Trustworthy Intelligent Systems (Fiabilité des Systèmes Intelligents) mi_liam_02

Artificial intelligence is everywhere. It is currently powering many systems in everyday life, modern enterprises and any
decision support system. It has been proven to be useful in many applications, such as healthcare, finance, industry, and
many critical and complex systems. As we move forward toward adopting AI in every part of the society, we as humans, we
still need to trust their output, especially when deployed in critical systems with decisions of high importance and high cost.
The Trustworthy Intelligent Systems (TAI) group aims to enable AI algorithms to be trustworthy, reliable, safe, robust and
explainable. Actually, we believe that we cannot trust the decisions made by AI algorithms unless we can assess their safety,
reliability, security and robustness. We aim also to address the application and deployment of trustworthy AI on different
domains such as Cyber-Physical Systems, Healthcare, Agriculture and the Industry. TAI will cover any existing algorithms and
architectures in AI, including machine learning and deep learning techniques, such as Natural Language Processing (NLP)
and Computer Vision. TIS will be powered by research projects such as PRFU, with possible supervision of PhD students on
recent topics in AI. It will also encourage Master students to be integrated in its research activities.

AI

Machine Learning

Deep Learning

Computer Vision

Natural Language Processing

Explainable AI

Trustworthy

Security

Safety

Robustness

Fairness

Reliability

Interpretability

Adversarial attacks