About AIXPERT¶

The AIXpert Project is a large-scale, multi-institutional research initiative uniting 17 partners under the Horizon Europe Research and Innovation Programme (Grant Agreement No. 101214389) and the Swiss State Secretariat for Education, Research and Innovation (SERI).

It aims to transform how AI is developed, deployed, and trusted by society, through a comprehensive framework for explainable, transparent, and accountable artificial intelligence.

Vision¶

An agentic, multi-layer, GenAI-powered backbone to make AI systems explainable, accountable, and human-centered. The project envisions an adaptable and trustworthy AI ecosystem that integrates explainability, fairness, autonomy, and robustness at every stage of AI development.

Objectives¶

Build an adaptable, explainable AI-agentic platform Develop interoperable modules that connect explainability, accountability, and fairness.
Define and assess AI trustworthiness Establish measurable criteria and indicators for evaluating the reliability and ethical alignment of AI systems.
Advance explainable multimodal foundation models Drive research in interpretable vision–language–reasoning systems.
Demonstrate real-world impact through pilot use cases Validate the framework across sectors including healthcare, employment, and education.

Consortium Partners¶

The AIXPERT consortium brings together leading academic, research, and industry organizations across Europe:

Athena Research Center, University of Barcelona, Amsterdam UMC, KYKLOS, Workable, University of Groningen, Philips, Sorbonne University, CNRS, Furhat Robotics, Orfium, Novelcore, Infinity Design Labs, ITML, Barcelona Supercomputing Center, Martel Innovate, and the Vector Institute (Canada).

The Vector Institute contributes expertise in Responsible AI, bias detection, fairness benchmarking, and explainable data generation pipelines within the global AIXPERT ecosystem.

Learn More¶

Team¶

The Vector Institute is a proud partner of the AIXPERT project — a Horizon Europe initiative building explainable, transparent, and human-centered AI. This site is maintained by Vector's AI Engineering team.

Shaina Raza, PhD

Ahmed Y. Radwan

Aravind Narayanan

Vahid Khazaie

Acknowledgment¶

Resources used in preparing this research were provided, in part, by the Province of Ontario, the Government of Canada through CIFAR, and companies sponsoring the Vector Institute.

Funding for the research was partly provided through Horizon Europe project AIXpert: An agentic, multi-layer, GenAI-powered backbone to make an AI system explainable, accountable, and transparent (ID: 101214389).