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Robot In-hand Dexterous manipulation by extracting data from human manipulation of objects to improve robotic autonomy and dexterity – InDex
Humans excel when dealing with everyday objects and manipulation tasks, learning new skills, and adapting to different or complex environments. This is a basic skill for our survival as well as a key feature in our world of artefacts and human-made devices. Our expert ability to use our hands result
Quantitative 3D ultrasound brain imaging: development of new bedside biomarkers to better predict neurodevelopmental outcomes in preterm infants – QUSBI
White matter lesions are one of the main risk factors for neurodevelopmental disorders (NDD) in premature infants, and among these, punctate white matter lesions (PWMLs) are the most frequent. MRI is the reference brain imaging technique, but it has certain limitations (poor accessibility, low port
Low energy neuromorphic devices based on spin wave scattering by topological spin texture – Neurowave
Artificial neural networks underpin the current revolution in artificial intelligence (AI), reshaping how society views, processes, and produces information. However, they have led to a large rise in the global IT power consumption due to poorly optimized hardware architectures and computationally
Multi-functional metasurfaces for communication and sensing using time and space modulation – METATEMPO
The unprecedented growth in wireless traffic and the expected densification of next-generation networks call for disruptive approaches to reduce the number of radiofrequency (RF) systems and their power consumption. Reconfigurable intelligent surfaces (RISs) offer an energy-efficient solution for sp
Domain Adaptation for Neural Data Integration – DANDI
Developing machine learning methods suitable for data-limited systems is a core concern of artificial intelligence (AI) for health which typically suffers from sparse data. One promising approach is to leverage related data-rich systems through transfer learning; for example, by pre-training models
France brazil collaboration on universal behavior of exotic nuclear systems – FBCUBES
The FBCUBES project aims to enhance our understanding of neutron-rich systems, which are crucial to contemporary nuclear physics. By employing few-body techniques alongside cutting-edge ab initio methods, we seek to address the challenges of modeling weakly bound neutron-rich systems. This research
Controlled Customization and Reproduction of Surface Appearance Through Microtexturing – APPEARANCE_ON_DEMAND
APPEARANCE_ON_DEMAND seeks to revolutionize surface design and manufacturing by enabling the precise customization and reproduction of material appearances through innovative microtexturing techniques. The project is dedicated to developing an optimized production process capable of creating microte
Multifractal and AI Approaches for Coherent and Resilient Energy Networks in Urban Territories – FRACNET-CITY
Urban areas increasingly face the challenge of integrating renewable energy sources while simultaneously managing the demands of high population density, land spare and resilience to extreme climate events. Traditional urban planning methods often lack the capacity to fully address the intricate, mu
Merging novel cascade reactions and flow chemistry to expand the glycochemical space – SweetDom
The overarching goal of this project is to expand the glycochemical space while pursuing a sustainability-oriented approach. The first objective is to exploit the high synthetic potential of bifunctional exo-glycals in novel catalytic cascade cyclizations. Such domino processes enable the one-step c
Generative modeling, Heavy tails, Outliers, Sparse Training – GHOST
Generative Artificial Intelligence (GAI) models are expensive, with massive energy requirements for both training and inference (use in applications). As GAI models are increasingly adopted to solve problems across industry, significant changes in how we train and use these models are required both
