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Catherine FaronView profile

Professor

• Artificial Intelligence
• Knowledge Management
• Semantic Web
• +8 more

Catherine Faron is a Full Professor at Université Côte d'Azur , affiliated with the I3S laboratory and Inria center . She serves as vice-head of the Wimmics joint research team and leads the Artificial Intelligence and Data Engineering (IAID) program at Polytech Nice Sophia engineer school. Habilitation à diriger les recherches (HDR) in Computer Science, UCA (2017) PhD in Computer Science, Univ. Paris 6 (1997) Her research focuses on Artificial Intelligence , particularly in Knowledge Representation and Reasoning (KRR) and Semantic Web technologies. She develops hybrid intelligent systems combining KRR with machine learning for knowledge extraction, integration, and exploitation across education, health, and digital humanities. Recent publications highlight her work on: 2025 : Knowledge graphs for historical zoological data 2024 : Semantic annotation frameworks in agronomy 2023 : Agricultural data mapping and medical record enrichment 2022 : Visual exploration of big linked data Scientific recognitions include: 2023: Best Paper Award, ESWC 2017: Scientific Excellence Award, UCA 2016: Best Demo Award, ISWC 2015: Best Paper Award, IC 2008: Best PhD Paper Award, ECPPM She has supervised 19 PhD/Master's students and leads/has led projects like D2KAB , DEKALOG , and ZOOMATHIA , with partnerships across academic and industrial institutions.

• Big Data Analytics
• Cloud Computing
• Data Stream Processing
• +4 more

Yanlei Diao is a Professor of Computer Science at École Polytechnique (France) with a joint appointment at the University of Massachusetts Amherst. She received her PhD from UC Berkeley in 2005. Her research focuses on scalable data systems, particularly in big data analytics, cloud computing optimization, and real-time stream processing. Research Interests: Her work spans cloud infrastructure optimization (UDAO project), explainable anomaly detection in data streams (EXAD), interactive data exploration (AIDEme), genomic data analysis (GESALL), and uncertain data management (CLARO). She leads the CEDAR team at Inria/LIX focusing on cloud-scale data exploration. Awards & Honors: ERC Consolidator Grant (2017-2023) CRA-W Borg Early Career Award (2013) NSF CAREER Award (2008) Keynote speaker at ACM DEBS 2021 and SWIFT 2023 AI Forum Best Paper Award at SIGMOD 2011 ACM SIGMOD Dissertation Honorable Mention (2005) Advising & Leadership: Mentored over 20 PhD students and postdocs, currently supervising 7 researchers. Served as PVLDB PC Co-Chair (2025-2026) and ACM SIGMOD Editor-in-Chief (2014-2019). Leads multiple projects with industry partners including Alibaba Cloud.

Marco Antonio CasanovaView profile

Professor

• Database Systems
• Conceptual Modeling
• Semantic Web
• +5 more

Marco Antonio Casanova is a Full Professor at the Department of Informatics and Coordinator of the Central Planning and Evaluation Office of the Pontifical Catholic University of Rio de Janeiro (PUC-Rio). He has held significant leadership positions at PUC-Rio including Graduate Program Coordinator (2005-2007) and Director of the Department of Informatics (2007-2011). His research interests concentrate on database conceptual modeling, construction of database management systems, and applications of Large Language Models. Dr. Casanova's work focuses on technologies that facilitate the dissemination and interpretation of data on the Web, with particular emphasis on techniques for designing databases to facilitate interoperability. His academic journey began with a degree in Electronic Engineering from the Military Institute of Engineering (1974), followed by an M.Sc. in Informatics from PUC-Rio (1976), and culminated with an M.Sc. (1978) and Ph.D. (1979) in Applied Mathematics from Harvard University. His recent publications (2023-2025) demonstrate a strong focus on the intersection of Large Language Models with database technologies, particularly in developing advanced Text-to-SQL and Text-to-SPARQL systems. His research spans both theoretical database concepts and practical applications across various domains including engineering, healthcare, and cultural heritage. Dr. Casanova has been particularly active in exploring how LLMs can enhance traditional database query interfaces while addressing real-world challenges in complex database environments. Scientific Recognition: Recipient of the Scientific Merit Award from the Brazilian Computer Society (2012) CNPq Level 1B Productivity Grant recipient Dr. Casanova maintains an active research program with numerous collaborations across Brazil and internationally. His work bridges theoretical database research with practical applications, particularly in the evolving landscape of AI-enhanced database systems. He has contributed significantly to the field of semantic technologies, knowledge graphs, and natural language interfaces to databases, with a recent emphasis on leveraging Large Language Models to solve longstanding database interoperability challenges. His laboratory and research team at PUC-Rio focus on developing innovative approaches to database management that incorporate cutting-edge AI techniques while maintaining strong theoretical foundations in database systems.

