoctoral work at the University of Athens (2006–2007), a lecturer position there (2007), and an internship at AT&T Labs-Research (2003). He leads the Software Technology and Network Applications Laboratory , contributing to projects like extreme-scale analytics platforms (INFORE) and federated learning systems. Research areas span IoT workflow optimization, communication-efficient distributed learning, and real-time maritime event detection. His work emphasizes scalability, efficiency, and practical implementations for big data challenges. Courses taught include Structured Programming . Notable contributions include DAG* algorithms for IoT workflows, federated learning frameworks, and systems for proactive streaming analytics at scale. He has pioneered methods for outlier detection in sensor networks and efficient query processing over distributed streams.

Pavlos Fafaliosمشاهده پروفایل

استادیار

• Information Systems
• Data and Knowledge Management
• Linked Data
• +۷ مورد دیگر

Pavlos Fafalios is an Assistant Professor of Information Systems at the School of Production Engineering and Management, Technical University of Crete, and an Affiliated Researcher at the Centre for Cultural Informatics (CCI) and Information Systems Laboratory (ISL), Institute of Computer Science, Foundation for Research and Technology - Hellas (FORTH). He holds a PhD and MSc in Information Systems from the University of Crete and an Engineer's Diploma from the University of the Aegean. His academic journey includes postdoctoral research at L3S Research Center, Leibniz University of Hanover, and FORTH-ICS, as well as teaching roles at Hellenic Mediterranean University and the University of Crete. His research interests span Information Systems , Data and Knowledge Management , and Linked Data , with a strong interdisciplinary focus on applications in Cultural Heritage and the Humanities . He develops semantic technologies, knowledge graphs, and information management systems for complex, real-world domains. The recent publications highlight a strong trend in applying semantic technologies to cultural and historical data, including earthquake data modeling, feminism history documentation, and museum data integration. His work consistently focuses on knowledge representation, ontology development, and data interoperability, particularly using CIDOC CRM and Linked Data principles. Individual postdoctoral research fellowship 'Marie Skłodowska-Curie' (H2020-MSCA-IF-2019) Finalist for the '2019 ERCIM Cor Baayen Young Researcher Award' Fellowship from legacy 'Maria Michael Manasaki' (2014-2015) 1st prize in Hack4Med 2014 1st prize in Blue Hackathon 2013 PhD and MSc scholarships by FORTH Pavlos Fafalios has been involved in significant research projects such as PortADa (MSCA Staff Exchange), RICONTRANS (ERC Consolidator Grant), FE.P.I.B., ReKnow (Marie Curie project), SeaLiT (ERC Starting Grant), and ALEXANDRIA (ERC Advanced Grant), where he served as principal investigator, scientific responsible, or lead researcher. He has supervised student projects that led to award-winning software tools. He is active in scientific committees and regularly publishes in international venues. He leads and contributes to research in the Centre for Cultural Informatics (CCI) and Information Systems Laboratory (ISL) at FORTH-ICS, collaborating on interdisciplinary projects that bridge computer science with humanities and cultural heritage. His lab work emphasizes practical tools for semantic data integration, exploration, and analysis.

Angelos Charalambidisمشاهده پروفایل

استادیار

• Programming Languages and Software Systems
• Declarative Programming Languages
• Computational Logic
• +۱ مورد دیگر

Angelos Charalambidis is an Assistant Professor at Harokopio University, affiliated with the Department of Informatics and Telematics. His academic and professional engagements focus on theoretical and applied aspects of computational logic and programming languages. Education: B.S. in Informatics, University of Athens (2005) M.S. in Computer Systems, University of Athens (2008) Ph.D. in Higher-Order Logic Programming, University of Athens (2014) His research interests include declarative programming languages, computational logic, and reasoning techniques, contributing to the broader field of Programming Languages and Software Systems. He has also explored applications in knowledge representation, preference modeling, and cloud-native systems. The trends in Angelos Charalambidis's publications highlight advancements in logic programming, including higher-order logic, fixpoint theory, ordered disjunction, and federated query processing. His work bridges theoretical foundations with practical implementations in formal methods and computational logic.

