Dr Fabio Pierazzi is an Associate Professor in Information Security at the Department of Computer Science, University College London. His research focuses on enhancing systems security through AI, particularly in environments where attackers rapidly adapt to defenses. He investigates adversarial attacks, concept drift mitigation, and explainability of ML-based security systems. Research emphasizes adversarial machine learning in security contexts Works on practical applications in malware analysis and network intrusion detection Explores concept drift robustness and problem-space constraints Collaborates with industry to improve real-world security solutions His publications span top-tier venues like IEEE Security & Privacy, ACM CCS, and USENIX Security. Key themes include adversarial robustness, security evaluation methodologies, and AI's limitations in practice. He supervises research degrees and provides consultancy for security projects.
Andrea Arcuri is a Professor at the School of Economics, Innovation and Technology within Kristiania University of Applied Sciences . His research focuses on Software Testing , Software Engineering , and Cloud Computing , with a particular emphasis on automated testing techniques for web APIs. Specialized in RESTful, GraphQL, and RPC API fuzzing Developer of the open-source EvoMaster testing tool Pioneer in integrating evolutionary algorithms and symbolic execution for test generation Active in bridging academic research with industrial software testing practices His recent publications show a strong focus on Search-Based Software Testing (SBST) , Automated Test Generation , and Industrial Adoption of Testing Technologies . He has contributed extensively to improving testability through mock generation and database handling in API testing. While no formal scientific awards are listed in the public records analyzed, his work has been consistently published in top-tier software engineering venues since 2013. The articles demonstrate increasing sophistication in fuzzing techniques, with recent extensions to handle complex dependencies like MongoDB and SQL databases.
Olaf Hartig is a Senior Associate Professor at Linköping University's Department of Computer and Information Science (IDA), affiliated with the Database and Information Techniques (ADIT) division. He is also an Amazon Scholar collaborating with the Neptune graph database team. His research focuses on data management, semantic web technologies, graph databases, and distributed data systems. Hartig holds a PhD from Humboldt-Universität zu Berlin and is a Docent at Linköping University. He has received numerous awards, including the SWSA Distinguished Dissertation Award and eight best paper awards, and was selected as a Wallenberg Academy Fellow in 2024. Education: PhD in Computer Science (Humboldt-Universität zu Berlin), Docent (Linköping University). Research interests span query processing for Linked Data, federated systems, RDF and GraphQL semantics, and knowledge graph construction. He leads research groups in Database and Web Information Systems and Semantic Web Technologies at IDA. Key achievements include pioneering traversal-based query execution, developing Triple Pattern Fragments, and contributions to standards like RDF* and SPARQL*. His work has been recognized through grants, patents (e.g., on graph acceleration techniques), and leadership roles in conferences like ISWC and ESWC. Teaching: Course leader for database technology courses (TDDD12, TDDD37) and advanced topics like big data analytics and bioinformatics databases. Active in curriculum design and interdisciplinary education. Labs/Teams: Database and Web Information Systems Group, Semantic Web Research Group, Sports Analytics Group (IDA) Grants: Wallenberg Academy Fellowship, Swedish Research Council funding
Riku Ala-Laurinaho is a Researcher at Aalto University's Department of Energy and Mechanical Engineering, with a focus on Digital Twin technologies and Industrial Automation. He holds a Master's (2019) and Bachelor's (2018) in Engineering and Technology from Aalto University. His research interests span Digital Twins in industrial contexts, Cyber-Physical Systems, IoT applications, and data-centric systems. He explores semantic-enhanced industrial metaverse frameworks and collaborative design paradigms. Recent work emphasizes context-aware systems, torsional vibration analysis tools, and Human-Centric Manufacturing processes. His publications (16+), including high-impact articles in Journal of Manufacturing Systems and SoftwareX , reflect a focus on industrial innovation. METEX award (2020) Contributions to 5+ open-source datasets (e.g., OpenTorsion, A!ex autonomous car dataset) His advising includes 1 supervised thesis, with grant details pending.