• Database Theory
• Computational Logic
• Parameterized Complexity
• +4 more

Reinhard Pichler is a Full Professor at the Vienna University of Technology (TU Wien), affiliated with the Faculty of Informatics and the Department of Databases and Artificial Intelligence . His research focuses on Database Theory , Computational Logic , and Parameterized Complexity . He leads multiple research projects like DeConquer (2023–2027) and HyperTrac (2018–2022), addressing challenges in query optimization and hypergraph decompositions. He holds the prestigious START Prize (2014–2022) for young researchers. His work spans theoretical foundations (e.g., hypertree decompositions) and practical applications (e.g., SPARQL query processing systems like SparqLog). He contributes to academic governance, serving on faculty councils and curriculum commissions. His research innovations bridge algorithmic theory and real-world database systems, emphasizing efficient query evaluation and tractability analysis. Key contributions include advancing fractional hypertree decompositions , SPARQL query optimization , and consistent query answering . His projects often involve collaborations with industry and international funders like the Austrian Science Fund (FWF) and Vienna Science and Technology Fund (WWTF). He actively publishes in top venues like Journal of the ACM , ACM Transactions on Database Systems , and Proceedings of the VLDB Endowment . His academic leadership extends to course design, teaching advanced topics like Complexity Theory and Theoretical Computer Science . He mentors doctoral students and oversees research teams exploring cutting-edge areas like uncertain databases and cloud-based computational social choice .

Maribel AcostaView profile

Professor

• Databases
• Semantic Web
• Artificial Intelligence
• +3 more

Maribel Acosta is a Professor of Databases and Information Systems at Ruhr-Universität Bochum's Faculty of Computer Science. She holds affiliations with the Institut für Neuroinformatik (INI), focusing on interdisciplinary research combining natural and artificial cognitive systems. Her work spans databases, semantic web technologies, artificial intelligence, and machine learning applied to knowledge graphs. Acosta earned her Ph.D. (Summa Cum Laude, 2017) and Master's in Computer Science from Karlsruhe Institute of Technology (KIT). She has held roles including Junior Professor at RUB (2020–present), Deputy Professor at KIT (2019–2020), and Assistant Lecturer at Heidelberg University (2020). Research Interests: Her primary research focuses on efficient querying of knowledge graphs, integration of machine learning in data management, and semantic web technologies. Key areas include knowledge graph population, federated query processing, and stability in neural networks. Recent work explores applications in automotive systems and social science data integration. Awards: Notable recognitions include a 2022 WWW Best Paper nomination, Aminer's Top-100 Influential Scholars (2020–2021), and multiple teaching excellence awards from KIT (2017–2020). Teaching & Labs: She teaches courses on database systems, knowledge graphs, and artificial intelligence at RUB. Her lab contributes to projects like SMART-KG and has pioneered federated SPARQL query frameworks. She actively supervises doctoral research in knowledge graph applications and machine learning.

