Search for a funded project
Explainable artificial intelligence for anti-money laundering – XAIforAML
Current AML-CFT systems deployed by financial institutions are costly. They rely on rule-based systems, generate large numbers of false positives, and their actual contribution to apprehending criminal funds has been debated. AI offers new perspectives to improve the efficacy of AML-CFT, but regulatory uncertainty, particularly on the lack of explainability of machine-learning models, is a major barrier.
Ultra-Rapid Sintering: Multiphysics Simulation, Mechanisms, Control And Stabilization – ULTRARAPIDE
Flash sintering (ultra-fast) is a very interesting process for the implementation of «ultra-fast« prototyping of ceramic objects. However, the inherent instability of the heating and sintering process strongly limits the use of this process to samples of a few millimeters. In this project, we will explore different hybrid heating configurations to extend the stability of the process to shapes of a few centimeters.
PARAsitoid based DEcision tools for insecticide use reduction against grape and wheat agrosystem pests – PARADE
Biological control by natural enemies’ conservation against insect pests, as the European grape-berry moths and the cereal aphids, is a promising strategy. Farmers are more and more aware of the important role that natural enemies may play on the control of crop pests. Developing decision support tools based on an early and efficient assessment of in-field parasitism rate of these pests will support them to reduce insecticides by preserving and improving the natural pest regulation.
Ecological consequences of Temperature induced Body size shifts – EcoTeBo
A common phenotypic response to climate change is the reduction in body size of ectotherms with temperature — the hotter it is, the smaller they get—. However, the ecological consequences of these body size changes on communities remain largely unexplored.
Glacial--Interglacial variations of the carbon cycle induced by climatic changes in Himalaya – GI-NOAH
This project aims to clarify the climate sensitivity of the Earth system by recording the carbon burial (organic and inorganic) linked to the erosion of the Himalaya at the glacial-interglacial scale. We will apply mineralogical and geochemical studies on the active levee (0-100 ka) as well as the other quaternary levees cored by IODP Exp. 354 in the Bay of Bengal.
Measuring and mapping the plant virus richness at the ecosystem scale – PHYTOVIRUS
Emergent diseases of plants, a high proportion of which are caused by phytoviruses, are a significant burden on the food security and economic stability of societies. However, no studies have provided a comprehensive view of the geographical distribution of phytovirus diversity to date, including both the numbers or richness of virus species and the evenness of their distribution in any individual environment on Earth.
NGAL, a novel target in Hypertension and associated comorbidities – NGAL-HT
«Our recent exploratory studies identified novel key roles of NGAL (Neutrophil Gelatinase-Associated Lipocalin) in the control of blood pressure. This led to the NGAL-HT consortium associating synergic expertise in pathophysiological research, translational studies and population genetics.
Federated statistical learning for new generation meta-analysis of large-scale and secured biomedical data – FED-BIOMED
Federated Statistical Learning for New Generation Meta-Analyses of Large-scale and Secured Biomedical Data
Changes in political work through the prism of big data – MUTADATA
The present research program examines the emergence of political expertise on big data and how they professionalize their skills. Service providers who gather, manage and analyze microtargetting data are at the cross road between profession, expertise, and activism. They embody the diversity and variation of political professionalism within moving partisan structures and evolving political activities and practices.
Learning to synthesize 3D dynamic human motion – 3DMOVE
It has recently become possible to capture time-varying 3D point clouds at high spatial and temporal resolution, which allows in particular for high-quality acquisitions of human motion. Currently, first tools to process and analyze the data in a robust and automatic way are being developed. Such tools are critical to learning generative models of dynamic human motion. The objective of 3DMOVE is to compute high-quality generative models from a database of dense 3D motion sequences of humans.