James Cheneyمشاهده پروفایل

استاد

• Databases and data provenance
• Programming languages and compilers
• Generic programming
• +۷ مورد دیگر

James Cheney is a Personal Chair of Programming Languages and Systems at the University of Edinburgh, working in the Laboratory for Foundations of Computer Science within the School of Informatics. He leads the Principles of Provenance research group and has been a Turing Fellow from 2018 to 2023. His educational background includes a PhD in Computer Science from Cornell University (2004), an MS in Mathematics from Carnegie Mellon University (1998), and a BS in Computer Science and Mathematics from Carnegie Mellon University (1998). Cheney's research focuses on the intersection of databases and programming languages, with particular emphasis on data provenance. His work spans several key areas: Databases and data provenance Programming languages and compilers Generic programming Logic and automated theorem proving Compression and information theory XML and related technologies His recent publications demonstrate a strong focus on language-integrated query systems, type systems for programming languages, and formal approaches to data provenance. These works often bridge theoretical foundations with practical applications in database systems and programming language design. Cheney has received several notable awards and recognitions: Royal Society University Research Fellowship (2008-2016) Turing Fellow (2018-2023) ERC Consolidator Grant for the Skye project (2016-2021) Google Research Award for Language-integrated provenance As an advisor, Cheney has supervised numerous PhD students and postdoctoral researchers who have gone on to positions at institutions including New York University, LSE, University of Southampton, Meta, and others. His research has been supported by various grants from DARPA, EPSRC, AFOSR, EU FP7, and industry partners including Google, Microsoft Research, and Huawei. Cheney leads the Principles of Provenance group, which conducts fundamental research on data provenance and its applications in security, data curation, and scientific computing. The group has worked on projects including Skye (a programming language for scientific data curation), ADAPT (a DARPA-funded project on advanced persistent threat prevention), and language-integrated provenance systems.

• Data Mining
• Machine Learning
• Graph Mining
• +۹ مورد دیگر

Michalis Vazirgiannis is a Professor in the Department of Informatics at the Athens University of Economics and Business (AUEB), specializing in data mining and machine learning with applications in web and social network analysis. His work bridges theoretical algorithms and real-world scalability challenges. Education: Bachelor Degree in Informatics, National and Kapodistrian University of Athens, 1986 Master (M.Sc.) in Robotics, National and Kapodistrian University of Athens, 1988 Master (M.Sc.) in Knowledge Based Systems, Heriot Watt University, Edinburgh, 1989 Ph.D. in Informatics, National and Kapodistrian University of Athens, 1994 Research Focus: Professor Vazirgiannis pioneers clustering algorithms with subjective/objective validation, distributed feature selection for evolving graphs, and temporal link analysis for dynamic page ranking. His research addresses critical gaps in semi-supervised learning for large-scale web and social networks, emphasizing dimensionality reduction and ranking predictability in temporal contexts. Publication Trends: His 2007-dominated publications reveal a strategic shift toward graph-based web mining, with recurring themes of distributed processing (P2P similarity search), clustering validity frameworks, and semantic web personalization. The work consistently targets scalability bottlenecks in real-world network data. Scientific Recognition: ERCIM Post-doctoral Scholarship (2001) Marie Curie European Scholarship (2006) Leadership & Collaboration: As ERASMUS coordinator for AUEB's Informatics Department and editorial board member of Intelligent Data Analysis journal, he bridges academia and industry. His EU project leadership (FP6 SQO-OSS, Marie Curie NGWeMiS) and program committee roles (IEEE/ICDM 2008, ECML/PKDD 2008) highlight his influence in data mining standardization. International collaborations span INRIA, Fraunhofer, Max Planck, and IBM Research. Technical Innovation: His patent contributions and invited lectures at ECML/PKDD 2006/SIAM/SDM 2006 demonstrate applied impact, particularly in web personalization engines (SEWeP) and evolving graph analytics.

