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Daniel WeidnerView profile

Researcher

• Artificial Intelligence
• Data Mining
• Deductive Databases
• +5 more

Daniel Weidner is a researcher at the Chair of Computer Science VI (Artificial Intelligence and Knowledge Systems) within the Faculty of Mathematics and Computer Science at the University of Würzburg. His work spans declarative programming, database systems, and artificial intelligence applications. Primary affiliation: Chair of Computer Science VI, University of Würzburg Research focus: AI-driven database systems and logic programming His research interests include declarative technologies, logic programming, and their applications in data mining, tennis analytics, and NoSQL databases. He has extensively contributed to the development of tools that bridge Prolog and Python environments. Weidner has supervised multiple theses and seminar papers, including works on tennis trajectory recognition, heating system data analysis, and declarative program evaluation. His projects often involve Python-based implementations of deductive database systems. Supervised: 4 bachelor's, 2 master's theses Teaching roles: Logic programming, database exercises, and advanced database seminars Scientific awards: No explicit honors mentioned in available records.

Achim RettingerView profile

Professor

• Machine Learning
• Knowledge Representation
• Natural Language Processing
• +4 more

Achim Rettinger is a full professor at Trier University, leading the research group krAil (Knowledge Representation Learning). He specializes in machine learning, natural language understanding, and human-centered AI. His work focuses on expressive knowledge representations and their applications in semantic technologies. Education: Studied Computer Science at Universität Koblenz (Germany), University of Georgia (USA), and University of Alberta (Canada). PhD in machine learning at TU Munich/Siemens AG, followed by habilitation at KIT (2016). Served as interim professor at Karlsruhe Institute of Technology (2018/19). Research interests include knowledge graphs, cross-lingual semantic annotation, and data-driven analysis in political and medical domains. Notable contributions include the X-LiSA framework and work on semantic web technologies. Awards include best paper and challenge awards at ISWC and ESWC conferences. Leadership roles include senior PC member at ISWC, track chair at ESWC, and membership in AI for Good Foundation. Active in EU projects, DFG grants, and large-scale collaborative initiatives. Key projects: BreXearch (cross-lingual Brexit analysis), xLiMe System (semantic search), and medical decision support systems for liver surgery. Collaborates with interdisciplinary teams on cognition-guided surgery and data integration. Publications span top venues like ISWC, NeurIPS, ICLR, and CVPR, with a focus on semantic web, machine learning, and applied AI solutions.

Stefan EdlichView profile

Professor

• Data Science
• NoSQL Databases
• Big Data Analysis
• +7 more

Prof. Dr. Stefan Edlich is a Professor at the Beuth University of Applied Sciences Berlin, leading the Data Science Master program and the Data Science Lab. He holds a Dr. med. Ing. and has authored 13 books, including the world's first NoSQL book. His research focuses on NoSQL databases, Big Data systems, AI applications in health, industry, and education, and data quality. Edlich organizes conferences on Big Data, functional programming, and Clojure, and manages the NoSQL Archive. He has been part of the Berlin Big Data Center (BBDC) since 2014. His work spans over 60 publications, with recent contributions in AI-driven healthcare, blockchain, and distributed systems. He advises students and maintains strong industry ties with companies like Zalando, Amazon, and IBM. His teaching excellence has earned him the 'Top 25 Lecturer' award multiple times at Beuth. Edlich's collaborations include projects like the MOMO mobile app for machine learning and the BBC-DaaS open-data platform. Research interests include data science applications in biodiversity, HCI innovations, and education technology. He actively contributes to open-source projects like Clarango (Clojure driver for ArangoDB) and advocates for data literacy through the Stifterverband initiative.

Katja ZeumeView profile

Professor

• Databases
• Information Systems
• Semi-structured Data
• +5 more

Prof. Dr. Katja Zeume serves as Professor and Dean of the Faculty of Computer Science and Communication at the Westphalian University of Applied Sciences in Gelsenkirchen, Germany. Her academic leadership spans theoretical and applied database systems research with emphasis on semi-structured data management. Her educational foundation includes a PhD from the University of Bayreuth (2015), where she completed her thesis "Foundations of Regular Languages for Processing RDF and XML" under the name Katja Losemann. Dr. Zeume's research centers on the theoretical underpinnings of database query languages, particularly investigating regular expressions in SPARQL for RDF and XML data models. Her work bridges formal language theory with practical database applications, addressing challenges in query complexity, data federation, and schema design for unstructured information. Key contributions include foundational analyses of deterministic regular expressions and their computational properties in semantic web contexts. Her publication trajectory reveals consistent focus on theoretical database foundations, evolving from XML schema research toward SPARQL complexity analysis. The body of work demonstrates deep integration of automata theory, complexity analysis, and practical query language design for modern data ecosystems. As Dean of the Faculty of Computer Science and Communication, she oversees academic strategy while maintaining active research engagement. Her teaching portfolio includes core database systems courses covering traditional SQL, NoSQL architectures, web-scale data management, and theoretical database principles.

