جستجوی استاد راهنمای دانشگاهی

Yves Wautelet serves as an Associate Professor at the Faculty of Economics and Business at KU Leuven, where he conducts research in conceptual modeling, business process management, and digital transformation. His work addresses critical challenges at the intersection of information systems engineering and business strategy, with particular focus on sustainability-driven modeling approaches and IT governance frameworks. His primary research interests include: Conceptual modeling methodologies and frameworks Business process management and information systems design Digital transformation strategies and implementation IT governance and business-IT alignment Sustainability-driven modeling for circular economy Agile software development practices and methods Requirements engineering with user stories Wautelet's recent publication record demonstrates significant scholarly productivity with numerous 2024-2025 publications spanning conceptual modeling frameworks for sustainability (Circulise), tools for identifying ambiguity in user stories (AmbiTRUS), and approaches to align strategic and operational agility. His work bridges theoretical foundations with practical applications across diverse domains including healthcare, circular economy, software development, and organizational transformation. His research consistently applies model-driven approaches to solve complex real-world problems, often integrating sustainability considerations into information systems engineering. As a promotor and co-promotor, Wautelet currently supervises multiple doctoral research projects including: Automatic generation of conceptual models from textual descriptions (2024-2028) Sustainability-Driven Modeling Assistant for Twin Transition in Vietnam (2024-2028) Home Care Business Process Management using Distributed Ledger Technologies (2024-2028) Teaching Modeling Skills in BPMN formalism (2021-2025) His research is conducted through the Information Systems Engineering Research Group (LIRIS) at KU Leuven's Brussels campus, where he contributes to advancing model-driven approaches for addressing contemporary business and technological challenges.

• Conceptual Modeling
• Business Process Management
• Digital Transformation
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Orphée De Clercq is an Assistant Professor at Ghent University, specializing in language technology for educational applications. Her research focuses on leveraging Natural Language Processing (NLP) and Machine Learning (ML) to enhance computer-assisted language learning , readability prediction , and automated writing evaluation . She also explores sentiment analysis , emotion detection , and event coreference resolution in Dutch and multilingual contexts. Education : PhD in 2015 with groundbreaking work in readability prediction and fine-grained sentiment analysis for Dutch. Research Trends in her recent publications emphasize: Readability across domains and languages Emotion Detection using transformers and affect lexica Event Coreference in cross-document news Automated Writing Evaluation through NLP Implicit Sentiment Analysis in user-generated content Cross-Lingual Transfer with multilingual datasets She co-supervises four PhD students and contributes to interdisciplinary projects like Steunpunt Toetsen , SentEMO , and NewsDNA . Her teaching includes courses on digital communication and Computer-Assisted Language Learning .

• Natural Language Processing
• Machine Learning
• Readability Prediction
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Els Lefever is an Associate Professor at Ghent University, where she works with the LT3 (Language and Translation Technology) research team. Her position focuses on computational linguistics and natural language processing research, with strong ties to both theoretical and applied aspects of language technology. Dr. Lefever earned her PhD in Computer Science from Ghent University in 2012 with her dissertation titled "ParaSense: Parallel Corpora for Word Sense Disambiguation." Her academic journey began as a computational linguist at the R&D department of Lernout & Hauspie Speech Products before transitioning to academia. Els Lefever's research spans multiple areas within computational linguistics with particular expertise in multilingual natural language processing. Her work focuses on computational semantics, cross-lingual word sense disambiguation, and multilingual terminology extraction. Recent research directions include automatic detection of irony in online text, argumentation mining in social media, sentiment analysis of financial news, language modeling for low-resourced languages, and computational approaches to Byzantine Greek epigrams. Her research demonstrates a consistent pattern of bridging theoretical computational linguistics with practical applications across diverse language domains and historical periods. Professor Lefever actively supervises PhD research on several cutting-edge topics including terminology extraction from comparable corpora, event extraction and sentiment mining of financial news, language modeling for low-resourced languages, argumentation mining in social media, and the automatic detection of links between Byzantine Greek epigrams. Her supervision portfolio demonstrates her commitment to advancing multiple frontiers of computational linguistics simultaneously. As an educator, Professor Lefever teaches courses in Terminology and Translation Technology, Language Technology, Localisation, Digital Text Analysis, and Digital Humanities. Her teaching reflects her research interests, providing students with both theoretical foundations and practical skills in language technology applications. The LT3 research group, where Professor Lefever is a key member, maintains strong connections with both academic and industry partners. The group has participated in numerous international conferences and shared tasks including SemEval competitions across multiple years, demonstrating consistent contributions to benchmark datasets and evaluation methodologies in natural language processing.