Antonia Saravanouمشاهده پروفایل

پژوهشگر

• Data Mining
• Machine Learning
• Anomaly Detection
• +۳ مورد دیگر

Antonia Saravanou is a Ph.D. graduate from the Department of Informatics and Telecommunications at the National and Kapodistrian University of Athens (NKUA), advised by Prof. D. Gunopulos. She holds an M.Sc. in Advanced Information Systems and a B.Sc. in Computer Science from the same department. Since 2011, she has worked as a Research Scientist and Engineer at NKUA and Athens University of Economics and Business (AUEB), and is affiliated with the Knowledge Discovery in Databases Laboratory (KDDLab) and the Management of Data, Information & Knowledge Group (Madgik). Her research spans Data Mining, Machine Learning, and Anomaly Detection, with a focus on Social Network Analysis, Graph Representations, and Healthcare Applications. She has completed research visits at Stanford University's Geometric Computing Group, Spotify Tech Research, and Bloomberg AI. Education: Ph.D., Informatics and Telecommunications, NKUA M.Sc., Advanced Information Systems, NKUA B.Sc., Computer Science, NKUA Her research explores graph-based methods for event detection in social networks, self-supervised node representation learning, and applications in healthcare and news analysis. Projects include music recommendation systems via graph representations, infant mortality prediction models using birth certificate data, and real-time news monitoring frameworks. She has also worked on knowledge graph applications for news ranking and anomaly detection in sparse time series data. Scientific Awards: Outstanding Reviewer for ICLR 2021 Top Reviewer for NeurIPS 2018 As a teaching assistant, she has supported graduate and undergraduate courses at NKUA, including Mining Big Datasets, Data Mining, and Artificial Intelligence. She actively participates in outreach programs like ACM Student Chapter UoA, Rails Girls Athens, and Django Girls.

Nikolaos E. Panagiotouمشاهده پروفایل

پژوهشگر

• Text Mining
• IoT/Smart-Cities
• Spatio-temporal Analysis
• +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.

• Semantic Web
• Digital Libraries
• Software Engineering
• +۷ مورد دیگر

Gioldasis Nektarios is a Lecturer in the School of Electronic and Computer Engineering at the Technical University of Crete , affiliated with the Distributed Information Systems and Applications Laboratory (TUC/MUSIC) . He has been a permanent member of the laboratory since 2006 and has contributed to numerous Research & Development projects. MSc in Informatics, School of Electronic and Computer Engineering, Technical University of Crete (2002) BSc in Applied Informatics, University of Macedonia (1999) His research interests span critical domains including: Semantic Web technologies and Open Linked Data Software engineering for Service Oriented and Multi-Tier Architectures Data modeling, metadata management, and semantic interoperability Digital libraries and multimedia management systems The article portfolio demonstrates expertise in XML-Semantic Web integration, query mediation, and cultural data systems, with a 2023 publication on location-based game platforms. Key trends include: Interoperability frameworks (2015-2012) Ontology-driven data access (2010-2009) Geospatial and cultural heritage applications (2011-2007)

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.

Sebastian Erdwegمشاهده پروفایل

استاد

• Programming Languages
• Software Engineering
• Incremental Computation
• +۷ مورد دیگر

Sebastian Erdweg is a Professor at the Institute of Programming and Software Engineering at Johannes Gutenberg University Mainz (JGU Mainz) in Germany. He actively contributes to the programming languages research community as evidenced by his extensive involvement in major conferences including PLDI, ECOOP, SPLASH, and ICFP. His leadership roles include serving as Workshops Co-Chair for ECOOP and ISSTA 2023, Steering Committee Chair for GPCE, and various program committee positions across multiple conferences. His research primarily focuses on programming language design and implementation, with particular expertise in incremental computation, Datalog-based systems, abstract interpretation, and language workbenches. Erdweg's work bridges theoretical foundations with practical applications in static analysis, compiler construction, and program transformation. His research demonstrates a consistent thread of improving developer productivity through better language design and tooling, with recent work emphasizing efficient incremental program analysis techniques. Erdweg's publication record shows a strong emphasis on Datalog as a foundation for program analysis, with increasing focus on incremental techniques and WebAssembly analysis in recent years. His work combines theoretical rigor with practical implementation, often resulting in open-source tools that advance the state of the art in language engineering. The consistent appearance of Datalog, incremental computation, and abstract interpretation across his publications indicates a cohesive research vision spanning over a decade. As an active member of the programming languages community, Erdweg has served in numerous organizational roles including Workshops Co-Chair for ECOOP and ISSTA 2023, Steering Committee Chair for GPCE, and various program committee positions. His contributions to conference organization demonstrate his standing within the academic community and commitment to advancing research in programming languages and software engineering.