Prashant SrivastavaView profile

Researcher

• Machine Learning
• Deep Learning
• Image Analysis
• +5 more

Prashant Srivastava is a Researcher at the Department of Systems Biology and Bioinformatics under the Faculty of Computer Science and Electrical Engineering at the University of Rostock, Germany. His work bridges machine learning with bioinformatics and financial risk modeling. Education: MSc Data Science and Analytics (2018-2020) from Royal Holloway, University of London Integrated B.S.-M.S. in Physics (2013-2018) from Indian Institute of Science Education and Research, Kolkata Master's Thesis in Computer Science (2020) on statistical risk methods in financial markets Master's Thesis in Physics (2017-2020) on extraordinary transmission in silicon-based micro-meter wire grid polarizers Research Focus: Prashant specializes in machine learning and deep learning applications. His work spans bioinformatics (bitter peptide prediction), data science (ConvGeN algorithm for imbalanced datasets), and financial risk modeling using VaR and Expected Shortfall frameworks. Recent Publications: His research trends include graph neural networks for peptide analysis, convex space learning for generative oversampling, and self-attention mechanisms for molecular interaction extraction from biological texts. Technical Expertise: Proficient in Python (numpy, scipy, tensorflow), R, C++, MATLAB, cloud computing (Azure), and database systems (SQL, NoSQL). He develops libraries like mgarch for GARCH modeling and applies advanced ML techniques (CNN, RNN, GAN, NLP) across domains. Labs & Teams: Active member of the Systems Biology and Bioinformatics group at the University of Rostock, contributing to interdisciplinary research at the intersection of computer science and life sciences.

• Data Science
• Energy Industry Applications
• Data Engineering
• +5 more

Volker Herbort serves as Professor and Dean of Business Informatics at Ulm University of Applied Sciences (THU). His academic work bridges business informatics with practical applications in the energy sector, focusing on data-driven approaches to modern energy challenges. Herbort's research interests center around Data Science applications in the Energy Industry , Data Engineering , and Digital Transformation . His work particularly emphasizes photovoltaic systems analysis, machine learning applications for energy monitoring, and business model innovation in utility sectors. He has developed expertise in Big Data technologies, NoSQL databases, and business analytics frameworks that support energy industry transformation. Analysis of his publication record reveals a consistent research trajectory focused on photovoltaic system performance analysis, with increasing integration of machine learning approaches since 2016. His work spans technical aspects of solar energy systems while also addressing business model transformations in the energy sector, particularly through his Utility 4.0 framework. The research shows strong practical application focus, especially in German energy markets. Herbort teaches courses in Big Data & NoSQL, Business Analytics, Database Programming, and fundamentals of business informatics, reflecting his dual expertise in information systems and energy applications. Available at room Q259 (Albert-Einstein-Allee 53-55, 89081 Ulm) with consultation hours by appointment, he maintains an active research profile as evidenced by his ResearchGate profile and recent publications through 2024.

Holger MeyerView profile

Professor

• Databases
• Digital Libraries
• Information Retrieval
• +5 more

Dr. Holger Meyer is a faculty member at the University of Rostock's Faculty of Computer Science and Electrical Engineering, specifically in the Institute of Computer Science. He is based at the Konrad Zuse House on Albert-Einstein-Straße 22, Room 332, and can be reached at phone number 0381-498 7597 or via email at hme@informatik.uni-rostock.de. Dr. Meyer teaches a variety of database-related courses including Database Application Programming (Bachelor), Databases for Users (Bachelor), Databases III (Master), and Digital Libraries and Multimedia Information Retrieval (Master). He also supervises projects under KSWS/Project/NEidI. His research focuses on database systems, digital libraries, information retrieval, data science, and XML database technologies. Dr. Meyer has made significant contributions to the development of digital archive systems, particularly through the Hydra.PowerGraph System, which enables building digital archives with directed and typed hypergraphs. His work also extends to applying crowdsourcing techniques in cultural heritage projects like the Mecklenburg Field Name Archive and developing SQL-based approaches for machine learning and signal processing tasks. Dr. Meyer's recent publications (2017-2019) demonstrate a strong emphasis on practical applications of database technologies across diverse domains including environmental monitoring (particulate matter analysis), automotive engineering, digital humanities, and historical geography. His work bridges theoretical database concepts with real-world applications, particularly through SQL-based implementations of machine learning operations and signal processing techniques. Throughout his career, Dr. Meyer has collaborated extensively with colleagues at the University of Rostock, particularly with Professor Andreas Heuer, Meike Klettke, and other researchers in the database and information systems group. These collaborations have resulted in numerous publications in prestigious venues including Datenbank-Spektrum, LNI proceedings, and international conferences.

