Explores atomic descriptors, emphasizing symmetry, locality, and the challenges of incorporating electrostatics in machine learning models for chemistry.
Explores data-driven modeling of haemodynamics in vascular flows, focusing on computational challenges, reduced order modeling, FSI problems, and neural network applications.