• Natural Language Processing
• Computational Linguistics
• Machine Learning
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Moharram Challenger is a tenure-track Assistant Professor in the Department of Computer Science at the University of Antwerp's Faculty of Sciences. Previously, he served as an assistant professor at Ege University (2017-2018) and as a post-doctoral researcher at the University of Antwerp (2019-2020) working on Flanders Make projects PACo and DTDesign. His academic journey includes R&D leadership roles at UNIT IT Ltd. (2012-2016), post-doctoral research at Wageningen University (2016-2017), and tenure-track faculty positions at IAU-Shabestar University (2005-2009). His research spans Cyber-physical Systems , Multi-agent Systems , and Domain-specific Modeling Languages , with recent publications focusing on quantum machine learning, digital twinning, and IoT optimization. Key projects include ITEA ModelWriter, ITEA Assume, and Flanders Make initiatives. His work demonstrates strong integration of model-driven engineering with emerging technologies like quantum computing and reinforcement learning. Challenger actively contributes to the academic community as a member of IEEE and ACM . His publication record shows consistent output across top venues, with 2025 featuring significant work in quantum-enhanced learning and CPS security. Current research emphasizes practical applications in drone energy modeling, medical diagnostics, and industrial IoT systems. His advising activities focus on cyber-physical systems and agent-based modeling, supported by grants from TUBITAK and Flanders Innovation & Entrepreneurship. Key collaborations include European ITEA projects and partnerships with industrial entities through UNIT IT Ltd. Challenger maintains active development through GitHub repositories related to code refactoring, model-driven engineering, and legacy system modernization, reflecting his commitment to practical software engineering solutions.

• Cyber-physical Systems
• Multi-agent Systems
• Domain-specific Modeling Languages
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Tijl De Bie is a Senior Full Professor at the University of Ghent, specializing in machine learning, data science, and their applications in bioinformatics, computational social sciences, and HR analytics. He leads the AI and Data Analytics (AIDA) research group within IDLab-ELIS. PhD in Machine Learning (KU Leuven, 2005) Worked at U.C. Berkeley, U.C. Davis, University of Southampton, and University of Bristol His research focuses on foundational aspects of data science, including fairness in AI, network embeddings, and human-centric methodologies. Recent work explores temporal network simulation, bias mitigation, and large-scale career trajectory datasets. Notable awards include an FWO Odysseus Group I grant and three ERC grants (Consolidator, Proof of Concept, Advanced). Current projects involve ethical AI frameworks and dynamic network analysis. Scientific Awards : FWO Odysseus Group I, ERC Consolidator, ERC Proof of Concept, ERC Advanced Grant He collaborates extensively in interdisciplinary research, applying machine learning to social media analysis and financial domains. His team develops open-source tools like EvalNE and Fondue for network embedding evaluation.

• Foundations of Data Science
• Human-Centric Data Science
• Exploratory Data Analysis
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Prof. Jochen De Weerdt is an Associate Professor at the Department of Decision Sciences and Information Management, KU Leuven, affiliated with the Faculty of Economics and Business. He is part of the Information Systems Engineering Research Group (LIRIS) and a member of Leuven.AI. His research focuses on Business Process Management, Process Mining, IoT-integrated analytics, and data-driven decision-making. He teaches courses such as Business Information Systems and chairs the Postgraduate Studies in Big Data and Analytics. His professional activities include organizing international workshops (e.g., BPI'14 and BPI'13) and serving as a reviewer for top journals like Information Systems and Decision Support Systems . Academically, he holds a PhD (2012) and MSc/BSc degrees (2009/2007) in Business Economics from KU Leuven. His work bridges theory and practice, addressing challenges in process optimization, fraud detection, and cross-domain applications of machine learning. He has pioneered methods for IoT-enhanced predictive process monitoring and graph-based analytics in dynamic systems. Research interests span predictive process analytics, adversarial robustness in models, and geospatial data integration. Teaching emphasizes practical skills in business informatics and data science, with a focus on industry-relevant outcomes. He actively collaborates on projects funded by institutions like the Australian Research Council (ARC).

• Business Process Management
• Process Mining
• Applied Data Analytics
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Bart Thijs is an Assistant Professor at the Faculty of Economics and Business of KU Leuven , Belgium. He is affiliated with the Department of Management, Strategy and Innovation and serves as a research expert at ECOOM , the Research and Development Monitoring Research Centre. He is also a member of Leuven.AI , the KU Leuven Institute for Artificial Intelligence, and participates in various faculty councils and program committees. Research Focus His research lies at the intersection of quantitative science studies , social network analysis , and interdisciplinary research evaluation . He employs advanced bibliometric and AI-based techniques to study knowledge networks, citation patterns, and the impact of interdisciplinary collaboration. His work often involves the development of new indicators and methodologies for assessing scientific output and collaboration. Projects & Collaborations NIKAW (2023–2027): Tracing the Impact of Change on Citation Networks in Ancient Literary Texts using Social Network Analysis. NIKAW (2022–2026): Networks of Ideas and Knowledge in the Ancient World. AI & Ancient World Scholarship (2021–2023): Linking traditional scholarship with digital tools via AI. Interdisciplinary Research & Impact (2020–2025): Co-promoting interdisciplinary initiatives. Teaching He teaches courses such as Analysis of Large Scale Social Networks and Advanced Research Methods in Quantitative Science and Technology Studies , contributing to both methodological and domain-specific education in scientometrics and network science.