Stephan KleukerView profile

Professor

• Software Development
• Quality Assurance
• Theoretical Computer Science
• +5 more

Prof. Dr. Stephan Kleuker is a faculty member at Osnabrück University of Applied Sciences , specifically within the Faculty of Engineering and Computer Science . He focuses on Software Development , Quality Assurance , and Theoretical Computer Science , with a particular interest in formal methods and practical software engineering education. Role: Chair of Software Development Contact: s.kleuker@hs-osnabrueck.de | Phone: 0541 969 3884 Research Interests Quality Assurance through Testing and Model Checking Formal Methods in Software Development Model-Driven Development and UML Business Process Modeling and Optimization Integration of Requirements Analysis with Quality Measures Teaching Current courses: Object-Oriented Analysis and Design, Software Quality Management, Theoretical Computer Science Focus on practical software development education with tools like Eclipse, Netbeans, and Apache Derby Projects Developed environments for teaching (e.g., 2 GB SEU package) Research on test automation, requirements modeling, and distributed Java programs Tools & Publications: Creator of tools like Interaction Board for Java beginners, and author of textbooks on Software Engineering with UML and Quality Assurance through Software Testing .

• Cybersecurity
• Privacy
• Threat Modeling
• +5 more

Wouter Joosen is a Professor at KU Leuven (Catholic University of Leuven) in Belgium, with an extensive research career spanning from 1988 to the present. His primary research focuses on cybersecurity, privacy, and secure software engineering, with significant contributions to threat modeling frameworks, particularly LINDDUN. Dr. Joosen's research interests center around privacy-enhancing technologies , security threat modeling , and machine learning applications in cybersecurity . His work bridges theoretical security concepts with practical implementations, focusing on real-world security challenges in cloud computing, authentication systems, and data protection. He has pioneered approaches to automate threat modeling processes and develop robust security mechanisms for modern distributed systems. His publication record shows a clear evolution from traditional software security in the 1990s-2000s to contemporary research on privacy-preserving machine learning, secure infrastructure as code, and advanced authentication systems. A notable trend in his recent work (2021-2025) is the integration of machine learning techniques to enhance security mechanisms while maintaining privacy constraints, particularly in access control systems and threat modeling frameworks. Dr. Joosen has collaborated extensively with researchers across Europe, particularly with Dimitri Van Landuyt, Davy Preuveneers, Danny Hughes, and Bert Lagaisse, indicating strong research group leadership and international collaboration. His research has significant practical applications in GDPR compliance, secure authentication, privacy-preserving technologies, and robust security frameworks for cloud-native applications. His work on OAuth 2.0 security, biometric authentication, and infrastructure security directly addresses current industry challenges in securing modern web applications and services.

• Semantic Web Services
• B2B Integration
• Workflow Management
• +3 more

Christoph Bussler is a prominent researcher with extensive contributions to Semantic Web Services B2B Integration Cloud Computing Workflow Management Enterprise Application Integration His work focuses on semantic technologies, data engineering, and optimization frameworks. Recent publications analyze Cloud storage tier optimization Graph-based cost modeling Taxonomy for cloud storage costs Serverless-container hybrid systems SQL for NoSQL databases These studies emphasize scalable solutions and semantic interoperability. He has collaborated with experts like Dumitru Roman, Radu Prodan, and Dieter Fensel on projects involving Triple Space Computing WSMX Architecture Peer-to-Peer Service Discovery Rule-Based Classification

• Database Systems
• NoSQL Databases
• Cloud Data Management
• +7 more

Norbert Ritter is a professor at the University of Hamburg, Germany, with a long-standing and active research career in database systems and data management. His work spans from foundational database theory to modern cloud and real-time systems, with significant contributions to NoSQL, polyglot persistence, and web performance optimization. He collaborates extensively with researchers such as Wolfram Wingerath, Felix Gessert, and Fabian Panse, and has published consistently in top-tier venues including VLDB, ICDE, and BTW. Research Interests: Database Systems NoSQL and Cloud Data Management Real-Time and Stream Processing Probabilistic and Incomplete Data Web Compression and Performance Spatiotemporal and Simulation Data His recent publications (2020–2024) show a strong focus on polyglot data management, adaptive systems, and efficient web encoding techniques. These works reflect trends toward heterogeneous storage, intelligent compression, and scalable simulation data handling, particularly in smart city and scientific contexts. The integration of machine learning with spatiotemporal data and graph-based modeling is also emerging as a key theme. Scientific Contributions: Co-authored influential tutorials and books on real-time data management and NoSQL systems. Contributed to reference works such as the Encyclopedia of Big Data Technologies . Editorial roles in journals like Datenbank-Spektrum and organizing roles in BTW workshops. Ritter has advised or collaborated with several researchers, though formal student listings are not available. His work often involves system design, benchmarking, and real-world deployment, suggesting involvement in grants and applied research projects. He has also contributed to the development of tools and frameworks for data integration, caching, and simulation environments.