Xiaokang Qiuمشاهده پروفایل

دانشیار

• Programming Languages
• Software Engineering
• Program Verification
• +۲ مورد دیگر

Xiaokang Qiu serves as Associate Professor in Purdue University's Elmore Family School of Electrical and Computer Engineering, specializing in Programming Languages and Software Engineering with core expertise in program verification, program synthesis, and automated deduction. His research establishes critical bridges between enumerative and deductive synthesis methodologies, developing novel frameworks for verified program generation. Key contributions include string transformation synthesis with concurrency guarantees, bit-vector manipulation optimization via syntax-guided enumeration, and network design automation through comparative learning techniques. This work consistently advances formal verification foundations while addressing practical software engineering challenges. Publication trends from 2017-2025 reveal escalating complexity in synthesis targets—from basic data-structure manipulations to concurrent string operations and network configurations. His approach increasingly integrates machine learning elements with formal methods, demonstrating how query-based learning can drive near-optimal system design while maintaining provable correctness guarantees across diverse computational domains.

Yannis Tzitzikasمشاهده پروفایل

استاد

• Semantic Data Integration
• Exploratory Search
• Knowledge Graphs
• +۲ مورد دیگر

Yannis Tzitzikas is Professor of Information Systems at the University of Crete and Affiliated Researcher at FORTH-ICS. He directs the Centre for Cultural Informatics and Semantic Access & Retrieval group, developing frameworks for large-scale semantic integration. His research enables exploratory analytics over RDF knowledge graphs, with applications in marine science and cultural heritage. Recent projects include BlueCloud (EU H2020) for marine data services and 4CH for cultural heritage preservation. Awarded six best paper/reviewer awards including ISWC'2022 and MTSR'2020. He coordinates the University of Crete's Open Data initiative and serves on ERCIM's executive committee.

• 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.

• Information Management
• Information Retrieval
• Text Categorization
• +۳ مورد دیگر

Kalamboukis Theodore serves as a Professor at Athens University of Economics and Business (AUEB), where he maintains active research and administrative roles. His institutional affiliation centers on AUEB's academic ecosystem, with significant leadership experience including two terms as Vice-Rector (2001-2007). His academic credentials include: BSc in Mathematics from Athens University Ph.D in Computer Science from the University of Glasgow Research activities prominently feature Information Management with specialized focus on cross-lingual text retrieval systems , medical information retrieval , and clustering-enhanced classification techniques . His methodological approach integrates computational linguistics with practical information system design, particularly addressing multilingual challenges in specialized domains like healthcare. Publication trends from 2004-2008 reveal consistent innovation in text processing architectures, with increasing emphasis on medical applications and cross-lingual solutions. His work demonstrates strong interdisciplinary connections between computer science, healthcare informatics, and linguistic engineering, particularly through clustering methodologies applied to classification problems. No scientific awards were documented in the provided materials. Academic supervision includes doctoral and Master's dissertations in Economics and Informatics. Research funding spans multiple high-impact projects: MedAS (2006): Cross-language medical retrieval and image systems TIME (2005): EU-ASIA ICT tele-imaging initiative Joint Research Programme (2002-2005): Collaboration with University of Iasi e-Lexicon (2002): Economic terminology digital dictionary DILOS (1999): Bilingual economic dictionary development He maintains active consultancy with EU research programs and Greece's General Secretariat for Research and Technology. As Administrator of AUEB's Information and Database Systems Laboratory, he directs research in database architectures and information management systems, providing infrastructure for text processing and cross-lingual applications development.

• Database Systems
• Virtual Reality Applications
• Digital Humanities
• +۴ مورد دیگر

Yannis Ioannidis is a Professor at the Department of Informatics and Telecommunications of the National and Kapodistrian University of Athens. His research spans interdisciplinary areas including database systems, virtual reality applications, and cultural heritage technology. He leads projects integrating technology with education, art, and social sciences, such as VR environments for urban planning (ARSINOE VR) and AI-driven scientific discovery frameworks. His work emphasizes collaborative tools for digital storytelling and participatory cultural experiences. Ioannidis has contributed to advancements in database query optimization, text exploration through SQL extensions (DETEXA), and indexing techniques for data lakes. His recent focus includes exploring the intersection of tabletop role-playing games with historical education and ethical AI-human coevolution. He actively participates in initiatives like the EBRAINS infrastructure for brain research and the MagicARTS social VR project. Notable research trends in his publications include leveraging VR for immersive learning, designing hybrid museum kits, and applying AI to support UN Sustainable Development Goals. His work bridges technical innovation with societal impact, addressing challenges in education, art preservation, and ethical technology use.