Emilie Kaufmann (born 1987)[1] is a French statistician and computer scientist specializing in machine learning, and particularly known for her research on the multi-armed bandit problem.
She is a researcher for the French National Centre for Scientific Research (CNRS), associated with the Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) at the University of Lille.
In 2011 she earned a master's degree in statistical learning from the École normale supérieure Paris-Saclay, and she completed her Ph.D. in 2014 at Télécom Paris.
[3] After postdoctoral research in the project on Dynamics of Geometric Networks (DYOGENE) with the French Institute for Research in Computer Science and Automation (Inria) in Paris, she joined CNRS and the Sequential Learning group (SequeL) of CRIStAL in 2015.
[4] Kaufmann was one of two winners of the 2014 Jacques Neveu Prize of the Société de Mathématiques Appliquées et Industrielles, recognizing the best French dissertations in mathematics and statistics from that year.