Patrick Lambrix is a Professor and Head of the Division for Database and Information Techniques at Linköping University's Department of Computer and Information Science (IDA). He holds a MSc in Mathematics and Computer Science from KU Leuven and a PhD from Linköping University. His expertise spans semantic web technologies, ontology engineering, and sports analytics. He leads the Database and Web Information Systems group and co-founded the Sports Analytics research group at IDA. Research interests include knowledge engineering applications in materials science and life sciences, ontology alignment, and performance metrics in sports. He coordinates the Master in Computer Science program and serves as Director of Studies. Notable contributions include award-winning systems in ontology debugging and completion, and organizing the Linköping Hockey Analytics Conference (LINHAC). Education: MSc (Mathematics & Computer Science, KU Leuven, 1988/1990), PhD (Linköping University, 1996) Leadership Roles: Head of ADIT Division, Director of Studies, WASP program participant Research Groups: Database & Web Info Systems, Semantic Web, Sports Analytics Publications focus on ontology engineering advancements and sports analytics innovations, with recent work on hockey performance metrics and ontology alignment methodologies. His teams collaborate with industry and sports organizations to apply semantic technologies in real-world scenarios.
Andrea Arcuri is a Professor at the Department of Computer Science within the Faculty of Technology, Art and Design at Oslo Metropolitan University. His research focuses on software engineering, particularly in automated testing, search-based techniques, and API security. Current research areas include cloud computing, cybersecurity, and software engineering. Key subfields: REST API testing, GraphQL fuzzing, evolutionary computation, and search-based test generation. Recent work emphasizes industrial applications of automated testing tools and frameworks like EvoMaster. His publications analyze trends in LLM integration with software testing, performance evaluation of industrial API testing, and tool development for search-based fuzzing. While no specific awards are listed, his contributions to software engineering are well-documented through 12 recent publications. Andrea collaborates extensively on empirical studies and tool development for API testing.
Ştefania-Gabriela Dumbravă is an Associate Professor in Computer Science at the École Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE), part of Institut Polytechnique de Paris. She leads the ACMES team at Samovar Laboratory (Télécom SudParis) and participates in international working groups including the Property Graph Schema Working Group and European Research Network on Formal Proofs. Education: PhD in Computer Science, Université Paris-Sud (2016) MSc in Computer Science, Jacobs University Bremen (2012) BSc in Mathematics, Jacobs University Bremen (2010) Research Focus: Her work centers on formal methods for designing and verifying graph database algorithms, with emphasis on: certified database engines, property graph schemas, threshold queries, progressive querying techniques, and knowledge graph evolution. She integrates theorem proving (Coq/Isabelle) with practical database applications. Publication Trends: Her recent works demonstrate strong focus on graph database foundations (schemas, query processing) and practical verification techniques. Publications frequently appear in top-tier venues (VLDB, SIGMOD, ICDE) and emphasize both theoretical rigor and real-world applications in areas like bioinformatics, transportation, and networking. Awards & Honors: EASST Best Software Science Paper (ICGT 2025) ICDE/SIGMOD Distinguished Reviewer Awards (2025) SIGMOD Best Paper & Research Highlight (2023) VLDB Best Paper Runner-Up (2022) Students & Grants: Supervises Master's interns on graph database applications. Leads the ANR JCJC VERDI project (2025-2029) on verified distributed graph systems. Actively recruits PhD candidates for this initiative. Labs & Service: ACMES team at Samovar Lab. Serves on editorial boards (TODS, TGDK) and program committees (VLDB, SIGMOD, ICDE). Coordinates VLDB 2026 Demonstrations Track and co-organizes multiple workshops (GRADES-NDA, TGD).
Joel Mattila is a Doctoral Researcher at Aalto University's Department of Energy and Mechanical Engineering . He contributes to cutting-edge research in digital twins and smart manufacturing systems. Research focus: Digital Twin Technology, Industrial Automation, Mechatronics Affiliation: Mechatronics research group Research Trends : His publications (2020–2022) highlight expertise in digital twin integration , industrial IoT , and API optimization using ROS, Gazebo, and Twinbase. Key themes include smart factories, extended reality applications, and computer vision for public infrastructure monitoring.
