MUFRAMEX is co-running a virtual panel discussion on Physics Aware Deep Learning, on June 19th, 2024.

Artificial Intelligence is increasingly finding its way into all fields of science. Physics is no exception to this trend, seeing its usual simulation processes impacted by new models powered by AI. The aim of this conference is to present the most recent research in this field in Mexico and France, with a particular focus on the studies of the two speakers.



Alejandro Guerrero is an associate professor at the Department of Mathematics at the UdeG, Mexico. He has worked in numerical optimization, evolutionary computing, and numerical methods. His interests lie in developing efficient numerical methods to solve differential equations and inverse problems. His research focuses mainly on neural network theory and applications, particularly studying new approaches to solving differential equations based on deep learning models.

Patrick Gallinari is a professor at Sorbonne University, affiliated with the ISIR laboratory, and a distinguished researcher at Criteo AI Lab in Paris. He is a pioneer in the field of neural networks. His research focuses on statistical learning and deep learning, with applications in various domains such as semantic data processing and complex data analysis. A few years ago, he spearheaded research on physics-aware machine learning and contributed to seminal works in this field. Additionally, he holds a national AI chair titled “Deep Learning for Physical Processes with applications to Earth System Science”.


June 19th, 2024  • 6 PM (France) • 10 AM (CDMX) • online (Zoom) • free and public event, in English

Event in partnership with the University Center of Exact Sciences and Engineering, the University of Guadalara, Sorbonne University and the Institute of Intelligent Systems and Robotics.