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
• +۵ مورد دیگر

Stijn Viaene is a Full Professor at KU Leuven and Partner at Vlerick Business School, specializing in digital transformation, IT management, and business process innovation. He holds a Doctorate in Information Systems Management from KU Leuven and serves as Programme Director of Take The Lead. His research focuses on leveraging technology (big data, AI, blockchain) for enterprise digitalization, with a strong emphasis on leadership, agility, and business-IT alignment. He is the author of Digital Transformation Know How: Connecting digital transformation, agility and leadership and teaches across MBA, Executive Development, and Digital Leadership programs. Recent work explores AI-driven leadership, blockchain platforms for sustainability, and intra-organizational labor platforms. He also serves as Jury President for the Data News Awards and Board Member at Herita vzw. Education: Doctor in Information Systems Management (KU Leuven). Research interests include digital innovation ecosystems, process management, and governance frameworks for digital value creation. His articles address topics such as ambidextrous ERP systems, paradox management in transformations, and open innovation in public administration. Advising & Grants: Involved in multiple industry-public sector collaborations. Notable projects include blockchain-based water trade platforms and frameworks for sustainable digital ecosystems. His work bridges academic research with practical business applications through case-based teaching and action design research methodologies. Labs/Teams: Active in Vlerick’s Digital Transformation and IT Management research groups, contributing to initiatives like the Digital Leadership programme and strategic consulting for global organizations.

• Digital Transformation
• Business Process Management
• IT Management
• +۳ مورد دیگر

Philippe Baecke is a Professor of Business Analytics and Artificial Intelligence at Vlerick Business School, where he also serves as Programme Director for the Master in Business Analytics & AI and two executive programmes. He holds adjunct roles as Lecturer at Trinity Business School, Ireland, and Professor at the University of Namur. He earned his Doctorate in Applied Economics from Ghent University, complemented by an Advanced Master and Master in Applied Economics, both from Ghent University. His research focuses on leveraging big data analytics across marketing, operations, and finance, with specialties in digital marketing, customer relationship management, and network analysis. Notable areas include ad targeting, spatial modeling, and the application of AI in call center optimization and emotion recognition. He advises companies like KBC, ING, and Telenet on data strategy, blending strategic and operational insights. His recent work explores digital transformation trends, cost-effective AI adoption for SMEs, and the integration of human judgment in forecasting systems. He has published extensively in peer-reviewed journals, addressing topics like telecom data monetization, churn detection, and consumer privacy in addressable TV advertising. Baecke’s expertise also extends to vehicle telematics in insurance risk selection and spatial econometrics in customer acquisition modeling. He has collaborated on projects involving Bluetooth tracking in retail environments and the analysis of urbanization effects on customer behavior.

• Big Data Analytics
• Digital Marketing
• Customer Relationship Management
• +۵ مورد دیگر

Dr. Vincent Ginis is a prominent academic at Vrije Universiteit Brussel (VUB), associated with the Applied Physics Department and the Data Analytics Lab. His roles include doctoral scholarship supervision and research leadership in interdisciplinary projects. He holds a strong background in applied physics, metamaterials, and AI-driven solutions for societal challenges. Current affiliations include: Principal Investigator in 19 funded projects (2010–2029), focusing on AI ethics, sustainable transitions, and historical data analysis Supervisor of 60+ student theses across master's and doctoral levels Recipient of 15+ prestigious awards including the Agathon De Potter Award and FWO/Barco Prize Research interests span: Applied Physics: Metamaterials, optics, and photonics AI Applications: Ethics, bias mitigation, and historical data digitization Social Sciences: Wealth inequality, intergenerational mobility, and policy impact analysis Recent work highlights include groundbreaking studies on: Large Language Models' performance in OCR tasks Bias patterns in AI citation practices Ethical frameworks for human-centered AI systems Notable collaborations span institutions in Europe and beyond, with 1295 citations across 120+ publications. His work is amplified through platforms like Strava data for urban planning and historical datasets from 19th-century archives.

• Applied Physics
• Artificial Intelligence
• Data Analytics
• +۴ مورد دیگر

Erik Mannens is a Professor at Ghent University and Research Valorisation Director at imec, specializing in Semantic Technologies and Artificial Intelligence since 2005. He leads the Data Science team at IDLab, managing over 50 researchers focused on advancing semantic data science and its applications. Education: PhD in Computer Science Engineering (2011), Master’s in Computer Science (1995), and Master’s in Electro-Mechanical Engineering (1992) The team explores the fusion of semantics and AI, aiming to: (1) analyze the Web’s societal impact, (2) study Web-enabled lifestyle changes, and (3) develop future Web innovations. Their work emphasizes Open Source , Open Access , and Open Knowledge principles. His research spans Semantic Intelligence , Big Data Analytics , and Linked Data applications, with notable publications on RDF mappings, IoT platforms, and distributed data querying. Key projects include MapVOWL, RMLEditor, and the MASSIF platform. Current affiliations include Ghent University’s IDLab , where he contributes to cutting-edge research in data science and semantic technologies.

