معرفی
Jérôme Euzenat is a senior research scientist at INRIA (Montbonnot, France) and holds a lecturer position at the University of Grenoble Alpes. He leads the mOeX project team focused on cultural evolution techniques applied to knowledge systems. With a PhD and habilitation in computer science, his expertise spans knowledge representation, semantic web technologies, and AI ethics.
His research interests include agent-based models, multi-agent social simulation, knowledge transmission dynamics, and computational approaches to cultural evolution. He investigates how variation and generalization in knowledge systems can lead to robustness and improvement without strong selection pressures.
Recent work explores reproducibility in machine learning, emphasizing replication and reevaluation processes. His presentations address topics like cultural knowledge evolution through example generation and agent interaction-driven ontology adaptation.
He is affiliated with INRIA's Grenoble center and collaborates with academic institutions in France. His current projects aim to model cultural evolution mechanisms in computational systems, blending AI with social science methodologies.
