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About

I am the Principal Investigator of the Decision and Bayesian Computation lab and a theoretical physicist by training. My research is focused on the algorithms and computation selected by evolution to perform biological decision-making.I address this topic with an interdisciplinary approach mixing statistical physics, Bayesian machine learning, information theory and various experimental biological setups. I am pursuing with the lab 3 following research axis:

Probabilistic pipelines and Artificial Intelligence to probe single biomolecule random walks (https://goo.gl/4UH7NZ). We designed an probabilistic software that identifies random walks and quantify their properties from single molecule microscopy imaging. We published more than 10 papers on the subject (e.g. Phys. Rev. Lett 2009, Biophys. J. 2012-2014-2016, Nat. Method. 2015, Science 2015, Cell. Rep 2017, Sci. Rep. 2018) and applied our schemes to receptor in synapses, CRISPR in the nucleus, HIV Virion formation etc. Current efforts are focused on TRamWAy, a machine learning software that entirely automates single molecule experiment analysis while being scalable to analyse Terabytes of data in few hours.

Diffusion landscape of Glycine receptor on the surface of a neuron.

Decision-making of biological system (https://goo.gl/28TfNC). We study biological intelligence and computation. We have developed approaches to probe biological decision by joining physical modelling, Bayesian inference and information theory to biological experiments. We probed the memory of bacteria (PNAS, 2012), the search strategies of leucocytes (Current Biol 2013) and decision making of insects in turbulent flows (J. phys. A. 2009, PNAS 2013, J. vis. Exp. 2014, Front. in AI. 2015, Plos. Comp. Biol. 2017, 2 patents). We are now focusing on algorithms implemented in the brain of the drosophila larva (Cell 2017).

Color coded behaviour of a drosophila larva as one neutron is being ontogenetically activated

 

Machine learning in Virtual Reality: DIVA ( https://goo.gl/dnNueu ). This project is a collaboration between my lab and Maxime Dahan’s lab. The project joins human cognition, probabilistic AI and virtual reality to explore complex unstructured data. Results are included in the software DIVA (J Mol Biol 2019). The DIVA-medical platform is now introduced in 4 hospitals with applications ranging from breast cancer surgery planning to pre-natal diagnosis from MRIs. The DIVA microscopy platform is now installed in more than 10 labs.

Confocal image of mice anterior/dorsal hippocampus neurons in DIVA

Courses

Scientific Programming in Python

The ever growing usage of high throughput technologies in Biology is revolutionizing the life sciences and profoundly changing its practices. Scripting languages are used on a daily basis in life science labs in order […]

2017-03-06 09:30:00 2017-03-18 17:00:00 Europe/Paris Scientific Programming in Python The ever growing usage of high throughput technologies in Biology is revolutionizing the life sciences and profoundly changing its practices. Scripting languages are used on a daily basis in life science labs in order […] 25 Rue du Dr Roux, 75015 Paris, France

Projects

Software

Patents

CV

Education and Academic Positions

  • 2008- … Research Scientist (Tenure) Pasteur Institute
  • 2016-… Visiting Scientist Janelia
  • 2014-2016 Invited Visiting Scientist Janelia Research Campus (on Campus)
  • 2014 Invited Visiting Scientist Institut Curie (Dahan’s lab-6 months)
  • 2009 Invited Visiting Scientist KITP (3 months)
  • 2004-2007: PhD: “Ionics constrast terahertz imaging – Statistical Physics of Surface Plasmon-Polariton”, LOB at Polytechnique under the supervision of Guilhem Gallot
  • 2002-2004 : Magistères (undergraduate + graduate) Theoretical physics (Astrophysics, Quantum field theory, Statistical Physics) at ENS-Lyon: with honours
  • 2000-2002 : Classe Préparatoire aux grandes écoles PC* : admitted Ecole Polytechnique, Ecole Normale Supérieure de Lyon

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