• Semantic Intelligence
• Big Data Analytics
• Semantic Web
• +۴ مورد دیگر

Jesse Davis is a Professor at the Department of Computer Science , KU Leuven , actively contributing to the Machine Learning group and the Sports Analytics Lab . He is part of the Faculty of Engineering Science and the Leuven.AI Institute . Ph.D. in Computer Sciences from University of Wisconsin-Madison (2007) M.S. in Computer Sciences from University of Wisconsin-Madison (2005) B.A. in Computer Science from Williams College (2002) His research focuses on machine learning, data mining, big data analytics, and sports analytics, with significant work in: Transfer learning and Markov logic networks Anomaly detection and semi-supervised learning Medical NLP and biomechanical data analysis Soccer performance metrics and tactical analysis His recent work explores spatio-temporal data analysis in sports and explainable AI for medical applications, with collaborations spanning finance, healthcare, and semiconductor manufacturing. Notable scientific awards include: Best Paper Award (Applied Data Science Track) at KDD 2019 Best Technical Paper Award at Intelligence Analysis Workshop He advises numerous PhD and Master's students in areas like: Football analytics Tree ensemble compression Medical question-answering systems Biomechanical load prediction His lab develops tools such as: GSSL for Markov network structure learning TODTLER for transfer learning Alchemy system for Markov logic networks

• Machine Learning
• Data Mining
• Big Data
• +۴ مورد دیگر

Daniel Peralta Cámara is a Postdoctoral Researcher at Ghent University's Faculty of Engineering and Architecture, Department of Information Technology (EA05). His work spans Machine Learning , Bioinformatics , High Performance Computing , and Biometrics , with a focus on Single-Cell Data Analysis , Image Cytometry , and Missing Value Handling . Affiliation: Ghent University Academic Rank: Researcher Research Disciplines: Data Mining, Parallel Computing, Bioinformatics, High Performance Computing His research designs scalable machine learning frameworks for biological and engineering applications, including SCIP for morphological profiling and MSDeepAMR for antimicrobial resistance prediction. He explores advanced techniques like Polar Encoding for missing data and Fuzzy Rough Sets for classification uncertainty, contributing to one-class classification and novelty detection through Python libraries like Fuzzy-rough-learn 0.2 . Key Trends: Hybrid CNN-LSTM for sports analytics Time-series feature selection in healthcare UWB/IMU wearable integration for animal monitoring Dr. Peralta supervises PhD candidates like Maxim Lippeveld (2025) and Oliver Urs Lenz (2023). His collaborations span Ghent University researchers including Eli De Poorter , Chris Cornelis , and Yvan Saeys . Applications: Badminton strategy analysis Goat activity classification White blood cell identification

• Machine Learning
• Bioinformatics
• High Performance Computing
• +۵ مورد دیگر

Ana Fernandez Inguanzo is a Scientific Researcher at the Institute for European Studies and House of Sustainable Transitions, affiliated with Vrije Universiteit Brussel's Faculty of Economic and Social Sciences and Solvay Business School. Her work bridges technology ethics, data protection, and socio-political implications of AI. Institute for European Studies House of Sustainable Transitions Vrije Universiteit Brussel Research Interests: Ana specializes in ethical and legal dimensions of emerging technologies, focusing on disinformation combat through AI (TITAN project), surveillance ethics, and big data governance. Her interdisciplinary approach integrates social sciences with technical systems. Ethical Impact Assessments Surveillance Technologies Metaverse Policy European Political Text Analysis Sustainable Transitions Scientific Awards: Recognized with the SANTANDER-CIDOB 35 UNDER 35 Prize (2023) for her contributions to technology ethics research.