• Quantitative Science Studies
• Social Network Analysis
• Interdisciplinary Research
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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.

• Automatic Terminology Extraction
• Machine Learning
• Language and Translation Technology
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Amanuel KOSHIMA is a researcher at the University of Namur, Department of Computer Science. He holds a PhD in Computer Science (2016) from the University of Namur, Belgium, an MSc in Computer Science (2009) from Vrije Universiteit Amsterdam, Netherlands, and a BSc in Information Systems (2005) from Addis Ababa University, Ethiopia. PhD: Computer Science, University of Namur, Belgium (2016) MSc: Computer Science, Vrije Universiteit Amsterdam, Netherlands (2009) BSc: Information Systems, Addis Ababa University, Ethiopia (2005) His research focuses on Model-Driven Engineering , Collaborative Editing , and Conflict Detection in domain-specific modeling environments. He has contributed to frameworks like DiCoMEF and METADONE, emphasizing distributed collaborative editing, artifact modeling, and rule-based systems for merging models. His publications highlight advancements in domain-specific modeling languages , model reconciliation , and collaborative software development . He received the MODELSWARD 2014 Best Paper Award for his contributions.

• Model-Driven Engineering
• Collaborative Editing
• Conflict Detection
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Professor Alexandra Simonenko (Ghent University) is a leading scholar in historical and diachronic linguistics, specializing in the evolution of determiners, nominal syntax, and pragmatic-driven language change across French, Finno-Ugric, and Scandinavian languages. Her work integrates treebank analysis, computational modeling, and formal semantics to trace grammatical shifts over time. Research Interests: Diachronic Semantics: Tracking how determiners and possessives shift from strong to weak interpretations Treebank-Based Methodology: Leveraging annotated corpora for quantitative analysis of Medieval French syntax Pragmatic Reasoning: Modeling language change through game-theoretic and information-theoretic frameworks Determiner Typology: Cross-linguistic analysis of full vs. clitic vs. bound determiners DP Islands and Factive Constraints: Investigating syntactic-pragmatic interactions in question structures Key Article Trends: Her recent work (2022-2026) focuses on determiner semantics, French possessive evolution, and computational models of definiteness. Earlier studies (2015-2019) emphasize Medieval French null subjects, cliticization, and treebank-based syntactic analysis.

• Historical Linguistics
• Diachronic Semantics
• Syntax-Semantics Interface
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Antonio Paolillo is a Professor in the Department of Informatics and Applied Informatics at Vrije Universiteit Brussel. His research focuses on real-time systems, embedded software, robotics, and synchronization protocols. He leads projects like Brubotics (sustainable human-centered robotics) and FORCES (reliable robotic systems), emphasizing safety, privacy, and performance in human-robot collaboration. Key contributions include the mmPrivPose3D dataset for gesture recognition and sensor-based safety systems. He actively contributes to conferences like ECRTS 2025 and is involved in OS design for embedded platforms. His work bridges theoretical formal verification with practical implementations in multi-core and NUMA architectures. Education details and specific degrees were not explicitly mentioned in the provided text. Research interests span real-time scheduling, hardware-software co-design, and robust embedded systems. Recent articles emphasize privacy-compliant human-robot interaction and compiler transpilation for safety-critical applications. He collaborates internationally in robotics and real-time systems domains. Current projects (2024-2029) include foundational work on embedded software performance, reconfigurable robotics, and conference organization for ECRTS 2025. His work often involves interdisciplinary teams and industry partnerships.

