Media & Information Interaction
The Media & Information Interaction Group develops AI systems for media and information interaction grounded in language, human interpretation, and information practices.
Introduction
The Media & Information Interaction Group develops AI systems for media and information interaction informed by language, human interpretation, and information practices. Our research combines recommender systems, information retrieval, and natural language processing to build systems that better reflect how people experience, understand, and interact with information and media.
We study subjective and contextual aspects of information interaction, including how people perceive relevance, how narratives and conversations shape media experiences, and how media representations can better account for personalization, contextual interpretation, and real-world domain constraints. Our work also develops human-centered evaluation methodologies that integrate computational, behavioral, and qualitative perspectives.
We work across domains such as music, podcasts, audiobooks, news, and conversational content in close collaboration with industry and interdisciplinary partners.
Our group is regularly posting job openings ranging from internships to researcher positions. To check the opportunities currently available or to submit a speculative applications use the link below.
Current group members
Latest publications
Michel, Gaspard, Elena V. Epure, and Christophe Cerisara. "Computational Narrative Understanding for Expressive Text-to-Speech." In Findings of the Association for Computational Linguistics: ACL 2026. 2026.
Sguerra, Bruno, Elena V. Epure, Harin Lee, and Manuel Moussallam. "A Study of Biases in LLM-Generated Musical Taste Profiles for Recommendation." ACM Transactions on Recommender Systems (2026).
Berthe-Pardo, Abigail, Gaspard Michel, Elena V. Epure, and Christophe Cerisara. "S-VoCAL: A Dataset and Evaluation Framework for Inferring Speaking Voice Character Attributes in Literature." In Proceedings of the 15th Language Resources and Evaluation Conference. 2026.
Baranes, Marion, Romain Hennequin, and Elena V. Epure. "Beyond Musical Descriptors: Extracting Preference-Bearing Intent in Music Queries." In Proceedings of the 4th Workshop on NLP for Music and Audio (NLP4MusA 2026), pp. 20-26. 2026.