
About
David Mercier is a Professor at the University of Artois, France, affiliated with the LGI2A laboratory and the IUT de Béthune's Department of Networks and Telecommunications. He holds a HDR (Habilitation à Diriger des Recherches) from 2015 and a PhD from the University of Technology of Compiègne (UTC), France (2006). His research focuses on information fusion, belief functions, and uncertainty management, with applications in electrical engineering, transportation systems, and machine learning.
Education
- DEA (M.S. Equivalent) in Artificial Intelligence, University Paul Sabatier, Toulouse (2003)
- PhD in Information Fusion for Postal Address Recognition, UTC (2006)
- HDR (Research Habilitation), University of Artois (2015)
Research & Awards
Notable contributions include work on contextual belief function corrections, vehicular network information fusion, and multi-target tracking. He received a co-best student paper award at BELIEF 2016. His research spans electrical machines diagnosis, stochastic simulations, and deep learning integration with Dempster-Shafer theory.
Students & Involvement
Supervised PhD theses include studies on evidential deep learning and motor fault diagnosis. Active in the Belief Functions and Applications Society (board member since 2010). Co-edited special issues in International Journal of Approximate Reasoning and authored book chapters on belief function applications.
Labs & Teams
Primary affiliation with LGI2A laboratory, collaborating with institutions like LSEE and industrial partners such as Solystic and SNCF. Research integrates theoretical advances with practical applications in smart mobility and fault detection.
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