Oscar Romero MoralView profile

Professor

• Data Management
• Data Science
• Data Governance
• +7 more

Oscar Romero Moral is a Professor at the Polytechnic University of Catalonia (UPC), affiliated with the Department of Services and Information Systems Engineering at the Barcelona School of Informatics (FIB). He leads research in the inSSIDE, inLab FIB, and DTIM groups, focusing on data management, data science, and big data technologies. His work emphasizes knowledge graphs, data governance, and machine learning integration with data systems. Affiliations: UPC, inSSIDE, inLab FIB, DTIM Group Research Interests: Data Management, Data Engineering, Big Data, Knowledge Graphs, Data Governance, Machine Learning Integration He has authored over 276 academic contributions, including peer-reviewed articles on federated healthcare data systems, GPU-accelerated workflows, and graph-driven data integration. His recent work addresses challenges in heterogeneous computing, automated data governance, and scalable data architectures. Romero has served on the program committees of major conferences like VLDB, ICDE, and EDBT, and led competitive research projects in data systems and analytics. He collaborates extensively with industry partners and academic institutions, driving innovations in distributed data management and edge computing.

Arka GhoshView profile

Researcher

• Heterogeneous data integration
• Ontology-based data access (OBDA)
• GeoBigdata (Spatial and Temporal Raster) integration and management
• +7 more

Arka Ghosh is a doctoral student and knowledge engineer at Umeå University , Department of Computing Science. He is affiliated with the AI for Data Management research group led by Prof. Dr. Diego Calvanese. Research focus: Virtual Knowledge Graphs (VKGs), heterogeneous data integration, and management of geospatial/raster data Email: arka.ghosh@umu.se Research Areas: Ontology-based data access (OBDA), semantic querying with SPARQL and NLP, Description Logic formalisms, raster/vector data processing, and temporal-spatial data modeling. Publications: Recent work presented at RuleML+RR 2024 and 2023 conferences includes extending VKG systems to handle large-scale satellite raster data and reformulating queries across heterogeneous data sources.

Axel PolleresView profile

Professor

• Semantic Web
• Knowledge Engineering
• Data Management
• +12 more

Axel Polleres is a full professor in the area of 'Data and Knowledge Engineering' at the Vienna University of Economics and Business (WU Wien) and a faculty member at the Complexity Science Hub (CSH) in Vienna, a position he has held since January 2017. His work bridges academic research and real-world applications in semantic technologies, knowledge graphs, and data governance. His research interests lie at the intersection of semantic web technologies, knowledge engineering, and data management. Focused on querying and reasoning over ontologies, logic programming, and rule-based systems, he explores how structured data can be effectively managed, validated, and integrated—especially through standards like SPARQL and SHACL. His work extends to applications in open data, legal data, biomedical informatics, and socio-environmental challenges such as climate and public health. The most recent publications highlight a growing trend toward practical and societal applications of knowledge graphs, including climate risk assessment, crisis response, healthcare accessibility, and open data governance. These works combine technical rigor in semantic modeling with impactful real-world use cases, particularly in European and Austrian contexts. Axel Polleres has been actively involved in international standardization, notably as co-chair of the W3C SPARQL Working Group, and serves on the editorial boards of the Semantic Web Journal and Journal of Web Semantics . He has contributed to numerous European and national research projects and has published over 100 articles in top-tier journals and conferences. He advises and collaborates with researchers across disciplines and institutions, contributing to interdisciplinary teams working on complex societal challenges. His work is supported by significant research grants, though specific funding sources are not detailed in the provided text. He leads and participates in research groups focused on semantic technologies, knowledge graphs, and data-driven policy.

• Semantic Web
• Knowledge Representation
• Graph Data Management
• +4 more

Shqiponja Ahmetaj is an Assistant Professor in the Department of Knowledge-Based Systems at the Faculty of Informatics, TU Wien. She specializes in semantic web technologies, knowledge representation, and graph data management. Her research focuses on SHACL validation, ontology integration, and formal methods for constraint satisfaction in graph databases. Education: PhD in Computer Science, TU Wien (2019): 'Rewriting approaches for ontology-mediated query answering.' MSc in Computer Science, TU Wien (2013): 'Planning in graph databases under description logic constraints.' Roles: Course instructor for 'Introduction to Artificial Intelligence,' 'Knowledge-based Systems,' and 'Semantic Technologies.' Principal investigator in projects like FRESH (2021–2026) and SEE (2012–2016). Research Interests: Her work addresses challenges in semantic web validation, ontology semantics, and graph data evolution. She develops formal methods for SHACL constraint validation, explanation generation for non-validation, and repair algorithms. Her contributions bridge the gap between semantic web standards and practical database systems. Her recent publications focus on SHACL validation of evolving graphs , ontology-ontology interoperability , and consistent query answering under constraints . Projects like FRESH emphasize theoretical and applied aspects of SHACL in knowledge graphs. Grants & Projects: FRESH (FWF, 2021–2026): 'Shapes in Graph Data: Theory and Implementation.' SEE (WWTF, 2012–2016): 'SPARQL Evaluation and Extensions.' Advising: Supervised theses such as 'SHACL validation of evolving RDF graphs' (2023) and 'A metaheuristic approach to crowdsourced package delivery' (2023). Labs/Teams: Active in TU Wien's research groups on semantic technologies and knowledge representation, collaborating with international institutions on projects like OMEGA and KtoAPP.

