Develops the use of geometric principles to solve real-world problems. From the geometry of proteins to the modeling of spacetime, this research vertical applies advanced geometric techniques to understand complex phenomena in areas such as biology, computer science, physics, and communications.
Led by Alberto Saa (UNICAMP)
Identification of solutions to the problem of determining 3D protein structures using intersections of spheres and spherical shells, as well as the analysis of latent space stability and the manipulation of latent variables, with applications in semantic image manipulation and content-based image retrieval.
Classification of horizon stability based on local geometric invariants, analysis of scattering and geodesic dynamics in General Relativity, and geometric classification of gravitational analogues in condensed matter.
Analysis of geometric constructions and properties of codes and networks to be applied in transmission across different channels, the study of problems related to lattice-based cryptography, and the application of the Fisher–Rao metric for data clustering in various contexts, as well as for optimizing supervised machine learning algorithms.