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Jean-Luc HainautView profile

Professor

• Reverse Engineering
• Database Application Engineering
• Information Systems Modelling
• +7 more

Jean-Luc Hainaut is a Professor at the Faculty of Computer Science , specializing in Database Application Engineering , Reverse Engineering , and Information Systems Modelling . His work spans theoretical and applied research in software engineering, with a focus on SQL symbolic execution , unit testing , and engineering tools . His research projects include: DB-MAIN : Database Application Engineering (1993–present) RetroWeb : Web Sites Reverse-Engineering Methodologies and Tools (2001–present) ReQuest : Research Program Schemas (2003–present) MIRROR : MedIcal Resource Real Time Optimizer (2012–2015) Key research areas: Reverse Engineering Database Evolution Symbolic Execution Healthcare Systems Modelling Automated Generation of Systems Selected publications highlight his contributions to SQL testing , data-oriented applications , and healthcare information systems . He has supervised numerous students and contributed to the Sustainable Development Goals related to Good Health and Well-being through medical resource optimization projects.

• Database Systems
• Semantic Web
• Graph Databases
• +3 more

Mirian HALFELD-FERRARI is a Professor at the University of Orleans , where she serves as Director of the Pamda Laboratory, member of the Sustainable Development Working Group, and International Relations Manager. Her research focuses on database systems, semantic web technologies, and graph data management. Key contributions include graph rewriting systems , RDF database evolution , and data consistency frameworks . Recent work explores clinical text-to-knowledge graphs , XML schema evolution , and context-driven urban data analysis . She collaborates with researchers across Europe on projects involving graph data science , service composition refinement , and semantic web sanitization . Her leadership roles include organizing workshops at conferences such as ADBIS and serving on editorial boards for international journals.

• Information Systems
• Data Analytics
• Business Intelligence
• +7 more

Nicolas PRAT is an Associate Professor at ESSEC Business School specializing in Information Systems, Data Analytics and Operations. He serves as Head of the Information Systems Track at the Cergy campus and has been with ESSEC since 1995, progressing from Lecturer to his current position as Associate Professor since 2006. His academic credentials include: Accreditation to supervise research (Université Paris Dauphine-PSL, 2012) PhD in Information Systems (Université Paris Dauphine-PSL, 1999) Specialized Master in Information Systems (ESSEC Business School, 1991) MSc in Management (ESSEC Business School, 1990) International Teachers Programme (Stockholm School of Economics, 2004) PRAT's research focuses on conceptual modeling, design science research, business intelligence, and knowledge management with increasing attention to emerging technologies like AI and blockchain. His work bridges theoretical foundations with practical applications, examining how data and knowledge engineering can support organizational decision-making processes. He has made significant contributions to understanding the evolution of conceptual modeling and taxonomy development for complex technologies. His recent publications demonstrate a clear research trajectory toward exploring generative AI's impact on business intelligence, sustainability frameworks for design science research, and advanced methods for taxonomy development in complex emerging technologies. These works reflect his ongoing engagement with cutting-edge developments while maintaining strong theoretical foundations in information systems research. Scientific recognition includes: Qualification to the function of full Professor in the French University system (Computer Science, 2013) PRAT has supervised doctoral research, including Demigha S. at Université Paris 1 Panthéon-Sorbonne in 2005. His academic leadership includes serving as Academic Director for specialized programs and Head of the Information Systems Track. He actively contributes to the scholarly community through editorial board memberships for "Systèmes d'Information et management" (since 2022) and "Journal of Database Management" (since 2013).

Dietmar SeipelView profile

Professor

• Logic Programming
• Deductive Databases
• Knowledge Engineering
• +5 more

Dietmar Seipel is a Professor at the University of Würzburg, affiliated with the Department of Computer Science within the Faculty of Mathematics and Computer Science. He has held this position since November 1995, establishing a distinguished academic career spanning over 25 years with significant contributions to logic-based computer science. Professor Seipel's research focuses on Logic Programming and Deductive Databases, with substantial expertise in Knowledge Engineering and Artificial Intelligence. His scholarly work bridges theoretical foundations with practical applications, particularly in rule-based systems, knowledge representation, and declarative programming paradigms. He has consistently advanced the field through both theoretical developments and practical implementations, creating tools that enable more effective knowledge management and reasoning systems. His publication trajectory demonstrates a clear evolution from foundational work in disjunctive logic programming to contemporary applications in knowledge representation and semantic technologies. Recent research shows continued innovation in integrating logic programming with modern programming languages and systems, including Python and JavaScript implementations. His work spans theoretical contributions to practical tool development, with applications across diverse domains including space systems, medical informatics, and business process management. Professor Seipel has made extensive contributions to the academic literature, with publications appearing consistently from the 1980s through to the present. His work has influenced both theoretical developments in logic programming and practical applications in knowledge-based systems. He has been actively involved in academic community building through conference organization, particularly for events related to declarative programming and knowledge management.

