Scholar
Emilie Kaufmann
Google Scholar ID: 9GE1vx4AAAAJ
CNRS & Univ. Lille (CRIStAL)
Citations & Impact
Citations
4,691
H-index
32
i10-index
52
Publications
20
Co-authors
10
list available
Contact
No contact links provided.
Publications
Resume (English only)
Background
- CNRS Junior Researcher at CRIStAL, Université de Lille
- Member of the Inria team Scool at Inria Lille - Nord Europe
- Research interests lie in statistics and machine learning, with a focus on sequential learning
- Studies stochastic models including variants of the Multi-Armed Bandit (MAB) and Markov Decision Processes (MDPs)
- Works on both reinforcement learning (maximizing rewards while learning) and adaptive testing (learning as fast as possible through adaptive data collection)
- Recent applications include bandit strategies for adaptive early-stage clinical trials and contextual bandits for precision medicine
