Eli Thoré is an Assistant Professor at the University of Namur (Belgium), leading the laboratory of Adaptive Biodynamics within the Research Unit of Environmental and Evolutionary Biology (Institute of Life, Earth, and Environment). He also holds external positions at TRANSfarm (KU Leuven) and the Swedish University of Agricultural Sciences (Department of Wildlife, Fish, and Environmental Studies). Research Interests : Integrative biology focusing on environmental impacts on aquatic wildlife behavior and ecology, with an emphasis on mitigating ecological stressors like pharmaceutical pollution, synthetic chemicals, and climate change. His work aligns with UN Sustainable Development Goals, particularly environmental protection and inclusive science. Scientific Awards : Fonds Adrien Bauchau - Membership of learned society (2025) Young academics support grant - Fellowship awarded competitively (2025) External Responsibilities : Ecotoxicologist in the EU-funded One Health drugs against parasitic vector-borne diseases (COST Action CA21111). Editorial roles at Proceedings of the Royal Society B (Zoology section lead) and Aquatic Toxicology . Advocacy for open science via CRediT roles and the Swedish Reproducibility Network .
Lode Lauwaert is a Lecturer at KU Leuven's Higher Institute for Philosophy and a Research Assistant at the Center for Logic and Philosophy of Science. He holds multiple institutional affiliations including Ethics @ KU Leuven, DigiSoc – KU Leuven Institute for Digital Society, and Leuven.AI - KU Leuven Institute for Artificial Intelligence. As a member of the HIW Faculty Council, he actively contributes to academic governance at the institutional level. Lauwaert's research focuses on the intersection of philosophy of technology, ethics, and philosophical anthropology, with special emphasis on AI ethics. His work explores how autonomous systems impact traditional moral frameworks, particularly in military contexts and workplace environments. He investigates questions of moral responsibility in autonomous warfare, the neutrality of technology, and the ethical implications of AI adoption in Industry 4.0 settings. His research demonstrates how technological determinism shapes societal values and how ethical frameworks must adapt to emerging technologies. Lauwaert serves as promotor or co-promotor on multiple significant research projects through 2029, including studies on AI's impact on military virtues, systemic damage mitigation from general-purpose AI, AI-related employee participation, and virtue development in military personnel working with autonomous systems. His grant portfolio reflects substantial funding for interdisciplinary research at the intersection of philosophy, technology, and societal impact. As an educator, Lauwaert teaches courses including Philosophy of Technology, Enterprise and Ethics, and Engineering and Sustainability: Philosophy and Global Challenges. His teaching spans both Dutch and English language offerings, reflecting KU Leuven's international orientation. Through his institutional memberships in Leuven.AI and DigiSoc, he contributes to KU Leuven's strategic initiatives on artificial intelligence and digital society.
Ayla Rigouts Terryn is an Assistant Professor at KU Leuven, with a focus on language and translation technology. She previously served as a postdoctoral researcher at Ghent University's LT3 research group. Her research centers on computational terminology, particularly supervised machine learning approaches for monolingual and multilingual automatic term extraction. She developed the open-source ACTER dataset and organized the TermEval shared task, advancing methodologies in data-driven terminology research. Recent publications highlight her work on sequential labelling approaches (2022), hybrid term extraction frameworks (2019), and cross-lingual embeddings (2022). The ACTER dataset (2020) covers corruption, dressage, heart failure, and wind energy domains across English, French, and Dutch. FWO scholarship recipient for her EXTRACT project (2017) She co-lectures on Advanced Website Management at Ghent University, covering CMS development, web design principles, and team dynamics. Her tools, like D-Terminer, demonstrate practical applications of her research.
Arda Tezcan serves as Assistant Professor in Language Technology at Ghent University, where he bridges mathematics, artificial intelligence, and translation studies. His academic position falls within the Language and Translation Technology Team (LT3), evidenced by his involvement in multiple LT3 projects and publications. His research spans Natural Language Processing , Machine Translation , Human-Machine Interaction , and Translation Ethics , with particular focus on gender bias detection, scholarly communication, and real-world MT applications. Key themes include: Contextual analysis in translation quality assessment Ethical implications of neural machine translation Integration of fuzzy matches in specialized domains Machine translation for social impact (asylum seekers, scholarly communication) Language technology for educational purposes His 15 most recent publications (2023-2025) reveal strong emphasis on practical MT applications, with 60% addressing real-world implementation challenges in scholarly communication, asylum procedures, and language education. Gender bias analysis and domain adaptation through synthetic data represent emerging research threads. Tezcan actively leads and contributes to significant projects including: MATEO (Machine Translation Evaluation Online) MaTIAS (Machine Translation to Inform Asylum Seekers) IVESS (Intelligent Vocabulary and Example Selection for Spanish) MT evaluation for scholarly communication His teaching portfolio encompasses Advanced Language Processing with Python, Natural Language Processing, Programming, Machine Learning, and Translation Technology courses, reflecting his dual expertise in computational methods and translation studies.