Dario ColazzoView profile

Professor

• Databases
• Programming Languages
• Cloud Computing
• +7 more

Dario Colazzo is a Professor at Université Paris-Dauphine, affiliated with the LAMSADE laboratory. His research focuses on database systems and programming languages, particularly in cloud databases, type systems for semi-structured data, and query processing optimizations. He has contributed extensively to XML and XQuery research, including parallel query execution and static analysis techniques. His teaching includes courses on programming (Java), UML, database systems, and semantic web technologies at both undergraduate and graduate levels (in French). Key research interests span XML/XQuery optimization, JSON processing, distributed systems, and type systems for safe and efficient data handling. His work emphasizes scalable cloud-based solutions and efficient query execution models. Publications highlight advancements in parallel query processing (e.g., PAXQuery), type-based optimizations for XML updates, and semantic graph analytics. He has collaborated with institutions like EDBT, WWW, and VLDB conferences.

Diego CalvaneseView profile

Visiting Professor

• Artificial Intelligence for Data Management
• Knowledge Representation and Reasoning
• Virtual Knowledge Graphs
• +5 more

Diego Calvanese is a Visiting Professor at Umeå University's Department of Computing Science and holds a full professorship at the Free University of Bozen-Bolzano, Italy. His research focuses on AI for data management, including virtual knowledge graphs (VKG), ontology-based data access (OBDA), and formal methods like description logics. He is part-time at Umeå, balancing roles with his primary position in Italy. Calvanese has received prestigious awards including the AAAI Classic Paper Award (2021), EurAI Fellow (2015), and ACM Fellow (2019). He supervises three doctoral students at Umeå and has authored over 350 publications, with an h-index of 71. His work emphasizes data integration, geospatial systems, and ethical AI applications. Key Roles: Associate Programme Chair (IJCAI 2025), Programme Chair (IJCAI-ECAI 2026), Head of AI for Data Management Research Group Research Interests: Knowledge representation, graph data management, explainable AI, and telemonitoring systems like reCOVeryaID. His research group develops tools like Ontop, a VKG system enabling seamless data access across heterogeneous sources. Current projects include geospatial data integration and temporal OBDA frameworks. Calvanese has served on over 150 program committees and editorial boards, including Artificial Intelligence and JAIR. His work bridges technical advancements with societal impacts, addressing AI's role in healthcare, climate, and democracy.

Ognjen SavkovicView profile

Assistant Professor

• Knowledge Graphs
• Semantic Web
• Database Management
• +7 more

Ognjen Savkovic is an Assistant Professor (RTD-a) at the KRDB Research Center for Knowledge and Data, Faculty of Engineering, Free University of Bozen-Bolzano, Italy. He is based at the NOI Techpark in Bolzano and is actively involved in research on Knowledge Graphs, Semantic Web, and data quality. His work bridges formal logic and machine learning to enhance data management systems. His research interests include Knowledge Graphs, Semantic Web, Database Management, Data Quality, Artificial Intelligence, and Logic Reasoning. He focuses on schema validation (e.g., SHACL), property graph schemas (PG-Schema), and integrating machine learning with declarative languages like Datalog for industrial applications such as welding quality monitoring and cloud resource configuration. His recent publications show a strong trend in semantic technologies for industrial applications, particularly in collaboration with Bosch and Siemens. His work spans theoretical foundations of schema languages and practical implementations in smart manufacturing and cloud systems. He has published in top venues including WWW, ISWC, CIKM, and SIGMOD. Scientific Awards: No specific awards mentioned. Ognjen Savkovic advises students and collaborates on research projects, though specific students are not listed. His research involves significant grant-funded collaborations, particularly in EU-level industrial AI and semantic technology initiatives. He has contributed to projects involving Siemens and Bosch, focusing on semantic diagnostics and scalable data science solutions. He is a key member of the KRDB Research Center, contributing to a vibrant research team working on knowledge representation, reasoning, and industrial applications of semantic technologies.

