Grands Challenges

One of the ambitions of TRAIL is to reconcile as much as possible cutting-edge research with the needs of the Walloon economic fabric. One approach to reach this objective was to bring researchers to define, in close collaboration with companies, not necessarily active in the AI sector at this time, 8 collective challenges.

Each of these challenges is placed under the responsibility of an accredited research center that coordinates the work of researchers from all the project partners. Each challenge also includes one or more of the 4 major research themes of TRAIL, which are:

Learning for Optimizing (Metaheuristics and Machine Learning for Combinatorial Optimization)

MDA

Machine Learning-based Energy Prediction, Management, and Optimisation Towards Better Energy Decision-Making Process

MDA

Full-Spectrum Privacy-Preserving Artificial Intelligence

TRU

Weakly-Supervised Machine Learning, Towards a More General AI

EMB

Trustworthy AI for Critical Systems

TRU

Interactions with State-of-the-Art AI to reach Zero-Defect, Zero-Accident, and Zero-Burnout in a Production Environment

HUM

Using Advanced AI Solutions to Achieve “First Time Right” and “Consistent Product Quality” Throughout the Product Development and Manufacturing Cycle

HUM

Hybrid Modelling Methods towards an Augmented Engineering: The Use Case of AI-enabled Additive Manufacturing

EMB