• Ethics
• Data Protection
• Big Data
• +۸ مورد دیگر

Thomas Neyens is an Associate Professor at the Department of Public Health and Primary Care, KU Leuven, affiliated with the Leuven Biostatistics and Statistical Bioinformatics Centre (L-BioStat). His work focuses on spatial statistics, hierarchical modelling, ecology, and public health, with notable contributions to epidemiological and ecological data analysis during the COVID-19 pandemic. He holds roles as promotor/co-promotor in interdisciplinary projects such as 'Trajectories of newly emerging evolving metacommunities' and 'A geostatistical framework to forecast malaria incidence'. His research integrates statistical methodologies with real-world applications in environmental health, disease mapping, and clinical data analysis. Recent publications highlight advancements in joint modelling approaches, analysis of opportunistic ecological datasets, and spatio-temporal epidemiology of respiratory pathologies. He teaches courses like Linear Models and Scientific Methodology at KU Leuven. Neyens collaborates with institutions like the One Health Institute and has contributed to projects evaluating vaccination effects, pandemic interventions, and environmental health impacts. His work emphasizes methodological developments for complex healthcare and ecological data.

• Spatial Statistics
• Hierarchical Modelling
• Ecology
• +۴ مورد دیگر

Mathieu LEGA is a Researcher at the Department of Decision Sciences and Information Systems, Faculty of Economics, Social Sciences and Business Administration, University of Namur. His work focuses on Business Intelligence adoption models, governance data culture, and mitigating information overload in public policy contexts. He holds a Master in Business Engineering (2020) and a Doctorate in Sciences (2024) from the same institution. His research bridges academic contributions with practical applications in local government and business decision-making systems. Key research interests include dashboard design impacts on user cognition, data-driven prioritization frameworks, and fostering data literacy in public sectors. Recent work explores cognitive load theory applied to Business Intelligence tools and conceptual models for local government data culture. He has contributed to journals like Transforming Government: People, Process and Policy and Data and Knowledge Engineering . Lega actively participates in academic conferences including the International Conference on Research Challenges in Information Science (RCIS) and the European Big Data Management Summer School. His interdisciplinary approach addresses both technical and organizational challenges in data utilization, particularly within Belgian public institutions.

• Business Intelligence
• Data Science
• Public Policy
• +۳ مورد دیگر

Pietro Zidda is a Professor at the University of Namur (UNamur), where he serves as Dean of the Faculty of Economics, Management, and Communication Sciences since August 2022. He is a Permanent Academic Member in the Department of Management Sciences and holds affiliations with multiple research entities including the Namur Digital Institute (NADI), the Center for Research on Consumption and Leisure (CeRCLe), and the Center on Consumers & Marketing Strategy (CCMS), a joint initiative of UCLouvain and UNamur. Education: Doctorate in Economics and Management Sciences (2000), Intercollegiate Center for Management Science (ICM, Brussels) & Université Catholique de Louvain (Mons) Doctoral program (part, ICM-Fellow, 1997-98), JL Kellogg Graduate School of Management, Northwestern University, United States Management Engineer (1993), Catholic University of Louvain (Mons) Certificate of Advanced Studies in Applied Computer Science (1993), Catholic University of Louvain (Mons) Professor Zidda's research focuses on the mathematical modeling of consumer choice behaviors, with particular emphasis on retail marketing and customer relationship management. His work explores how consumers make decisions in various contexts, from traditional store environments to digital platforms and emerging technologies. He has made significant contributions to understanding brand and store loyalty, the adoption of new technologies like mobile payment systems and interactive recommendation engines, and specialized areas such as wine marketing. His methodological expertise in sampling designs and choice modeling has been widely recognized in top marketing and operational research journals. His research has evolved to address contemporary challenges in marketing, with recent work examining virtual agents in healthcare e-commerce, interactive recommendation systems, and the sharing economy. This trajectory demonstrates his ability to adapt traditional marketing models to new technological contexts while maintaining rigorous methodological standards. Scientific Awards: Emerald outstanding paper in International Journal of Wine Business Research (2007) Best paper award - 3rd International Wine Business and Marketing Conference (Montpellier, 2006) ICM-Fellow (Intercollegiate Center for Management Science, Brussels) (1997-2000) Professor Zidda has held significant administrative positions including twice serving as Director of the Department of Management Sciences at UNamur (2008-2010 & 2015-2018), Director of CeRCLe, Director of CCMS, and member of the Executive Committee of the Louvain School of Management. He has secured numerous research grants, including projects on bike sharing systems (SHAREABIKE), loyalty programs (I.D.7 and I.D.4), cultural sector pricing (III.A.3), and wine sector channel choice (I.C.5). His collaborative work extends across institutions, with partnerships at UCLouvain and various international business schools. As a member of the Namur Digital Institute and the Center for Research on Consumption and Leisure, Professor Zidda contributes to interdisciplinary research teams exploring the intersection of technology, consumer behavior, and business strategy. His leadership in the SHAREABIKE project demonstrates his commitment to applying academic research to real-world community challenges through intelligent systems.

