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A deeper insight on water use in plants thanks to portable MRI – DISRUPTOR
Terrestrial ecosystems play a key role in carbon sequestration. To trap carbon, plants need water. To do so, plants absorb water through their roots, which is then transported through the xylem to the leaves where sugars are synthesized from carbon dioxide during the photosynthesis. A tight coupling
AI-Driven Work Transformations in Creative and Cultural Industries – AI-CCI
In the contemporary landscape, characterized by the emergence of cutting-edge generative artificial intelligence, there is a growing apprehension regarding the impact of these technologies on the quality of work. The International Labour Organization (Gmyrek et al., 2023) issues a cautionary note, h
Creating Algorithms for Compact Decomposable Circuits – CERADOC
As artificial intelligence (AI) systems become increasingly integrated into sensitive domains, the need for transparency, reliability, and explainability becomes paramount. This project aims to enhance trust in AI by leveraging knowledge compilation techniques, particularly through the optimization
Adaptive Distributional and Algorithmic Robustness – ADAR
In machine learning, safety concerns arise from various factors, including data variability, algorithm instability, fairness and privacy constraints, and unpredictable environmental changes. Distributionally Robust Optimization (DRO) tackles these challenges by optimizing models across potential dat
Smart actuator and sensor networks for icing condition monitoring and low-consumption de-icing system control – SmartICE
The project focuses on addressing aircraft icing issues in the context of decarbonizing aviation. Aircraft icing, which affects lift, drag, and engine performance, is a significant risk, especially as climate change creates more adverse weather conditions like freezing rain. Future energy-efficient
Facial Analysis and Regulation - Support for Ethics and Explainability – FAR-SEE
The FAR-SEE project aims to study the issues of sampling bias, fairness, uncertainty and explicability of these features for Artificial Intelligence (AI)-based face recognition systems, with the aim of improving existing algorithms, revealing 'optimal' performance/fairness/explicability trade-offs a
The Interrogative Model of Inquiry Meets Dynamic Logic – IMI
The last 20 years have witnessed the emergence of a new logical paradigm which looks at the underlying unity of reasoning and rational arguments. The meaning of the term "logical" has been stretched to go beyond the study of traditional abstract logical notions like proof, computation, and expressiv
Mobility Assistance for Visually impaired People through Collaborative Acoustic Positioning – MAPV
The Mobility Assistance for Visually Impaired People through Collaborative Acoustic Positioning (MAPV) project aims to improve the mobility and independence of visually impaired people (VIP) by providing an accurate, infrastructure-free, and privacy-focused positioning framework. Over 2.2 billion pe
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
Synchronization of speech and gestures – SYNCOGEST
The SYNCOGEST project aims at modeling a part of the gestuality (mimics, postures and gestures) spontaneously deployed by speakers and their interlocutors during face-to-face communication, with a view to endowing embodied virtual conversational agents (ECAs) with a more natural and efficient attitu