Tim Holzheim is a researcher at the Department of Computer Science, Faculty of Mathematics, Computer Science and Natural Sciences, RWTH Aachen University, affiliated with Lehrstuhl Informatik 5 (Database and Information Systems Group). He is actively involved in teaching and research, particularly in the areas of Knowledge Graphs, Semantic Web, and data integration technologies. Institution: RWTH Aachen University School: Faculty of Mathematics, Computer Science and Natural Sciences Department: Department of Computer Science Research Group: Lehrstuhl Informatik 5 (DBIS) Email: holzheim@dbis.rwth-aachen.de His research focuses on Knowledge Graphs , Semantic Web technologies , Wikidata , RDF , and GraphQL for semantic data access . He explores methods for knowledge extraction, data integration, and enabling efficient querying and hosting of large-scale semantic datasets. His work bridges theoretical semantic modeling with practical implementation in data systems. The recent publications highlight a consistent research trajectory in semantic data engineering, particularly in making knowledge graphs more accessible, interoperable, and usable through tools for bootstrapping APIs, analyzing property structures, and semantifying academic data. His contributions appear in workshops co-located with top-tier conferences such as ISWC and ESWC. There are no listed scientific awards or honors in the provided information. Tim Holzheim is involved in academic advising and teaching, offering courses such as Datenbanken und Informationssysteme and Knowledge Graph Lab . While no formal students are listed, his supervision likely includes thesis projects and lab participants. He is also engaged in research projects such as NFDI4DS, contributing to national data infrastructure initiatives. He is a member of the Database and Information Systems (DBIS) research group led by Prof. Dr. S. Decker, which focuses on scalable and semantic data management solutions. The group is active in developing tools and methodologies for knowledge graphs, data spaces, and semantic integration.
Federico Olmedo is an Assistant Professor at the Computer Science Department of the University of Chile, where he teaches courses like Program Analysis and Verification ( CC4101 ) and Discrete Mathematics for Computer Science ( CC3101 ). His research focuses on the semantics and verification of probabilistic programs , with applications in language-based security , differential privacy , and formal verification of cryptographic systems . Previously, he was a postdoctoral researcher at RWTH Aachen University and earned his PhD from the Technical University of Madrid in 2014. Research Interests : Program Verification Probabilistic Programming Language-Based Security Theorem Provers Quantum Computing Cryptographic Proofs Publications span formal methods for probabilistic programs, including weakest precondition calculi , runtime analysis of quantum programs , and machine-checked proofs for cryptographic protocols . Notable works include the Best Theory Paper Award at ECOOP 2016 and foundational research on conditioning in probabilistic programming . He co-developed the CertiCrypt and CertiPriv frameworks for verifying cryptographic proofs and differential privacy in Coq. Scientific Awards : ECOOP 2016 Best Theory Paper Award
Louis Mandel is a Researcher at Inria, specializing in reactive programming languages and probabilistic systems. He co-developed ReactiveML and Q*cert (a verified query compiler), with applications in chatbots and cloud log analysis. His work bridges formal methods and practical tools for embedded systems.
Dr. Jinan Fiaidhi is a Professor of Computer Science at Lakehead University, Canada since 2001. She served as Graduate Coordinator for the MSc and PhD programs in Computer Science and Biotechnology. She holds adjunct positions at the University of Western Ontario. Her academic journey includes degrees from Essex University (PgD, 1983) and Brunel University (PhD, 1986). She has held academic roles at institutions like Sultan Qaboos University and Philadelphia University prior to Lakehead. Her research focuses on Thick Data Analytics , Deep Learning , and Collaborative Learning , with applications in healthcare, medical imaging, and AI-driven diagnostics. She is a Professional Engineer (PEng) in Ontario and a Senior Member of IEEE. She chairs the IEEE Special Interest Group on Big and Thick Data for eHealth and founded the International Journal of Extreme Automation and Connectivity in Healthcare (IJEACH) as its Emeritus Editor-in-Chief. Her research is funded by NSERC and MITACS grants. Key projects include developing frameworks like QL4POMR for problem-oriented medical records and applying thick data analytics to Crohn’s disease, ulcerative colitis, and cataract severity analysis. Education: PhD in Computer Science, Brunel University (1986) PgD in Computer Science, Essex University (1983) Awards: None explicitly listed, but holds professional designations: PEng, IEEE Senior Member, ISP (CIPS), and MBCS (Chartered Computing). Grants: NSERC, MITACS (specific projects unspecified). Labs/Teams: Leads IEEE eHealth initiatives and collaborates on projects involving thick data analytics in healthcare interoperability and extreme automation.
