Jacobo Ayensa

On February 20, Jacobo Ayensa-Jiménez was invited to give a talk at the  Madrid Institute for Advanced Studies in Material Science  (IMDEA Materiales). He explained his work on Physically-Guided Neural Networks with Internal Variables (PGNNIV) and presented some applications in computational solid mechanics, where PGNNIV may be used for understanding materials and predicting their behavior. He also presented some applications of PGNNIV to biomedical engineering, such as the use of this methodology for understanding the metabolic switch of glioblastoma (GBM) cell cultures and the prediction of GBM progression in microfluidic devices.

He also took the opportunity to meet with our close collaborators and define the next steps of what will surely be a fruitful collaboration.

If you want to know more about PGNNIV, check our articles:

Ayensa-Jimenez, J., Doweidar, M. H., Sanz-Herrera, J. A., & Doblare, M. (2021). Prediction and identification of physical systems by means of Physically-Guided Neural Networks with meaningful internal layers. Computer Methods in Applied Mechanics and Engineering381, 113816.

Ayensa-Jiménez, J., Doweidar, M. H., Sanz-Herrera, J. A., & Doblaré, M. (2020). On the application of physically-guided neural networks with internal variables to continuum problems. arXiv preprint arXiv:2011.11376.

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