• Semantic Web
• Internet of Things
• Stream Reasoning
• +5 more

Pieter Bonte is a FWO Senior postdoctoral fellow and IMEC Postdoctoral researcher at Ghent University's Faculty of Engineering and Architecture, Department of Information Technology. His research focuses on Semantic Web technologies, stream reasoning, and Internet of Things applications. His research interests span Semantic Web, Internet of Things, Stream Reasoning, Knowledge Graphs, Context-aware Systems, RDF Processing, Linked Data, and Healthcare Informatics. His work bridges theoretical semantic technologies with practical applications, particularly in healthcare and IoT domains. Bonte's publication record shows a strong focus on streaming data processing, with numerous papers on Streaming Linked Data, context-aware query derivation, and semantic reasoning frameworks. His research demonstrates a progression from foundational semantic web technologies toward practical implementations in healthcare and IoT applications, with an increasing emphasis on privacy considerations and efficient processing techniques. His work frequently involves collaborations with Femke Ongenae, Filip De Turck, and other researchers at Ghent University and IMEC, indicating strong institutional research networks. His publications appear in respected venues including the Journal of Web Semantics, Semantic Web Journal, and various conference proceedings in the semantic technologies field.

• Database Systems
• Data Management
• Data Mining
• +4 more

Michael Grossniklaus is a Professor at the University of Konstanz, Germany, specializing in database systems, data management, and information systems. His research focuses on query optimization, social media data streams, and object-oriented databases. He has contributed to the development of C-SPARQL for RDF stream processing and frameworks for adaptive data management. Grossniklaus has collaborated extensively with researchers in areas such as trajectory data modeling, cloud database optimization, and context-aware systems. His work emphasizes practical applications in education technology, mobile computing, and semantic web technologies. Affiliation: University of Konstanz, Germany Key Research Areas: Database Systems, Data Mining, Social Media Analysis, Query Optimization Notable Projects: C-SPARQL, Sahara (cloud database optimization), LPLM (neural cardinality estimation) Recent publications highlight advancements in neural models for cardinality estimation, trajectory data models, and memory optimization in cloud databases. His interdisciplinary approach bridges theoretical foundations with real-world applications in education, social media, and mobile systems.

Antonio García CabotView profile

Associate Professor

• Artificial Intelligence
• Educational Technology
• Natural Language Processing
• +5 more

Antonio García Cabot is an Associate Professor in the Department of Computer Science at the University of Alcalá. His research focuses on artificial intelligence, educational technology, natural language processing, and mobile computing. He leads the INTELIA research group (Interaction Technologies and Artificial Intelligence Lab) and previously contributed to the PMI group (Intelligent Mobile Platforms). He earned his Doctorate in Computer Science from the University of Alcalá in 2013 with a thesis titled *Propuesta de un sistema multi-agente para la adaptación de contenidos docentes a las competencias, contexto y dispositivo del usuario*. His work emphasizes accessibility in digital education, gamification in MOOCs, and software engineering innovations like automated code repair using LLMs. Research trends in his 2024-2025 publications include: Advancing AI applications in educational assessment (e.g., automated question generation, distractor design) Improving mobile app usability through gesture-based interfaces and sensor integration Developing large language model-based tools for vulnerability repair and teacher simulation analysis Systematic reviews on digital competence ecosystems and multilingual AI systems His contributions to open educational resources (OER) and accessible virtual campuses have been widely adopted in Latin America. Current research extends into embedded systems education and olfactory stimuli impacts on mobile app performance.

