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 at the Friedrich–Alexander University (FAU), Erlangen (Germany). He is also the Director of the Chair of Computational Mathematics at Deusto Foundation, Universidad de Deusto (Bilbao, Basque Country-Spain) where he led the research team funded by the ERC Advanced Grant DyCoN project (2016-2022). He is also a Professor of Applied Mathematics since 2001 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!
An inverse problem for Moore-Gibson-Thompson equation arising in high intensity ultrasound
Averaged turnpike property for differential equations with random constant coefficients. Mathematical Control and Related Fields
Boundary Controllability for the 1D Moore-Gibson-Thompson equation
Controllability properties from the exterior under positivity constraints for a 1-D fractional heat equation
Discrete Carleman estimates and application to controllability for a fully-discrete parabolic operator with dynamic boundary conditions
Enrique Zuazua: TOP TALENT de la CIENCIA
Networks, Waves and Control
StudOn AG Neural Differential Equations, Control and Machine Learning
DyCon blog: Multilevel Selective Harmonic Modulation via Optimal Control
Jornada de Primavera en EDPs
Perceptrons, Neural Networks and Dynamical Systems
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