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Multi-scale matching for flows with a grid – MultiMatchGrid
A novel first principle approach will be proposed for dealing with multi-scale laminar, transitional and turbulent flows across weakly porous grids. Taking advantage of the separation of scales due to the small size of the grid pores, MultiMatchGrid will match the large far-grid to the small near-gr
BRAIN-Net: Spiking Neural Networks for Real-Time Processing of Brain Signals – BRAIN-Net
Large-scale neural recordings using high-density electrode arrays are key to understanding brain dynamics and designing brain-computer interfaces for rehabilitation. These devices produce large data flows that raise new challenges to extract relevant information in real time with limited power consu
THeory and Evidence to Measure Influence in Social structures – THEMIS
This project is positioned in the core of the emerging research area on social influence analysis but goes further in trying to demonstrate not only that this framework can be applied to other research domains through a property-driven approach, but also that the algorithmic and strategic aspects pl
Leveraging Interpretable Machines for Performance Improvement and Decision – LIMPID
Huge increase of collected data, storage capacity and computing power promote the field of Artificial Intelligence (AI) to the status of panacea to all problems. Indeed, neural networks improved the results in the fields challenging for the handcrafted algorithms previously. However, there is always
Rheological homeostasis of the expanding plant cell wall – HOMEOWALL
Every plant cell is surrounded by a wall, which is at the same time sufficiently strong to resist the turgor pressure and extensible to allow growth. Understanding how plants grow requires studying the architecture and the mechanical homeostasis of this polymer network. The objectives of HOMEOWALL a
Deciphering continuous MOLecular MOVements of BIOmacromolecular complexes by new cryo-Electron Microscopy image analysis methods – EMBioMolMov
Cryo-electron microscopy (cryo-EM) is under constant development for a routine determination of biomolecular structures (conformations) at high resolution. This project is focused on the development of approaches for identifying continuous conformational transitions from cryo-EM images through high-
Quantum Machine Learning: Foundations and Algorithms – QuantML
Quantum Machine Learning is an emerging field of research, with fast growth. This research field is largely driven by the desire to develop artificial intelligence that uses quantum technologies to improve the speed and performance of learning algorithms. Strong interdisciplinary collaborations are
Universite de Lyon Doctoral Program in AI – IADoc@UdL
In 2018, The Université de Lyon, with its institutional members and the scientific federation "Computer science in Lyon", jointly led a thorough study that identified the numerous strengths and assets of the local academic players on Artificial Intelligence and its societal outcomes. The Université
A Visual Memory Network for Scene Understanding – AVENUE
People visually interpret any new environment, interact with, and navigate it almost effortlessly. Despite significant progress, this level of visual intelligence has not been achieved by artificial systems. Project AVENUE aims to address this through a visual memory network for human-like interpret
Neurotechnology User Training System – NUTS
Despite their current lack of reliability, brain-computer interfaces (BCIs) based on motor imagery hold promise for a wide range of clinical and non-clinical applications. The user training that these technologies require, during which people learn to control their own brain activity, is a significa