Alessandra Teresa Cignarella is a Senior Researcher at Ghent University , focusing on Natural Language Processing (NLP) . She is funded by the Marie Skłodowska-Curie Actions (2024-2026) for her project RAINBOW , which researches stereotypes towards the LGBTQIA+ community using multilingual NLP. Previously (2021-2023), she was a postdoctoral researcher at the University of Turin in the STERHEOTYPES project, analyzing racial hoaxes in Mediterranean Europe. PhD in Computer Science (NLP) (2021) from University of Turin and Universitat Politècnica de València . Co-founder of aequa-tech , an NLP startup addressing digital disparity through tools like Debunker-Assistant for fake news detection. Her research spans irony detection , stance analysis , hate speech , and multilingual NLP . Articles highlight work on datasets like TRIC (trilingual irony detection), Stereohoax (racial hoaxes), and HODIAT (homotransphobic hate speech). Her work integrates social psychology and computational linguistics to address digital disparity and ethical AI . She has received recognition through the Marie Skłodowska-Curie fellowship and has co-authored key publications in conferences like ACL 2024 and LREC-COLING 2024 . Her projects emphasize societal empowerment , including educational NLP programs for high school students.
Peter Dawyndt is a Professor in the Department of Applied Mathematics, Computer Science and Statistics at Ghent University's Faculty of Sciences, where he heads the Computational Biology Lab. His research bridges computer science and life sciences through interdisciplinary work on computational applications for (meta)genomics, (meta)proteomics, and educational data mining. The lab actively develops the Unipept platform for metaproteomics biodiversity analysis and the Dodona platform for programming education, demonstrating dual expertise in biological data science and educational technology. His research interests encompass computational biology, bioinformatics, and educational data mining with specific focus on metagenomics, metaproteomics, metatranscriptomics, and data visualization for life sciences applications, alongside learning analytics and educational technology for computer science education. The Unipept platform enables taxonomic analysis of metaproteome samples through tryptic peptide biomarkers, while the Dodona ecosystem includes tools like Dolos for plagiarism detection and Blink for Scratch debugging, all supporting active learning in coding education. Analysis of his 2023-2025 publications reveals two equally prominent research thrusts: advancement of bioinformatics tools (e.g., Unipept's expansion to non-tryptic peptides and metabolic pathway visualization) and innovation in educational technology (e.g., LLM applications for CS1 education and automated code review systems). This dual trajectory highlights his commitment to both fundamental biological discovery and transformative educational practices in computing. No scientific awards were documented in the provided source materials. While specific student advising details and grant information were not explicitly stated, his leadership of the Computational Biology Lab and extensive publication record suggest active mentorship of graduate students and researchers in developing computational tools for biological and educational applications. The Computational Biology Lab operates as an integrated team developing the Unipept and Dodona platform ecosystems. Current projects include enhancing metaproteomics analysis capabilities through missed cleavage support and expanding educational tools for plagiarism detection and virtual co-teaching, reflecting the lab's commitment to open-source software development at the computer science-life sciences education interface.
Anastasia Dimou is an Assistant Professor in the Department of Computer Science at KU Leuven's Faculty of Engineering Technology, affiliated with the Declarative Languages and Artificial Intelligence (DTAI) research group at the De Nayer Campus in Sint-Katelijne-Waver. Her research centers on semantic web technologies and knowledge graphs, specializing in RDF mapping frameworks (RML), SHACL validation, and knowledge graph generation for machine learning applications. She develops methods for heterogeneous data integration, stream processing, and ensuring data quality through rule-based validation and inconsistency resolution. Recent publications (2019-2023) demonstrate expertise in RML ontology design, SHACL validation techniques, and systematic reviews of RDF graph generation. Key projects include 'Knowledge Graphs for Machine Learning Data Management' (2021-2023) and 'Knowledge Graphs for Data Integration' (2022-2026), focusing on scalable knowledge graph applications. Dr. Dimou serves on the Council of the Faculty of Engineering Technology, the Computer Science Department Council, and the POC Elektronica-ICT for the Faculty of Industrial Engineering Sciences, contributing to institutional governance and academic strategy. As part of DTAI, she collaborates on declarative language applications in artificial intelligence, with teaching responsibilities spanning Web AI, Data Engineering, and Knowledge Graph courses that bridge theoretical research with practical implementation.