Andreas PierisView profile

Lecturer

• Database Theory
• Knowledge-Enriched Data
• Uncertain Data
• +6 more

Andreas Pieris is a Lecturer at the School of Informatics, University of Edinburgh, specializing in database theory with a focus on knowledge-enriched data, uncertain data, knowledge representation, and computational logic. He has held academic positions at Vienna University of Technology (Institute of Information Systems) and the University of Oxford (Department of Computer Science). His teaching includes the advanced course Advanced Topics in Foundations of Databases (ATFD) , covering relational query languages, XML databases, graph databases, and ontologies. Research Interests : Database theory, knowledge representation, computational logic, consistent query answering, and ontology-based data access. Collaborations : Extensive co-authorships with Marco Calautti, Ester Livshits, Markus Schneider, and others. Service : Regular participation in program committees of top-tier conferences like PODS, ICDT, IJCAI, AAAI, and KR. His recent publications analyze Datalog query provenance, chase termination algorithms, and consistent query answering under existential rules. He emphasizes the application of computational logic to database systems, leveraging complexity theory and automata for scalable solutions.

Kerstin SchneiderView profile

Professor

• Databases
• Data Engineering
• Workflow Management Systems
• +4 more

Kerstin Schneider is a full-time Professor for Databases at Harz University of Applied Sciences since 2007. She operates within the Faculty of Automation and Informatics , focusing on database theory, data engineering, and AI-driven educational technology solutions. Current research emphasizes adaptive e-learning platforms (ALEA system) Interdisciplinary projects in AI Engineering (AiEng 2021-2025) Custom database applications for SMEs (TEA project) Her research interests span: Reliable workflow execution in distributed systems Multimedia information systems Semantic data recommendations Temporal XML database models Recent publications (2021–2017) highlight trends in: Academic database foundations Intelligent e-learning architectures Life science data analytics Historical data visualization Scientific Awards : 2004 Research and Innovation Award of the Rhine-Neckar Triangle Foundation She contributes to academic governance through roles in: Steering Committee for Fundamentals of Databases Examination Board AI Engineering Senate Deputy at Harz University Equal Opportunities Officer for AI Department Key collaborative projects include: APRICOTS (CORBA-based workflow systems) GEIST (Intelligent History Information Systems) Team projects with international universities Open Educational Resources (OER) development

Florian RoseView profile

Researcher

• Database Systems
• Data Privacy
• Data Efficiency
• +2 more

Florian Rose is a researcher at the University of Rostock , affiliated with the Faculty of Computer Science and Electrical Engineering . He holds a B.Sc. (2019) and M.Sc. (2020) in Computer Science from the same university.

Fadila BentayebView profile

Associate Professor

• NoSQL Data Warehouses
• Text Warehousing
• Personalization & Recommendation Systems
• +5 more

Fadila Bentayeb is an Associate Professor (HDR) at the University of Lyon 2, affiliated with the ERIC Laboratory and the Department of Informatics and Statistics (DIS). She leads the Complex Data Warehousing and OLAP research team (SID) and has served as Head of the first year of the Master's degree in Computer Science at the Institute of Communication (ICOM) since 2014. Her work bridges academic research and practical applications in data-intensive systems. HDR (Habilitation to Direct Research), University of Lyon 2 (2011) Ph.D. in Computer Science, University of Orléans (1998) Her research focuses on NoSQL data warehouses, text warehousing, and personalization systems, with emphasis on scalable architectures and context-aware analytics. Recent work explores AI-driven security in IoT networks and temporal modeling for evolving data structures. Key trends in her publications include: (1) Graph-based multidimensional modeling (GAMM framework), (2) Optimization of distributed big data warehouses using machine learning, (3) Medical text classification via hybrid CNN-LSTM models, and (4) Temporal data warehouse evolution. As part of the ERIC Laboratory’s leadership team, she contributes to strategic research directions and mentors students in advanced data systems. Her technical expertise extends to Hadoop/Spark optimization, OLAP cube design, and semantic integration of heterogeneous data sources.

Curtis DyresonView profile

Professor

• Database Systems
• Software Systems
• XML Databases
• +3 more

Curtis E. Dyreson is a Professor in the Department of Computer Science at Utah State University. His research focuses on database systems, including temporal databases, XML databases, data cubes, and proscriptive metadata. He previously held faculty positions at James Cook University, Bond University, Washington State University, and was a visiting assistant professor at Aalborg University. He earned his Ph.D. from the University of Arizona under Richard T. Snodgrass and a bachelor's degree from New College. Education: Ph.D., Computer Science, University of Arizona (Advisor: Richard T. Snodgrass) Bachelor's Degree, New College Research Interests: His work spans advanced database systems, including temporal data management, XML schema evolution, and database interoperability. He has contributed to projects like Symbiota2, an open-source biodiversity data mobilization platform, and developed tools such as XMorph for XML transformation. His research emphasizes practical applications in fields like environmental science and healthcare. Publications: Over 129 publications, with recent work on Temporal JSON, plug-and-play database systems, and AI-driven pandemic screening. His articles explore topics such as query optimization, temporal SQL translation, and database indexing techniques. Awards: 2015 SIGMOD Contributions Award Advising & Grants: Advises graduate students including Vishal Sharma (PhD), Arihant Jain (M.Sc.), and Chetna Suryavanshi (M.Sc.). His grants include collaborative research on biodiversity data platforms and carbon modeling. Labs/Teams: Active in the Symbiota2 project, an international collaboration for biodiversity data sharing and visualization.

