BioComp 2019

BioComp 2019 will take place from May 13th to 15th at the IRCICA in Lille.

Registration:

To register, you just need to fill the online form:

https://docs.google.com/forms/d/e/1FAIpQLScSCIiwmh7jn_x6uMjdk3a9Jzsq4EJvTbG6Uoh2tDNPc7ynOg/viewform?usp=pp_url

Venue:

IRCICA – 50 Avenue Halley – 59650 Villeneuve-d’Ascq, Lille

This map shows all locations relevant to the workshop GDR Biocomp 2019.

How to come: Venue

Where to sleep: Hotels

Poster Sessions:

Several poster sessions will be organized: please let us know in the online form if you would like to present your work.

Program:

The workshop will start on Monday, May 13th at 13h00 and will finish on Wednesday, May 15th at 12h00.

The detailed schedule of the workshop can be found here.

The BioComp’2019 meeting will be followed at the same place in Lille by a Nanospike workshop from May 15th in the afternoon to May 16 on “Spiking Neuron Networks, Nanodevices, Biodiversity”.

Presentation abstracts:

Marc Bocquet, IM2NP, Aix-Marseille Université

In-Memory and Error-Immune Differential RRAM Implementation of Binarized Deep Neural Networks

François Cabestaing, CRIStAL, Université de Lille

Recording and low-level processing of electrical brain activity

Yann Coello, SCALab, Université de Lille

A functional approach to the representation of space for interacting with objects and people

François Danneville, IRCICA, Université de Lille

Scaling progress of an ultra-low power neuromorphic technology for spiking neural network

Elisa Donati, ETH Zurich

Neuromorphic hardware for biomedical applications

Julie Grollier, Unité Mixte de Physique, CNRS-Thales

Neuromorphic computing with spintronic nano-oscillators

Maxime Jacquot, FEMTO-ST, Besançon

Photonic Neural Networks

Renaud Jolivet, Département de Physique Nucléaire et corpusculaire, Université de Genève

Energy-efficient information transfer in neural networks 

Benoît Larras, ISEN, Lille

LEOPAR: Low-Energy On-chip Pre-processing for Activity Recognition

Philippe Millet, Thales

Challenges in embedded Artificial Neural Network applications

Sdrjan Ostojic, LNC2, Ecole Normale Supérieure

Minimal implementations of behavioral tasks using low-rank recurrent neural networks

Mathieu Poumeyrol, SNIPS

Tract: running deep models on the edge

Jochen Triesch, Neurosciences group, Frankfurt Institute for Advanced Studies

Active Efficient Coding for Building Self-Calibrating Vision Systems

Blaise Yvert, BrainTech Laboratory, Inserm et Université Grenoble Alpes

Neuromorphic spike sorting: Toward very low-power neural processing in cortical implants