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Resilient multimodal transport management with shared autonomous electric vehicles under disruptions – RAISE
Natural disasters, technological failures, and human-caused accidents frequently disrupt public transport lines and infrastructure. This may result in shutdowns of public transport services and shift of travel demand to road networks. Without effective emergency response strategies, urban traffic sy
Dynamique et Optimisation des Processus de TRansport Intermittents – DYOPTRI
Many transport and search processes can be analyzed in term of a succession of two types of exploring steps. This intermittency is a general feature for numerous physical, chemical, biological and industrial systems. At the microscopic scale, we can mention the diffusive motion of species in confine
Optimization under uncertainties of fueling stations for electric and hydrogen vehicles – OSIRMEH
Decarbonising the transport sector remains the major challenge in the coming years at a global level. A massive development of mobility solutions based on hydrogen and electricity carriers is expected. For the land-based mobility, this will require the development of multi-energy carriers fueling st
XAI for Black-Box Models Using Logic-Based Formal Methods and Combinatorial Optimization – FORM-XAI
The FORM-XAI project addresses the growing need for interpretability in the field of artificial intelligence (AI), particularly in critical sectors such as healthcare, finance, and transportation. Complex models, such as deep neural networks, while effective, raise concerns about their opacity, ther
Combinatorial Optimization for Competing Agents – COCA
The project deals with problems at the interface between combinatorial optimization and game theory. Combinatorial optimization is a very active field in computer science. This is certainly due to the numerous real world applications (e.g. in telecommunications, transportation, engineering design...
Compression and Alignment for Efficient Machine Learning – CALME
The increasing availability of massive datasets presents a number of challenges for machine learning (ML), with two key issues standing out: the high dimensionality of the data and the difficulty of obtaining high-quality labelled data. This project aims to develop ML methods that require moderat
Mathematics of Stochastic and Deterministic Optimization for Deep Learning – MaSDOL
Machine learning (ML) and artificial intelligence are rising themes of research for decades because they have been considered as one way to produce new algorithms for solving striking challenges such as language understanding, best advice finding, automatic signal processing, fraud detection. The ex
Flexible and Intelligent Transportation Systems – FITS
The project FITS aims at proposing novel mathematical models and solution approaches in order to develop intelligent tools to help optimizing the delivery of services (such as care or maintenance deliveries) to customers located potentially at home. Service providers have human resources (possibly o
Analysis and characterization of pneumatic conveying of non-conventional solids – PHOBARS
The PHOBARS project (Pneumatic Handling Of Bio And Recycled Solids) aims at studying the pneumatic transport of non-conventional powders resulting from plastic wastes or second-generation biomasses. The scientific objective of the project is to understand the mechanisms and phenomena involved in the
Scalable routing in Multi-Modal transportation networks – MultiMod
The targeted breakthroughs of MultiMod is the scalability of routing algorithms exploiting real-time events. We ambition to do in large-scale networks like Ile-de-France (where existing solutions are mostly mono-modal) better than what is done in Lyon (planed multimodal), by including unplanned tran