Evgeny KharlamovView profile

Associate Professor

• Artificial Intelligence
• Knowledge Representation
• Machine Learning
• +3 more

Evgeny Kharlamov is an Associate Professor at the University of Oslo and Senior Research Expert at Bosch AI. His research focuses on Neuro-Symbolic AI, Knowledge Representation (knowledge graphs, rules, ontologies), data integration, and applications in manufacturing, energy, and corporate intelligence. He has published over 190 papers in venues like IJCAI, AAAI, WWW, and holds an h-index of 41 with ~6K citations. Key awards include ranking 7th in the AI 2000 Knowledge Engineering list (2024) and top 111 German AI researchers (2023). **Education & Previous Roles**: Previously held positions at the Universities of Oxford and Bozen-Bolzano, INRIA Saclay, and Telecom Paris. His expertise spans individual research to managing teams at Bosch AI and coordinating a research center at the University of Oslo. He raised ~6.7M EUR in EU/UK research funding and led multiple large-scale EU projects. **Research Interests**: Combines theoretical advances in AI with industrial applications, emphasizing explainable and scalable solutions. Key areas include knowledge graphs, semantic web technologies, and LLM-centered systems like RAG. **Awards**: Notable recognitions include the 2020 Best Research Paper Award at ESWC, multiple ISWC awards (2015–2017), and IBM’s Best Master’s Thesis Award (2008). His PhD thesis was honored by AI*IA (2012). **Grants & Projects**: Co-secured ~6.7M EUR in funding. Led projects in semantic data integration (e.g., Siemens streaming data), digital twins, and predictive quality monitoring in manufacturing. **Teaching**: Taught courses on Digital Ecosystems (2024), Semantic Web (2023), Knowledge Graphs (2023), and Foundations of Databases (2007). **Labs/Teams**: Active in Bosch AI’s research initiatives and the University of Oslo’s data science teams, focusing on industrial AI applications.

Jesus Joaquin Garcia MolinaView profile

Professor

• Computer Science
• Database Systems
• Model-Driven Engineering
• +5 more

Jesus Joaquin Garcia Molina is a Professor in the Department of Computer Science and Systems Engineering at the Universidad de Murcia's Faculty of Informatics. He holds a Doctorate from the same university with a thesis on the conformational and dynamic study of flexible macromolecules (1988). His research focuses on database systems, model-driven engineering, NoSQL technologies, and software modernization. He is actively involved in projects related to schema evolution, user interface generation from wireframes, and AI applications in healthcare and education. Key research areas include database schema management, cross-platform data migration, and the development of unified query languages like Skiql. He has contributed to frameworks such as Guizmo for automated UI generation and tools for reverse-engineering legacy systems. His work bridges theoretical computer science with practical applications in software development and education technology. Recent publications emphasize NoSQL schema evolution, AI-driven radiology support systems, and the integration of interactive educational content in social robots. His interdisciplinary approach spans computer science, medicine, and pedagogy, with notable contributions to both academic and applied domains.

• Database Systems
• Semantic Heterogeneity
• Federated Databases
• +3 more

Dennis McLeod is a Professor at the University of Southern California , specializing in Database Systems , Ontology Engineering , and Semantic Heterogeneity resolution. His work bridges Federated Database Systems and Web Engineering , focusing on component-based architectures, adaptive ontologies, and geospatial data processing. Key Research Areas : Semantic heterogeneity, ontology-driven data mining, mobile web information management, and distributed systems. Collaborations : Extensive partnerships with researchers like Qing Li , Cyrus Shahabi , and Stefania Leone across institutions. Publications (2014-1995) span topics from component-based web engineering to distributed earthquake science , with recent work on geostreaming, social network tag-geotag analysis, and spam filtering using ontologies. His contributions include frameworks for multi-resolution document transmission , object-oriented database sharing , and adaptive query optimization in federated systems. Scientific Impact : Co-chairs and tutorials at major conferences (VLDB, CoopIS, ICDE). Co-edited proceedings for ICWL 2008 and contributed to Expert Database Systems (1989-1991). Pioneered INTERBASE for controlled sharing in federated databases (1990).