Scholar
Rémi Bardenet
Google Scholar ID: Nj74Gv4AAAAJ
CNRS, CRIStAL, Ecole Centrale Lille, Univ. Lille, France
Citations & Impact
Citations
9,225
H-index
28
i10-index
49
Publications
20
Co-authors
16
list available
Contact
Publications
Resume (English only)
Academic Achievements
- PI of ERC starting grant Blackjack (2020-2025), funded at 1.5M€; holder of a national chair in artificial intelligence; recipient of the 2021 CNRS bronze medal.
Research Experience
- Postdoctoral researcher at the University of Oxford, UK, working with Chris Holmes on Markov chain Monte Carlo for tall data; since February 2015, has been a senior researcher at CRIStAL, University of Lille, France, continuing research in computational biology.
Education
- Ph.D. obtained in November 2012 from University Paris-Sud, France, under the supervision of Balázs Kégl, focusing on Monte Carlo methods and Bayesian optimization applied to particle physics and machine learning.
Background
- Research interests include Monte Carlo methods and their applications in Bayesian inference, particularly how to scale these methods for expensive-to-evaluate integrands and large datasets. Specializes in data science with applications to natural sciences.
Miscellany
- Offers an open position for a master's internship followed by a PhD, focusing on negative dependence and point processes in data science, co-supervised with Subhro Ghosh from the National University of Singapore.
