My field of expertise covers various aspects of Applied Mathematics

including Partial Differential Equations (PDE), Numerical Analysis, Control and Data Sciences. These interconnected fields have as goal the modelling, analysis, computer simulation and control and design of natural phenomena and engineering processes arising in several contexts of R+D+i.

Analysis of Partial Differential Equations (PDE)

Control of diffusion models arising in Biology and Social Sciences

Modeling and control of multi-agent systems

Hyperbolic models arising in traffic flow and energy transport

Fractional PDE

Optimal design in Material Sciences

Micro-macro limit processes

The interplay between discrete and continuous modelling in design and control

The emergence of turnpike phenomena in long-time horizons

Inversion and parameter identification

Development of new computation tools and software

Waves in heterogeneous media: discrete and continuous

Optimal placement of sensors and actuators

Interactions with Industry

I had also the opportunity to work and run a numerous research projects in close collaboration with industry:

Aeronautics optimal design

In collaboration with my former PhD student Francisco Palacios (The Boeing Company, Long Beach, CA) I developed an intensive research agenda in aeronautic optimal design and numerical analysis with connections with industry and in particular the Airbus Consortium. This research has lead to the development of the new software Stanford University Unstructured – SU2

Electrical Networks

I was the PI of a joint industrial research project with the Arteche Group to develop computational software for parameter identification of electrical networks from onsite measurements.

Fluid Dynamics

I contributed to launch the research group in Computational Fluid Dynamics of Baltogar company

Research & Innovation

I had the honour of collaborating with Eibar City Hall in the development of dissemination activities on Research and Innovation

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Date: Wed. October 5, 2022 Event: FAU DCN-AvH Seminar Organized by: FAU DCN-AvH, Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany) Title: FAU DCN-AvH Seminar “Large-amplitude modulation of periodic traveling waves” Speaker: Prof. Dr. Kevin Zumbrun Affiliation: Department […]
Approximating the 1D wave equation using Physics Informed Neural Networks (PINNs) Code: • See the complete report by Dania Sana   Introduction Accurate and fast predictions of numerical solutions are of significant interest in many areas of science and industry. On one hand, most theoretical methods […]
Date: Mon. September 19, 2022 Event: FAU MoD Lecture Series Organized by: FAU MoD, Research Center for Mathematics of Data at FAU Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany) Title: FAU MoD Lecture “Learning-Based Optimization and PDE Control in User-Assignable Finite Time” Speaker: Prof. Dr. Miroslav Krstic Affiliation: University of […]
Practical course: Modeling, simulation, optimization FAU DCN-AvH. Friedrich-Alexander Universität Erlangen-Nürnberg (Germany) Period: Summer 2022 (IFAC CPDE 2022 Course) _ This course gives a general introduction and some recent developments on the interface between Control, Numerics, and Machine Learning (Supervised Learning and Universal Approximation). The first part […]
Date: Tue. September 6, 2022 Event: M4CSA, Mathematics for Computer Science and Applications. Title: Control and Machine Learning Speaker: Our Head Prof. Enrique Zuazua Affiliation: Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany) Our Head Enrique Zuazua talked about “Control and Machine Learning” at the M4CSA, Mathematics for Computer Science and […]
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