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Hello! I am Miguel Alfonso Mendez and I am an Associate Professor at the von Karman Institute for Fluid Dynamics (VKI). Here I teach differential equations for fluid mechanics, signal processing, and experimental methods at the Research Master program (Master after Master) in fluid dynamics. My research interest includes engineering modeling of fluid flows, experimental fluid mechanics, data-driven modal analysis, flow control, inverse problems, and machine learning.

Currently, I am supervising several Ph.D. theses in these fields and I am developing two new courses dedicated to machine learning for fluid dynamics. This website collects some material about my courses, upcoming events, ongoing projects, and publications

News

September 10th 2023

Back from London, where I took part in a short course on machine learning for energy systems: https://citycompressorsconference.london/short-course-forum/; Big thanks to Dr. Sham Rane for inviting me to give a lecture!

September 1th 2023

Back from Karlsruhe, where I took part in a wonderful summer school on digital twins for Nuclear Reactor Design and  Optimization (more info https://www.fjohss.eu/215.php). Big thanks to Prof. Dr. Stieglitz, Robert and Dr. Jacqmin, Robert, for inviting me to give a few lectures on machine learning for fluid dynamics. 

June 29th 2023

I re-activated this website. Sorry for the long absence... more news is coming soon!

April 1st 2022

Coming back from the 78th European Space Agency - ESA Parabolic Flight Campaign! (see post)

March 22nd 2022

I have the pleasure and honor to give a seminar titled 'A tutorial on Multiscale Proper Orthogonal Decomposition (mPOD) ' at the Computational Methods in Systems and Control Theory group of Prof. Benner at the Max PLanck Insittute (link)

March 11th 2022

Our article 'Artificial neural networks modeling of wall pressure spectra beneath turbulent boundary layers' is published on Physics of Fluids  (Linkedin Post)

March 1th 2022

Check out the notes from my keynote lecture on 'Challenges and Opportunities for Machine Learning in Fluid Dynamics' at the NURETH conference (Linkedin Post)

February 23rd 2022

Our article on the comparative analysis of machine learning methods for flow control' is on arxiv! (Linkedin Post)

December 23rd 2022

Our article on the meshless integration of pressure fields using RBFs' is on arxiv! (Linkedin Post)

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