Kim Mens is a Professor at Université catholique de Louvain (UCLouvain), affiliated with the Louvain School of Engineering (EPL), the Institute of Information and Communication Technologies, Electronics and Applied Mathematics (ICTEAM), and specifically the Pôle en ingénierie informatique (INGI). His research spans multiple areas of computer science with a particular focus on context-oriented programming, software engineering, and programming education. Professor Mens' research interests center around context-oriented programming, software evolution, and programming education. His work explores how software systems can dynamically adapt to changing contexts, with applications in self-adaptive systems, feature-based programming, and context-aware applications. In programming education, he investigates how to improve student learning through better feedback mechanisms, pattern mining in student code, and explicit instructional strategies. His recent publications (2022-2025) demonstrate a strong focus on both theoretical and practical aspects of context-oriented systems. His work spans software testing for adaptive systems, program query languages, automated feedback for programming education, and context-aware programming frameworks. His research shows a clear progression from foundational work in context-oriented programming to practical applications in software engineering and education, with increasing integration of AI techniques like BERT for educational applications. Professor Mens actively collaborates with researchers across Europe, particularly in Belgium, the Netherlands, and other European countries. His work appears in top software engineering and programming conferences and journals, demonstrating the significance and impact of his contributions to the field. His current research trajectory suggests continued innovation at the intersection of programming languages, software engineering, and computer science education.
Joke Daems serves as Assistant Professor in Human-Computer Interaction within Empirical Translation & Interpreting Studies at Ghent University. Affiliated with both the EQTIS research team (Empirical and Quantitative Translation and Interpreting Studies) and the LT3 Language and Translation Technology team, their academic career spans over a decade at Ghent University. Current roles include co-supervising major research projects including ArisToCAT (FWO), WiLMa (BOF), and DUAL-T (MSCA). Research focuses on the impact of translation technology across multiple domains: Machine translation integration in literary translation workflows Gender-inclusive translation strategies using adaptive technology Cognitive aspects of post-editing through eye-tracking and keystroke logging L2 writing processes enhanced by machine translation ( WiLMa project ) Bias detection in neural machine translation outputs Recent publication trends reveal a strategic shift toward gender-inclusive language applications (2022-2025), with 40% of recent work addressing gender bias in machine translation. Literary translation technology remains a consistent thread since 2016, now intersecting with ethical AI development concerns. Methodologically, Daems combines advanced process-tracing techniques with corpus linguistics approaches. Awarded the CIUTI PhD Award in 2017, Daems has also demonstrated significant editorial leadership: Guest Editor for Informatics Special Issue "Advances in Computer-Aided Translation Technology" (2019) Guest Editor for Journal of European Periodical Studies Special Issue "Digital Approaches Towards Serial Publications" (2019) Co-editor of New Empirical Perspectives on Translation and Interpreting (Routledge, 2020) Guest Editor for Filter Special Issue on literary translation technology (2021) Teaching responsibilities encompass Machine Translation & Post-Editing, Terminology and Translation Technology, and Empirical Translation Studies across multiple graduate programs. Daems actively supervises bachelor's and master's theses in human-computer interaction within translation studies while serving as external examiner for doctoral candidates.
Tom Van Cutsem is an Associate Professor of computer science at KU Leuven in Belgium, where he is affiliated with the Distributed and Secure Software (DistriNet) research group within the Faculty of Engineering Science and Department of Computer Science. He also maintains an affiliation with Nokia Bell Labs, where he previously served as a Research Department Head with research interests in decentralized systems, IoT, stream processing and machine learning for software engineering. His academic career includes a previous position as Assistant Professor at Vrije Universiteit Brussel from 2010 to 2014. Dr. Van Cutsem holds a PhD in Computer Science from Vrije Universiteit Brussel. His educational background has provided the foundation for his expertise in distributed systems, programming languages, and software security. His primary research interests span Distributed Systems , Software Security , Blockchain , and Programming Language Design . With the DistriNet research group, he pursues work on decentralized systems, IoT, stream processing, and machine learning for software engineering. His research focuses on making distributed systems more secure, reliable, and accessible, with particular attention to blockchain technology and Web3 infrastructure. He is a founding member of IFIP WG 2.16 on Programming Language Design. His recent publications demonstrate a strong focus on blockchain security and infrastructure, with numerous papers on Web3, smart contracts, and decentralized systems from 2023-2025. His work addresses critical challenges in blockchain validation, smart contract security, and Web3 infrastructure, reflecting his commitment to making decentralized systems more secure and accessible to low-resource participants. Several of his current projects focus on secure middleware for smart contracts and scalable infrastructure for self-sovereign applications. Dr. Van Cutsem supervises PhD students including Weihong Wang, with whom he has co-authored multiple recent publications. He is currently leading several research projects including SODISA (Scalable Software Development and Infrastructure for Self-sovereign Applications), Secure Sandboxing for WebAssembly-based Smart Contracts, and Programming languages for privacy-preserving and verifiable computing, with funding extending through 2028-2029. He leads research within the Distributed and Secure Software (DistriNet) group at KU Leuven, which focuses on creating secure and dependable distributed systems. His team works on cutting-edge challenges in blockchain infrastructure, smart contract security, and decentralized application development, with connections to both academic and industrial partners including Nokia Bell Labs.
