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QUANTum mechAnicS for prediction and arTificial Intelligence for early thermal runaway deteCtion and mitigation – QUANTASTiC
indicators such as pressure, utilizing artificial intelligence (AI) for enhanced monitoring. Additionally,
Pyrotechnical safety-critical system – STEPY
conducted, opening the possibility for future intelligent activation to address cases of malicious intrusion
Pushing a PETase to the extremes of NMR – NMRATOMIC
engineering has been accelerated by artificial intelligence and high-throughput screening, surpassing the
Pull the COVID-19 replicative catalytic core apart – PullCoVapart
SARS-CoV and will combine methods in artificial intelligence with protein biochemistry to propose therapeutic
Protein in silico assessment – PISA
with this challenge using an hybrid artificial intelligence approach combining deep artificial neural networks
Protein fold diversity and evolution in Archaea: from adaptation to extreme environments to the origin of eukaryotes – DArchFolds
revolutionized structural biology with an artificial intelligence network able to predict 3D protein structures
Protection Against Criminal use of Steganography – PACeS
Detection of hidden information in images and images generated using artificial intelligence.
Prospect FD : development of an aid decision-making tool for the prospection of vine Flavescence Dorée – Prospect FD
The Prospect FD project proposes to combine different techniques (imagery, artificial intelligence, information systems, precision viticulture and human expertise) for the detection of flavescence dorée. It relies (i) on a choice of sensors embedded on harvesting machines, (ii) on a data infrastructure that makes it possible to centralize, process and make available the information captured, (iii) on a geographical application (Decision Support System) presenting all information to experts.
Propositional Reasoning for Large-Scale Optimization. Application to Clean Energy Mobility Issues – Massal'IA
Propositional reasoning has been already successfully used in real optimization. However, the state of the art does not allow to treat more complex information. This proposal aims at obtaining significant advances in automatic reasoning and large-scale optimization by combining propositional reasoning (SAT and Max-SAT) and machine learning, by taking into account complex information with incomplete and uncertain data that are evolving over time.
Propagation of hydrogen flames for safety applications – PHYSSA
to developed an approach based on Artificial Intelligence to reconstruct information from 2D experimental
