Isabelle Linden holds master’s degrees in Mathematics (University of Liège), Philosophy (University of Liège), and Computer Science (University of Namur). She earned her PhD in Computer Science with a thesis on the semantics of coordination languages.

Since 2009, she has been a Professor of Information Management at the Namur School of Management, where she teaches data analysis and artificial intelligence. Driven by the challenge of supporting decision-making within organizations, she has developed a research program aimed at integrating Artificial Intelligence techniques and data analysis to inform decision-making processes.

Her work initially focused on two main research axes:

1. Knowledge Modeling and Reasoning: She explores how knowledge is modeled, articulated in reasoning, and acquired—especially when it is only available in poorly structured forms. She has investigated these questions in diverse contexts, such as legal texts related to estate planning and inheritance calculations (SEPlanS and Proceplans research projects, Casubel software), as well as expert knowledge for exception handling in logistics chain processes (BEM project). Adopting an analytical perspective supported by interactive dashboard visualizations, she also examines how novel visualizations can support and generate text analysis while preserving meaning, polysemy, evocation, and intertextuality.

2. Data-to-Knowledge Transformation: She studies how data is transformed into knowledge, whether through Business Intelligence (BI) platforms or data-driven artificial intelligence techniques. Her research spans public data management (CIPS project), attrition prediction in telecommunications, and defect prediction in production chains.

More recently, her research has expanded to a third axis:

1. Ethical Issues and Generative AI: After working on projects involving both symbolic AI and connectionist AI, she now focuses on the ethical questions raised by AI techniques, particularly generative AI. She investigates their technical and philosophical implications, including how these technologies reshape our relationship with the world, the nature of the relationships we can have with AI, and the criteria for discerning the appropriate use of AI.

• Knowledge Modeling, Acquisition and Management
• Decision Support Systems, Business Information Systems
• Information Management, Intelligent Systems
• Coordination Languages and Models
• Formal Methods and Programming Methodologies
• Concurrent
• Programming and Distributed System

• Artificial Intelligence
• Ethics of AI

Ph.D. in Computer Science (FUNDP 2007)
Master in Computer Science (FUNDP 2002)
Master in Philosophy (ULg 1999)
Master in Mathematics (ULg 1995)