
About the chair
The Chair of Computational Mathematics of Fundación Deusto at University of Deusto, Bilbao (Basque Country, Spain) aims to develop an active research, training and outreach agenda in various aspects of Applied Mathematics. The Chair is committed with the development of ground-breaking research in the areas of Partial Differential Equations, Control Theory, Numerical Analysis and Scientific Computing; key tools for technological transfer and for the interaction of Mathematics with other scientific disciplines such as Biology, Engineering, Earth and Climate Sciences.

Enrique Zuazua
Enrique Zuazua (Eibar, Basque Country – Spain, 1961) holds an Alexander von Humboldt Professorship (FAU DCN-AvH) at Friedrich–Alexander-Universität Erlangen-Nürnberg (Germany). He is Director of the Chair of Computational Mathematics (DeustoCCM) at Deusto Foundation, University of Deusto (Bilbao, Basque Country-Spain). He has been awarded the Advanced Grants of the European Research Council (ERC) CoDeFeL (2022), DyCon (2016), NUMERIWAVES (2010). Since 2001 he is also a Professor of Applied Mathematics at the Department of Mathematics of the Autonomous University of Madrid where he holds a Strategic Chair.

ERC CoDeFeL
ERC CoDeFeL. Control for Deep and Federated Learning is an European project funded by the European Research Council – ERC (2024 – 2029), developed in cooperation between the FAU, Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany) and the University of Deusto in Bilbao, Basque Country (Spain). CoDeFeL seeks to make a breakthrough that takes the mathematical foundations of Machine Learning beyond their present frontiers, through the systematic development of new ideas and methods inspired by control theory.
Our latest!
Turnpike in optimal control and beyond: a survey
Large-time asymptotics for hyperbolic systems with non-symmetric relaxation: An algorithmic approach
Pointwise constraints for scalar conservation laws with positive wave velocity
Gaussian Beam ansatz for finite difference wave equations
Representation and Regression Problems in Neural Networks: Relaxation, Generalization, and Numerics

Gender Roles in Maths

At FAU-ZISC “Data-Driven COVID Modeling”

New Approaches to controlling Dynamics

CCM Webinar: Swinging up the double pendulum & Data Driven COVID modeling

Matemundo, by Enrique Zuazua
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