Rémi Bardenet

CNRS researcher

This page contains a summary of my research and teaching activities. For a detailed CV and full publication list, please click here;

Biographical Sketch:

I graduated in 2009 from ENS Cachan (France) with an MSc in mathematics for vision and learning. I obtained my PhD in 2012 at University Paris-Sud XI (France), working under the supervision of Balazs Kégl. In 2013, I joined 2020 science and Chris Holmes' group in the Statistics department of the University of Oxford (UK), as a postdoctoral researcher. Since 2015, I hold a research position at CNRS, and I am based at CRIStAL, the Computer Science and Signal Processing lab of the University of Lille (France).

Research Interests: 

I am interested in numerical Bayesian methods. Particular topics include large-scale approximate inference, adaptive Markov Chain Monte Carlo (MCMC), and Bayesian optimization. During my PhD, I was first interested in solving methodological problems motivated by MCMC inference in the Pierre Auger experiment, a large-scale cosmic ray observatory located in the Argentinian pampa. Second, I worked on automatic hyperparameter tuning methods, with the idea in mind to deliver turn-key machine learning software. Besides continuing research on these topics, I am currently interested in approximate Bayesian inference and decision-making for large datasets, and a variety of inference and model comparison applications in complex biological systems.

Teaching: 
  • 2015: I lectured 2x4 hrs on practical machine learning, for master-level engineering students of Ecole centrale Lille.
  • 2014: I lectured part of the course on Monte Carlo methods for 4th year students at Oxford's department of Statistics, 8x1 hrs.
  • 2013: I tutored problem classes for the same course, 11x1 hrs.
  • 2009-2012: I was a teaching assistant in computer science and applied maths at Polytech' Paris-Sud engineering school, where I gave 3x64 hrs of undergraduate (U) and graduate (G) exercise and practical sessions on linear and nonlinear optimization (U), stochastic processes (U), basic algorithmics and C programming (U), integer programming (G). Besides, I also took part in an orientation module to help first-year students to plan their studies.
Contact Email: 
remi [dot] bardenet [at] gmail [dot] com
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cvFull_bardenet.pdf295.46 KB