• Artificial Intelligence
• Educational Technology
• Mobile Applications
• +3 more

Eva García López is a Professor in the Department of Computer Science at the University of Alcalá. She holds a PhD from the same institution, completing her thesis on improving the usability of interfaces for teaching objects in m-learning in 2013. Her research focuses on usability engineering, artificial intelligence, and educational technology, with emphases on mobile applications, accessibility, and gamification. She is affiliated with the INTELIA research group (Interaction Technologies and Artificial Intelligence Lab) and previously contributed to TIFyC (Information Technologies for Training and Knowledge) and PMI (Intelligent Mobile Platforms). Eva’s work spans developing adaptive learning systems, enhancing digital content accessibility, and leveraging large language models for educational tools. Her projects include MOOC development, social gamification experiments, and usability evaluations of mobile instant messaging apps. She has also explored the impact of olfactory stimuli on user performance and the application of NLP in automated question generation. Her contributions include guidelines for accessible digital content creation and frameworks for personalized learning paths in web engineering curricula. Her research integrates interdisciplinary approaches, combining machine learning, human-computer interaction, and educational theory to address challenges in digital learning ecosystems. Notable contributions include frameworks for curriculum development, methodologies for usability evaluation, and tools for automated code vulnerability repair.

Petra HermankovaView profile

Assistant Professor

• Digital Epigraphy
• Greek Epigraphy
• Latin Epigraphy
• +5 more

Petra Hermankova serves as an Assistant Professor in Classical Archaeology at Aarhus University's School of Culture and Society, where she also contributes to the Social Resilience Lab. Her academic appointment is active with ongoing projects through 2025 and recent publications in 2025 confirm her current faculty status. Her research focuses on digital epigraphy and the application of computational methods to ancient inscriptions. She employs text mining, machine learning, and social network analysis to study inscription functions across Graeco-Roman societies, economic history patterns, and labor specialization. Her work emphasizes FAIR and Open Science principles in archaeological data management, particularly through leadership in the Epigraphy.info initiative which develops international standards for digital epigraphy. Hermankova's publication trends reveal increasing engagement with computational approaches to ancient social networks and epigraphic big data , with recent work integrating SPARQL querying, RDF modeling, and network visualization techniques. Her research bridges traditional archaeological methods with cutting-edge digital humanities tools, focusing on Mediterranean communities from Thrace to the Roman Empire. She actively participates in major collaborative projects including The Past Social Networks Project (Carlsberg Foundation, 2022-2025), PPAP: Perachora Peninsula Archaeological Project (2019-2024), and SDAM: Small data - Big Challenges (2019-2023). Hermankova regularly organizes international workshops through Epigraphy.info and teaches practical courses in digital epigraphy methodology.

Ruben VerborghView profile

Professor

• Decentralized Web Technology
• Semantic Web
• Linked Data
• +5 more

Ruben Verborgh is a Professor of Decentralized Web Technology at IDLab of Ghent University – imec and a Visiting Fellow at the Oxford Martin School within the University of Oxford . As a hybrid academic and industry expert, he serves as a Solid Ecosystem Architect for Inrupt and advises other companies on decentralized data architectures. His research focuses on enabling a post-Big Data era through decentralized knowledge graphs, where individuals control their data storage and sharing. He investigates technologies that balance societal trust with economic incentives , aiming to dismantle data harvesting business models. Key areas include Linked Data , Web APIs , and trust envelopes for responsible data reuse. Recent publications emphasize automated policy negotiation , ODRL policy interoperability , and query optimization in Solid environments. His work spans decentralized healthcare data, semantic transport systems, and rule-based agents for personal data stores, reflecting a cross-disciplinary approach to digital trust and data sovereignty . As a co-designer of the Solid ecosystem , Verborgh contributes to projects like Components.js for dependency injection and Comunica for federated SPARQL query engines. His collaborations with institutions such as Oxford and industry partners highlight his role in bridging academic innovation with real-world implementation .