Emmanuel Dupoux

Emmanuel Dupoux is a Professor at the École des Hautes Études en Sciences Sociales (EHESS), affiliated with the Laboratory of Cognitive Sciences and Psycholinguistics (LSCP) and the Département d'Études Cognitives (DEC) at École normale supérieure (ENS), Paris. He leads the Cognitive Machine Learning team, focusing on interdisciplinary research at the intersection of cognitive science, artificial intelligence, and language development.

His research centers on understanding human cognition through computational models, particularly in the domain of infant language acquisition. By leveraging machine learning techniques, his work aims to reverse-engineer how children learn language, bridging gaps between developmental psychology and AI. This includes modeling early phonological and lexical development using synthetic learning systems.

The recent internship and postdoctoral positions advertised under his supervision highlight a growing focus on applying data science and AI to behavioral analysis in neurodegenerative diseases, indicating an expansion of his research into clinical cognitive neuroscience. His collaborative work with the Interventional Neuropsychology Laboratory underscores this interdisciplinary trajectory.

• Scientific Awards: No awards listed in the provided text.

Emmanuel Dupoux actively advises graduate students and postdoctoral researchers, as evidenced by his role as principal adviser for an M1/M2 internship on reverse engineering infant language development and co-adviser for a postdoctoral position in AI for neurodegenerative disease analysis. While specific grants are not mentioned, his leadership in hosting research positions suggests active external funding. He is involved in fostering research teams that integrate cognitive theories with machine learning frameworks.

He is associated with the Cognitive Machine Learning team at LSCP and collaborates with the Interventional Neuropsychology Laboratory, where he co-supervises research on AI-driven behavioral analysis in neurological disorders. These affiliations reflect a strong commitment to translational cognitive science, linking fundamental research in language development with clinical applications.