Yannick Prié
Département Informatique
Rue Christian Pauc
44306 Nantes cedex 3
(+33)2 40 68 32 48
(+33)2 40 68 32 40

Short bio

Born 16/11/1971. One child. Engineer Degree in Computer Science IMT Atlantique (formerly Ecole Nationale Supérieure des Télécommunications de Bretagne), Brest (1995), Master's degree in Artificial Intelligence and Cognitive Sciences, Interpretative Semantics and Computing, with honours, University of Rennes 1. PhD Thesis, Representing Audiovisual Documents with Annotations Interconnected Strata for Contextual Exploitation from INSA-Lyon, with honours. Associate professor at the Claude Bernard Lyon 1 University between 2000 and 2012. HDR (Habilitation à Diriger des Recherche) entitled Towards a Phenomenology of Digital Inscriptions. Dynamics of Activity and Informational Structures in Interpretation Systems in nov. 2011. Full Professor at University of Nantes since sept. 2012. Research interests include Human-Computer Interaction, Information Visualization, User experience, with a focus on interdisciplinary approaches for the study of human-machine coupling and co-development.


His general interest is on Human-Computer Interaction, which he proposes to consider from two points of view: that of activity from the humane side, and of the information structures that are manipulated from the machine side. The aim is to be able to think about the co-evolution of activity and information structures at various time scales, focusing on the individual level, which is the place of signification for action, while taking into account the social level where the activity takes place.

One privileged domain is that of Knowledge Work mediated activity considered as permanent reading and writing of digital inscriptions in a both individual and collective information space, where the user as a subject builds his/her interaction and tools with the system, interpreting data and documents. Two approaches are considered:

  • The analytical approach consists in studying how users’ activity and systems co-evolve (how users do appropriate systems, the way usages evolve, learners’ engagement on distant learning platforms, etc.) by analyzing digital traces of the activity that range from user experience assessment to logs, and methods raging from data mining to qualitative annotations.

  • The system engineering approach consists in designing systems that support the development of human-machine coupling either by assisting users in the development of their activity, or being flexible enough to be shaped by users.

Interpretation systems such as video annotation or visual analytics systems play a pivotal role: systems are build (second approach) that allow knowledge workers to construct interpretations of activity traces, and which dynamics of coupling can be studied (first approach).

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