On 07/12  the Graduate School Chemistry is organizing its first annual event on the theme of “Machine Learning in Experimental Sciences” in partnership with the DiiP (Data Intelligence Institute of Paris).

The objective  is to provide GS students (master and PhD)  with an overview of the ML methods developed and their use in the main experimental research fields such as biology, physics, health, the environment…. The ambition is not to train specialists in ML but to present the tools and their uses for the analysis of data classically encountered in science (image analysis, statistical data, etc.). They will thus be able to understand the interest and limitations of the methods and develop collaborations with specialists in the field.

9h00 - 9h30     Welcoming coffee, distribution of badges

9h30 - 9h40       Data Intelligence Institute of Paris and Graduate School Chemistry presentation 

9h40 - 10h20    ●  Introduction to machine learning, Definition, Scope and Tools

                             Zografoula Vagena, Université Paris Cité, Data Intelligence Institute of Paris (diiP).

10h20 - 11h00  ●  Scalable High-Dimensional Similarity Search for Chemistry and Beyond

                             Thémis Palpanas, Université Paris Cité & Institut Universitaire de France (IUF). 

11h00-11h20     Coffee Break 

11h20 - 12h00  ●  Machine Learning for High Energy Astroparticle Physics

                             Yvonne Becherini, Université Paris Cité

12h00-12h40    ●  Machine Learning and Geosciences

                             Marc Bocquet, CEREA, École des Ponts et EdF R&D, île-De-France, France. 

12h40 - 14h00   Lunch 

14h00 - 14h40  ●  Artificial Intelligence and Clinical Decision

                             Anita Burgun, Université Paris Cité, Cordeliers Research Center, APHP, PR[AI]RIE Institute.

14h40 - 15h20  ● When Digital Pathology meets Artificial Intelligence : from staining modeling to companion test

                             Nicolas Loménie, Université Paris Cité, LIPADE, UFR Mathématiques et Informatique. 

15h20-15h50    Coffee break 

15h50 - 16h30  ●  How AI changes structural biology: the impact of improved structure predictions

                             Irène  Barbarin-Bocahu, Lab. BIOC, CNRS, Ecole polytechnique & Antoine Taly, LBT, CNRS

16h30 - 17h10  ●  Machine learning to accelerate discovery in chemical and materials sciences

                             François-Xavier Coudert, Chimie ParisTech, PSL Research University, CNRS. 

17h10              Conclusive Cocktail

Amphithéâtre Buffon

Bâtiment Buffon:17 rue helene brion 75013 Paris 75013 Paris

Métro Ligne 14, Bibliothèque François Mittérand