• Real-Time Systems
• Embedded Software
• Robotics
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Abdelmounaim Debieche is a Researcher affiliated with the Faculty of Computer Science. He holds a Bachelor's degree in Mathematics and Computer Science from Houari Boumediene University of Science and Technology (Algeria), and dual Master 2 diplomas in Software Engineering from the same institution and the University of Paris-Est Marne-La-Vallée (France). Bachelor's Degree in Mathematics and Computer Science, Houari Boumediene University of Science and Technology, Algiers - Algeria Master 2 Diploma in Computer Science Specializing in Software Engineering, Houari Boumediene University of Science and Technology, Algiers - Algeria Master II Diploma in Computer Science and Engineering Software Course, University of Paris-Est Marne-La-Vallée, France His research focuses on Internet of Things (IoT) systems, aging population support, and model-driven engineering for healthcare solutions. He contributed to projects like SEMIA (semantically augmented medical imaging) and presented at workshops/conferences including MODELSWARD 2017 and ER 2016 Workshops . Debieche's work explores user-centric DSLs for IoT systems and engineering solutions for elderly well-being. His publications emphasize IoT system architecture, medical imaging applications, and aging-related technologies. He has participated in events such as Meetup IoT Be (2016) and presented research on IoT systems at conferences in Portugal and Japan. His h-index is 16 based on Scopus citations, with 15 citation indexes and 17 reader captures according to Plum Print metrics.

• Internet of Things
• Software Engineering
• Aging Population
• +۳ مورد دیگر

Veronique Hoste is a Full Professor of Computational Linguistics at Ghent University's Faculty of Arts and Philosophy , where she serves as Department Head of the Department of Translation, Interpreting and Communication and Director of the LT3 Language and Translation Technology Team . Her work bridges machine learning with natural language processing, focusing on semantics, discourse modeling, and practical applications in emotion detection, irony recognition, and customer service dialogue analysis. PhD in Computational Linguistics from University of Antwerp (2005) 2023-2024: Francqui Chair at Université Libre de Bruxelles 2024: Elected to Royal Flemish Academy of Belgium (KVAB) Research Interests: Specializes in machine learning approaches to coreference resolution, sentiment analysis, and multimodal emotion detection. Leads projects like FlandersAI (empathy in conversational agents), METRICS (emotion trajectories in service dialogues), and SENTiVENT (financial event extraction). Develops high-quality datasets (e.g., EmotioNL , ENCORE ) for broader NLP community use. Recent Publications span Dutch social media irony detection, Classical Chinese poetry sentiment analysis, and multimodal emotion datasets. Collaborates on interdisciplinary initiatives like NewsDNA (news recommendation) and SentEMO (commercial sentiment analysis). Scientific Awards Francqui Chair (2023-2024) KVAB Membership (2024) Outreach includes co-founding AlfaSent (LT3 spin-off for customer feedback analysis) and authoring the first Dutch-language NLP book Taaltechnologie Ontrafeld (2024). Coordinates AI education initiatives like the AI at School project.

• Computational Linguistics
• Natural Language Processing
• Machine Learning
• +۷ مورد دیگر

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.

• Human-Computer Interaction
• Machine Translation
• Empirical Translation Studies
• +۶ مورد دیگر

Vincent Englebert is a Professor at the University of Namur's Faculty of Computer Science, where he is affiliated with the Research Center on Information Systems Engineering (PReCISE) and the Namur Digital Institute (NADI). His office is located in the IT Building at Rue Grandgagnage, 21 in Namur, Belgium. He teaches courses including Organisational and Business Modelling, Software Architecture Engineering, and Software Engineering Laboratory for the 2023-2026 academic period. Bachelor and Master in Computer Science (University of Namur) Doctor of Science in Computer Science (2000), thesis: 'A smart Meta-CASE: towards an integrated solution' Englebert's research focuses on Domain-Specific Modeling Language (DSML) Engineering, Modeling & Meta-modeling, and Software Architecture Engineering, with additional interest in Computers and Aging applications. His work spans theoretical foundations of modeling languages to practical applications in business processes and aging populations. The fingerprint of his research shows strong emphasis on design (100%), engineering (78%), computer codes (70%), Reverse Engineering (63%), architecture (60%), tools (56%), modeling (55%), and transformations (50%). His recent publications (2020-2024) demonstrate continued productivity in model-driven engineering, with particular focus on software product lines, feature modeling, and applications for aging populations. These works show a clear trajectory from theoretical modeling foundations to practical implementations and societal applications. Best paper at International Conference Modelsward'2014 Englebert has supervised numerous research projects, including the current e-Anacarde: Digitalisation project (2024-2028) and previously led major initiatives like UsiXML and METADONE. He has been active in media and public engagement, particularly regarding computer science education in schools, with multiple expert commentaries in 2016. His external responsibilities have included significant leadership positions, notably as Dean of the Faculty of Computer Science (2015-2019) and Director of the PRECISE/IS research center (until 2011). He is active in research networks and collaborations, with recent external collaborations spanning multiple countries. His work with the NAM-IP Museum demonstrates ongoing engagement with cultural institutions, while his presentations on Alzheimer's disease and computer technology show commitment to applying informatics to societal challenges.

• Domain-Specific Modeling Language Engineering
• Modeling & Meta-modeling
• Software Architecture Engineering
• +۴ مورد دیگر