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Maxime Gobert is a researcher at the University of Namur's Faculty of Computer Science, specializing in database systems and software engineering. Having completed his PhD in March 2023 titled 'Design, Manipulation and Evolution of Hybrid Polystores,' Gobert has established himself as an expert in hybrid database systems, particularly focusing on the HyDRa framework for modeling and evolving polystores. His research interests span database systems, hybrid polystores, database schema evolution, software engineering, data-intensive systems, and static program analysis. Gobert's work bridges theoretical database concepts with practical applications, particularly in NoSQL databases like MongoDB and complex hybrid data storage environments. His publication record demonstrates a clear trajectory from his 2013 Master's thesis on database reverse engineering through to his recent work on database testing best practices and sign language processing applications. His research shows strong collaboration with colleagues at the University of Namur, particularly with Professor Cleve A., and extends to international collaborations as evidenced by his 2016 guest researcher position at the University of Geneva. Best New Idea and Emerging Results (NIER) Paper Award at the 20th IEEE Working Conference on Source Code Analysis and Manipulation (SCAM 2020) Jean Fichefet 2013 award Gobert has contributed significantly to the development of the HyDRa framework for hybrid polystore management and has extended his research into sign language processing through collaborative projects creating bilingual sign language dictionaries and parallel corpora. His work demonstrates both technical depth in database systems and a commitment to applying this expertise to accessibility-focused applications.

• Database Systems
• Hybrid Polystores
• Database Schema Evolution
• +4 more

Dimitri Van Landuyt serves as an Associate Professor in the Department of Computer Science at KU Leuven , affiliated with the Information Systems Engineering Research Group (LIRIS) . He leads and co-promotes multiple high-impact research projects focused on security and privacy engineering, including initiatives on model-driven security risk analysis , privacy by design , and IoT security . His work spans GDPR compliance, synthetic data management, and threat modeling innovations. Academic Leadership : Member of the Council of FEB and Campus Council Leuven/Kortrijk Research Pillars : Privacy threat modeling, security automation, IoT systems, GDPR technical implementation His publications demonstrate expertise in privacy-enhancing technologies, with recent work analyzing LLM applications in threat modeling, developing tree-based privacy analysis frameworks, and creating adaptive trust management architectures. He explores serious games for security training, synthetic data quantification standards, and runtime threat assessment mechanisms. Dimitri contributes to educational programs through courses in ICT Service Management , Security & Privacy by Design , and Research Methodologies . He supervises student research while collaborating with industry and academia on data protection challenges.

• Information Systems Engineering
• Privacy Threat Modeling
• IoT Security
• +4 more

Guy De Tré is an Associate Professor at the Department of Telecommunications and Information Processing within Ghent University's Faculty of Engineering and Architecture. He leads the Database, Document and Content Management (DDCM) research group and focuses on computational intelligence in information systems, with expertise in bi-polarity handling, uncertainty modeling, and multi-valued logic systems. Primary Affiliation: Ghent University Research Focus: Data quality, fuzzy querying, spatio-temporal modeling Key Contributions: Foundational work in possibilistic databases and explainable AI His research combines theoretical and applied approaches to information management systems. Theoretical work includes: Bipolarity and uncertainty handling in databases Multi-valued logic frameworks Interval B-tree indexing for possibilistic data Applied research spans: NoSQL database optimization Decision support systems Contextualized machine learning 3D/4D modeling for geological resources Recent publications show increasing focus on explainable AI, with multiple works on contextualized support vector machine classification and orthographic similarity measures for graph-based data representations. His work bridges database theory with practical applications in data quality assessment, medical informatics, and cultural heritage projects like the Byzantine Book Epigrams database. Research Group: Leads the DDCM group at Ghent University, specializing in: Database management innovation Content modeling techniques Fuzzy logic implementations Temporal data indexing Intelligent information systems

• Computational Intelligence
• Data Quality
• Decision Support Systems
• +7 more

Loup Meurice is a Computer Science researcher at the University of Namur specializing in database systems and human-computer interaction technologies. His work bridges theoretical computer science with practical applications in data management and accessibility. His academic foundation includes: Bachelor in Computer Science (2011, University of Namur) Master in Computer Science (2013, University of Namur) PhD in Computer Science (2017, University of Namur) Meurice's research focuses on evolutionary database systems and accessibility solutions. His HyDRa framework revolutionizes hybrid polystore management through dynamic schema evolution techniques, while his recent work applies transformer models to sign language recognition. These dual research streams demonstrate exceptional versatility across low-level database engineering and high-impact assistive technologies. His publication trends reveal a strategic shift from core database engineering (2022 schema evolution frameworks) toward socially impactful applications (2023 sign language translation systems), maintaining technical rigor while expanding societal relevance. Award recognition: Best Paper Award at QRS 2016 for reliability/security innovations As academic supervisor, Meurice co-promotes doctoral research on French language acquisition tools for deaf students, demonstrating commitment to educational technology. His collaborative network spans 10+ international researchers across database theory and AI accessibility domains. Current projects involve the HyDRa framework development and context-aware sign language translation systems, operating within the University of Namur's computer science research ecosystem through multidisciplinary teams combining database specialists and human-computer interaction experts.

• Database Systems
• Software Engineering
• Schema Evolution
• +5 more

Boris Cherry is a Research Fellow at the Faculty of Computer Science, University of Liège, specializing in software engineering with focus on static program analysis and database systems. His educational background includes: PhD in Sciences (2024) with thesis on "Empirical Investigation and Static Detection of Code Smells in Applications using Document-Oriented Datastores" Master in Computer Science (2020) with thesis on "JCrashPack2.0: Search-based crash reproduction hardness analysis" Cherry's research centers on static analysis techniques for database applications, particularly MongoDB. He investigates code smells, crash reproduction mechanisms, and software quality metrics through empirical studies and tool development. His work bridges theoretical program analysis with practical database application challenges, emphasizing empirical validation and reproducibility in software engineering research. Publication trends (2020-2024) reveal consistent specialization in MongoDB-related static analysis, evolving from crash reproduction studies to comprehensive code smell detection frameworks. His research combines database theory, software quality metrics, and empirical validation methods, with strong emphasis on tool development for practical industry application. Cherry actively contributes to academic community building through event organization, including co-organizing the 2024 PhD Student Day for the Faculty of Computer Science. His collaborative work with the Software Evolution and Analysis Group demonstrates strong institutional integration and interdisciplinary research approaches.

• Static Program Analysis
• Software Engineering
• Database Systems
• +2 more