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

Oct. 3rd, 2017, 12h, room TBA.
Jean-Luc Starck (CEA)
Title: Cosmostatistics: Tackling Big Data from the Sky
Abstract: Since the dawn of time, humans have been wondering about their place in the Universe. Over the past century, advances in modern physics, technology and engineering, along with the unique possibilities offered by space missions, have opened new windows to explore the cosmos. All-sky surveys, with observations across the entire electromagnetic spectrum, are the best strategy to fully understand and model the Universe in detail. Major upcoming research facilities, such as the Large Synoptic Survey Telescope (LSST), the Square Kilometer Array (SKA) and the Euclid space telescopes will provide key elements to addressing this challenge, by producing high quality data of petabyte volumes. These surveys prove to be a major 'big data' challenge, which require the development of innovative statistical methods essential both for the data analysis and their physical interpretation. I will present some highlights of this methodology and more specifically show how novel techniques of sparsity and compressed sensing open new perspectives in analysing cosmological data. These enable us to answer fundamental questions about the nature of our Universe with impressive accuracy.