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

Feb. 6th, 2018, 12h00-13h00, room Salle Jean Jaurès, 29 rue d’Ulm (sous-sol).
Maureen Clerc (INRIA)
Title: Brain-computer interfaces: two concurrent learning problems
Abstract: Brain-Computer Interfaces (BCI) are systems which provide real-time interaction through brain activity, bypassing traditional interfaces such as keyboard or mouse. A target application of BCI is to restore mobility or autonomy to severely disabled patients. In BCI, new modes of perception and interaction come into play, which users must learn, just as infants learn to explore their sensorimotor system. Feedback is central in this learning. From the point of view of the system, features must be extracted from the brain activity, and translated into commands. Feature extraction and classification issues, are important components of a BCI. Adaptive learning strategies, because of the high variability of the brain signals. Moreoever, additional markers may also be extracted to modulate the system's behavior. It is for instance possible to monitor the brain's reaction to the BCI outcome. In this talk I will present some of the current machine learning methods which are used in BCI, and the adaptation of BCI to users' needs.

March 13rd, 2018, 12h00-13h00, room CONF IV (physic dpt, Rue Lhomond).
Elizabeth Purdom (Berkeley)
Title: TBA
Abstract: TBA