István Koren is a PostDoc Research Associate and Scientific Assistant at the Chair of Process and Data Science, RWTH Aachen University, where he contributes to interdisciplinary research at the intersection of computer science and production engineering. He is also the deputy coordinator of the infrastructure area within the Cluster of Excellence Internet of Production , leading computer science initiatives involving around 50 researchers. His educational background includes a PhD from RWTH Aachen University (2013–2019) in the Advanced Community Information Systems group under Priv.-Doz. Dr. Ralf Klamma, with a thesis titled DevOpsUse: Community-Driven Continuous Innovation of Web Information Infrastructures . He holds a Master’s and Bachelor’s degree in Computer Science and Media from Technische Universität Dresden, with a focus on mobile software engineering and computer networks. Dr. Koren's research centers on societal software engineering and empowering professional communities of practice through accessible, user-driven software development. He investigates how evolving web technologies—such as WebRTC, WebAssembly, and GraphQL—can be stabilized through sustainable methodologies to support long-term information infrastructure development. His work emphasizes the role of end users in shaping systems that affect their work and well-being. Although no recent publications or awards are listed in the provided text, his research direction aligns strongly with community-driven innovation, web infrastructure, and digital collaboration in complex industrial environments. He has international research experience from internships in Japan (Shizuoka University), Brazil (PUC-Rio), and industry work in India (Amadeus Labs). He actively engages in interdisciplinary collaboration and welcomes discussions on emerging web technologies and their societal impact. His work supports the integration of computer science into advanced manufacturing within Industry 4.0 contexts.
Huanyu Li is an Assistant Professor at the Department of Computer and Information Science (IDA) of Linköping University, Sweden, within the Human-Centered Systems (HCS) division. His research focuses on Semantic Web and Ontologies, particularly ontology engineering, ontology-driven data integration, and applications in materials design and circular economy domains. Education : PhD in Computer Science, Linköping University (2022) MEng in Software Engineering, Harbin Institute of Technology (2016) BEng in Software Engineering, Harbin Institute of Technology (2014) Research Interests : Ontology engineering and alignment methodologies Domain-specific ontology development (materials science, semiconductor technologies) Interoperability frameworks for heterogeneous data sources Circular economy applications through ontology networks Service Roles : Co-chair of VOILA!, OM, and SeMatS workshops Program committee member for ESWC, ISWC, and other conferences Management committee member of EU COST Action EuMINe Reviewer for journals like Nature Scientific Data and Advanced Engineering Materials Awards : Recipient of the Lawson Stipendium (2022) for contributions to ontology matching and materials science communities Collaborations : Swedish e-Science Research Centre (SeRC) - DCMD group OPTIMADE discussion group on ontologies
Nepomuk Wolf is a researcher at the Chair of Computing in Civil and Building Engineering at the Technical University of Munich. His work focuses on integrating heterogeneous data systems using GraphQL for Building Information Modeling (BIM) and digital twinning applications. Research Interests: Artificial Intelligence, Digital Twinning, Construction Simulation, and Pedestrian Dynamics. Email: nepomuk.wolf@tum.de Wolf has published on topics such as IFC-to-GraphQL schema mapping and web-based sensor data integration for infrastructure. His recent work emphasizes API development for civil engineering applications and data interoperability.
