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Eduardo BRANDAO

Eduardo Brandao is an Associate Professor at Jean Monnet University / Télécom Saint-Étienne, and a member of the Hubert Curien Laboratory and the Inria MALICE team. He holds a BSc in Physics from the University of Lisbon, an MSc in Applied Mathematics from the University of Waterloo, and graduated from the international Master in Machine Learning and Data Mining at Jean Monnet University. He defended a Manutech-SLEIGHT co-funded PhD in Physics-Guided Machine Learning in 2023. His work is linked to Manutech-SLEIGHT projects including PGML and PIMALEA, on physics-guided learning, laser-matter interaction and surface engineering.


MAIN REPONSABILITIES

Member of the Scientific Committee of the EUR MANUTECH-SLEIGHT.
Responsable pédagogique of CITISE 1 and CITISE 2 at Télécom Saint-Étienne, from September 2026.


TEACHING

Mathematics, computer science, machine learning and scientific machine learning for engineering students at Télécom Saint-Étienne.


COURSES
  • Mathematics for engineering students.
  • Object-oriented programming in C++.
  • Deep learning
  • Numerical methods for physical modelling


PUBLICATIONS
E. Brandao, A. Nakhoul, S. Duffner, R. Emonet, F. Garrelie, A. Habrard, F. Jacquenet, F. Pigeon, M. Sebban, J.-P. Colombier, “Learning Complexity to Guide Light-Induced Self-Organized Nanopatterns”, Physical Review Letters 130, 226201, 2023.
E. Brandao, J.-P. Colombier, S. Duffner, R. Emonet, F. Garrelie, A. Habrard, F. Jacquenet, A. Nakhoul, M. Sebban, “Learning PDE to Model Self-Organization of Matter”, Entropy 24, 1096, 2022.
F. A. Banna, E. Brandao, A. Nakhoul, R. Emonet, M. Sebban, J.-P. Colombier, “Photonic Learning in Ultrafast Laser-Induced Complexity”, Ultrafast Science, 2026.
F. A. Banna, A. Caradot, E. Brandao, J.-P. Colombier, R. Emonet, M. Sebban, “Unrolled-SINDy: A Stable Explicit Method for Nonlinear PDE Discovery from Sparsely Sampled Data”, ECML PKDD 2026.