Data Science Colloquium


of the ENS

Welcome to the Data Science Colloquium of the ENS.

This colloquium is organized around data sciences in a broad sense with the goal of bringing together researchers with diverse backgrounds (including for instance mathematics, computer science, physics, chemistry and neuroscience) but a common interest in dealing with large scale or high dimensional data.

The seminar takes place, unless exceptionally noted, on the first Tuesday of each month at 12h00 at the Physics Department of ENS, 24 rue Lhomond, in room CONF IV (2nd floor).

The colloquium is followed by an open buffet around which participants can meet and discuss collaborations.

These seminars are made possible by the support of the CFM-ENS Chair “Modèles et Sciences des Données.

You can check the list of the following seminars bellow and the list of past seminars.

Videos of some of the past seminars are available online.

Organizers

The colloquium is organized by:

Next seminars

Nov. 14th, 2017, 12h00-13h00, room CONF IV (physic dpt, Rue Lhomond).
Rémi Monasson (ENS)
Title: Searching for interaction networks in proteins: from statistical physics to machine learning, and back
Abstract: Over the last century, statistical physics was extremely successful to predict the collective behaviour of many physical systems from detailed knowledge about their microscopic components. However, complex systems, whose properties result from the delicate interplay of many strong and heterogenous interactions, are notoriously difficult to tackle with first-principle approaches. It is therefore tempting to use data to infer adequate microscopic models. I will present some efforts made along this direction for proteins, based on the well-known Potts model of statistical mechanics, with an emphasis on computational and theoretical aspects. I will then show how machine learning, whose unsupervised models encompass the Potts model, can be an inspiring source of new questions for statistical mechanics.

Feb. 6th, 2018, 11h00-12h30, room TBA.
Maureen Clerc (INRIA)
Title: TBA
Abstract: TBA