• Retail Marketing
• Consumer Choice Modeling
• Customer Relationship Management
• +۳ مورد دیگر

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
• +۴ مورد دیگر

David Wrathall is an Associate Professor at Oregon State University's College of Earth, Ocean and Atmospheric Sciences. He investigates climate change impacts on human migration, focusing on vulnerable coastal communities in developing countries. His research examines how climate hazards like sea-level rise and flooding interact with socio-political factors to influence migration patterns. Previously, he served as an associate academic officer at the United Nations University Institute for Environment and Human Security and was a National Science Foundation postdoctoral researcher at UC Santa Cruz. Education: PhD in Geography, King's College London Research Interests: Dr. Wrathall's interdisciplinary research spans climate adaptation, migration dynamics, and political ecology. He explores: (1) how vulnerable populations use migration as an adaptation strategy amid environmental stress; (2) intersections of resource politics, labor economics, and climate vulnerability; and (3) data-driven analysis of human mobility patterns using innovative methods like mobile network analytics. His fieldwork emphasizes Central America and South Asia. His publications predominantly focus on climate-induced migration (38%), political ecology of resource conflicts (25%), disaster resilience (20%), and illicit economy-environment linkages (17%). Recent work increasingly incorporates big data approaches to track climate adaptation patterns. Affiliations: Lead Author, IPCC Sixth Assessment Report (Working Group II: Poverty, Livelihoods) Fellow, Hugo Observatory on Environment, Migration and Politics Steering Committee Member, Population-Environment Research Network

• Climate Change Adaptation
• Human Migration
• Political Ecology
• +۳ مورد دیگر

Koenraad Brosens is a Professor and Vice Dean of Education at KU Leuven's Faculty of Arts, where he leads the Art History Research Group. He serves as Campus Vice Dean of Education and is a member of DigiSoc – KU Leuven Institute for Digital Society. His institutional roles include membership on the Board of the Institute for Living Languages, Faculteitsraad Letteren, Faculteitsbestuur Letteren, and Onderwijsraad. His research centers on Art History with specialization in Tapestry Studies, Digital Humanities, and Network Analysis. He investigates material culture, social dimensions of art production, and AI-mediated art experiences. Current projects explore corporeality in textile art, Chinoiserie tapestries, and the impact of aging on Color Field paintings, bridging historical analysis with computational methods. Analysis of his recent publications reveals a strong interdisciplinary trajectory merging art history with data science. His work consistently examines valuation systems in tapestry, social network structures in creative communities, and digital tools for art historical research, with increasing focus on AI's role in artistic interpretation and experience. Brosens actively supervises doctoral candidates including Ilse De Prekel, Evelien Muls, and Hiba Lamqaddam. His research is supported by multiple grants, notably Living Corpora (2025-2029) on human-AI collaboration in digital humanities and Lichamelijkheid, Materialiteit en Betekenis in Textiele Kunst (2025-2029) as principal investigator. He leads Project Cornelia, a pioneering digital humanities initiative mapping social networks of early modern Flemish tapestry producers, and develops visualization tools like KUbism for data exploration in art historical contexts. His work integrates computational approaches with traditional art historical methodologies to analyze creative ecosystems.

• Art History
• Tapestry Studies
• Digital Humanities
• +۵ مورد دیگر

Dirk Van den Poel is a Professor of Data Analytics/Big Data at Ghent University, Belgium, specializing in statistical computing, social media analytics, and predictive modeling. He has co-founded pioneering academic programs including the first predictive analytics master’s program globally, the Master of Science in Statistical Data Analysis, and the Master of Science in Business Engineering/Data Analytics. Teaches courses: Statistical Computing, Big Data, Social Media Analytics Research focus: Analytical CRM, ensemble classification methods, big data 110+ ISI-indexed publications in journals like IEEE Transactions on Power Systems and Decision Support Systems His recent work explores topics such as rumor detection in social media, predictive maintenance using sensor data, and crisis response through service adaptation. He leverages machine learning and deep learning for applications in agriculture, healthcare, and energy sectors. Current projects involve topic modeling (BERTopic), credit scoring with interpretable models, and spatiotemporal crime prediction using mobile phone data. Dirk’s methodology integrates stream processing frameworks , reinforcement learning , and ensemble techniques .

• Data Analytics
• Streaming Processing Frameworks & Analytics
• Internet of Things (IoT) & Industry 4.0
• +۲ مورد دیگر