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19th Ave New York, NY 95822, USA

Basque Center for Applied Mathematics

Bilbao – Spain


The Basque Center for Applied Mathematics – BCAM is an international research centre in the field of Applied Mathematics and a centre promoted by the Department of Education of the Basque Government, which is part of the BERC network (Basque Excellence Research Centers). It was created in 2008 by the Basque Government through Ikerbasque. It also has the support of the UPV/EHU, the Provincial Council of Bizkaia, Innobasque and Petronor Innovacion. One of its main objectives is to put mathematics at the service of society through the transfer of knowledge, extending the results of its research to sectors such as biosciences, health, energy or advanced manufacturing, and working jointly with local and international institutions and companies.

It currently has a staff of more than 150 researchers of 25 nationalities working in diverse areas, from data science or computational mathematics to mathematical modelling. BCAM has been accredited three times in a row as a “Severo Ochoa” centre of excellence by the State Research Agency, a distinction awarded to the best research institutions in the world in their field.

Role in the project

The work at BCAM will be done as part of the BCAM Severo Ochoa Strategic Lab on Trustworthy Machine Learning. The Strategic Lab is a joint research lab between BCAM (Spain), and the University of Sussex (UK) established in 2021. We will contribute to leading the development of reliable models with fairness and bias considerations, translating those reliable models into ethical and trustworthy decision-making and contributing to case studies.As for the case-studies we are contributing to supporting loan officers and applicants in credit lending decision processes, and public policy makers in designing incentives and allocating funds.

The research areas involved in the project are as follows:

  • Algorithmic fairness
  • Transparency and uncertainty in algorithmic fairness
  • Robustness in machine learning models