• Information Systems
• Database Design
• Conceptual Modeling
• +7 more

Jacky Akoka is a Professor at the Conservatoire National des Arts et Métiers (CNAM), affiliated with the CEDRIC Laboratory in Paris, France. With a distinguished academic career spanning nearly three decades, Akoka has established himself as a leading researcher in information systems, database design, and conceptual modeling. Akoka's research interests primarily focus on Information Systems , Database Design , Conceptual Modeling , Data Quality , and more recently, Big Data applications in humanities (particularly prosopography). His work demonstrates a consistent evolution from foundational database research to interdisciplinary applications bridging computer science with historical and social sciences. Analysis of Akoka's recent publications (2019-2023) reveals a strong emphasis on Design Science Research methodology, historical database applications, and data quality assessment. His work increasingly intersects with digital humanities, particularly through prosopography research that applies database modeling techniques to historical social network analysis. The consistent publication output across top venues indicates ongoing research productivity and scholarly impact. Akoka has maintained a longstanding research partnership with Isabelle Comyn-Wattiau, with whom he has co-authored numerous publications across multiple decades. This collaboration represents one of the most enduring research partnerships visible in his publication record. His work with the CEDRIC Laboratory has contributed significantly to the fields of information systems quality, database reverse engineering, and more recently, the application of information systems methodologies to humanities research. The laboratory environment appears to support interdisciplinary work that bridges technical database research with practical applications in historical and social sciences.

• Databases
• Information Systems
• Data Quality
• +5 more

Isabelle Comyn-Wattiau is a full professor at ESSEC Business School and affiliated with the Conservatoire National des Arts et Métiers (CNAM) , contributing to the CEDRIC laboratory. With over two decades of academic activity, her work bridges computer science, information systems, and digital humanities through conceptual modeling, data quality, and reverse engineering. ESSEC Business School (since 2013) CNAM - CEDRIC Laboratory (since 2001) Her research interests focus on database design, quality assessment, and modeling techniques, particularly for historical data and business intelligence applications. Key themes include: Conceptual modeling of prosopographic databases Uncertainty detection in historical data Quality metrics for web applications Security requirements engineering with ontologies Mapping multidimensional schemas to graph models Evaluation frameworks for design science research Her article trends show consistent contributions to database evolution (2001-2023), with recent work emphasizing design science research (2019-2023) and historical data quality (2019-2021). Collaborative patterns reveal long-term partnerships with Jacques Akoka and Nathalie Prat across multiple domains.

Wensheng DouView profile

Researcher

• software analysis and testing
• distributed systems
• database systems
• +1 more

Wensheng Dou is a Researcher at the Institute of Software, Chinese Academy of Sciences . His work bridges software engineering, distributed systems, and database technologies, with a strong emphasis on improving system reliability through advanced testing methodologies. Research Focus: Dou's interests span: Software Testing & Analysis : Differential testing, fault injection, and bug detection in databases and distributed systems. Systems Reliability : Cloud systems, graph databases (Gremlin/RDF), and transaction processing. Emerging Platforms : IoT, mobile apps (WeChat), and LLM-assisted bug fixing. Publication Trends: His recent work (2022–2025) demonstrates a consistent focus on: Automated testing tools for databases (e.g., FaultFuzz ) and distributed systems. Bug characterization in real-world systems (cloud, IoT, mini-apps). Innovations in differential testing and coverage-guided fault injection.

Véronique BenzakenView profile

Professor

• Data-Centric Programming Languages
• Formal Verification of Data Management Systems
• XML/JSON Data Processing
• +3 more

Véronique Benzaken is a Full Professor at Université Paris-Saclay, affiliated with the Laboratoire de Méthodes Formelles (LRI) and INRIA Saclay's Toccata group. Her research focuses on Data-Centric Programming Languages , formal verification of data management systems, and type-safe XML/JSON processing. Key projects: ℂDuce XML-centric functional language, Datacert data certification initiative Collaboration with Oracle Labs on multi-lingual query interfaces using QIR Active in Coq formalization of SQL, Datalog, and data provenance Research interests include: Formal foundations for NoSQL/BigData languages Coq-based verification of database systems Type systems for data models Cloud computing data abstraction Her work bridges theory and practical implementation through collaborations with both academic and industrial partners.