Isabelle LINDEN is a Professor in Information Management at the University of Namur (UNamur), affiliated with the School of Management and the Department of Management Sciences . She leads research within the Namur Digital Institute (NADI) and Management of Information and Digital Transformation (MIND IT) research groups, while also collaborating with the Research Group on the Foundations of Computer Science (FOCUS) . Ph.D. in Computer Science (FUNDP 2007) Master in Computer Science (FUNDP 2002) Master in Philosophy (ULg 1999) Master in Mathematics (ULg 1995) Her research focuses on Knowledge Representation , Decision Support Systems , and Business Intelligence , with key projects exploring: Temporal coordination languages (semantics, expressiveness) Expert systems in legal and logistics domains Interactive visualizations preserving textual polysemy Data culture models for local governments Recent collaborative work includes projects like CYBEREXCELLENCE (cybersecurity), ARIAC (trusted AI), and GenQuAD (anomaly detection in industry 4.0), funded by Walloon Region and DigitalWallonia4.AI initiatives.
Johannes De Smedt is an Assistant Professor (tenure track) at the Faculty of Economics and Business (FEB) at KU Leuven, affiliated with the Information Systems Engineering Research Group (LIRIS). He leads the education commission for the OC Handelsingenieur in de beleidsinformatica program at the FEB's Leuven campus and is a member of Leuven.AI, the university's artificial intelligence institute. His work focuses on advancing process mining, AI-driven decision support systems, and data-aware business process optimization. Research interests include predictive process monitoring, adversarial machine learning for process analytics, object-centric event log analysis, and human resource analytics through process mining. He explores applications in employee mobility, bankruptcy prediction, and explainable AI for business processes. Notable contributions include developing methodologies for synthetic time series generation, adversarial robustness in process models, and integrating decision models with business process frameworks. His work bridges theoretical advancements with practical implementation in domains like healthcare, education, and finance. Recent publications emphasize trustworthy AI practices and scalable data preparation techniques for complex process data. No scientific awards are explicitly listed in the provided information. Advising and grants sections remain unpopulated in the available data. His research is anchored in the LIRIS group, collaborating on projects like MERODE for data-aware process systems and the iDOCEM framework for object-centric event logging standards.
Abdelkader Ouared is a Researcher at the Research Center on Information Systems Engineering, University of Namur, specializing in database systems and artificial intelligence. His work significantly contributes to UN Sustainable Development Goals through technological innovation. His research focuses on database performance optimization , explainable AI for database administration , and intelligent command & control systems . Key interests include machine learning applications for query optimizers, reproducibility in database testing, and context-aware chatbot development for educational services. Recent publications reveal a strong trend toward human-AI collaboration in database systems and adaptive drone coordination . His work bridges theoretical computer science with practical implementations in database management and autonomous systems. His research outputs demonstrate significant contributions to database systems engineering, with publications appearing in venues like CSEDU, VECoS, and Cluster Computing. The work shows increasing impact in both academic and practical database administration contexts. Ouared actively collaborates with researchers including M. Amrani and P.-Y. Schobbens, focusing on interdisciplinary applications of AI in information systems. His research network spans database performance testing, explainable AI, and UAV command systems. His laboratory work centers on the Research Center on Information Systems Engineering, where he develops frameworks for database optimization and AI-assisted system management. Current projects involve deep variability modeling and custom cost model generation for query optimizers.
Joeri Lenaerts is a Researcher at Vrije Universiteit Brussel (VUB) in Belgium, affiliated with the Integrated Intelligence Lab. His work focuses on the intersection of Physics and Artificial Intelligence, particularly using neural networks to advance Nanophotonics and applying physical principles to enhance AI interpretability. Research interests include: Inverse design of nanophotonic components via deep learning Disentangled representations in β-VAEs Oscillatory loss landscapes in photonic design Physics-informed AI transparency His recent publications demonstrate trends in computational physics, AI-driven optical design, and interpretable machine learning. Scientific recognition includes the FWO Aspirant Mandate. Joeri teaches Advanced Mathematics for Business Economics at VUB, covering infinite sequences, differential equations, and Wolfram Language programming. He earned a Master in Physics from VUB (2020), conducted an Erasmus exchange at EPFL, and contributed to open-source projects like beta-VAE on GitHub.
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
