I’m pursuing an M.Sc. in Computational and Applied Mathematics at Friedrich-Alexander-Universität (FAU) Erlangen-Nürnberg, specializing in Optimization and Numerical Analysis. My thesis explores lower bounds on optimal cooling, leveraging optimization methods for PDEs, Semi-definite Programs (SDPs), and finite element discretization, mainly exploring 2 open problems:

1. Proving that the convergence for the lower bound, with a \(\Gamma\)-convergence analysis, exploiting Hardy-BMO duality, and that \(H_0^1(\Omega)\) is continuously embedded into \(\text{BMO}(\Omega)\).
2. Finding an efficient implementation, via a low-rank Newton method.

I hold a B.Sc. in Applied and Computational Mathematics from the University of São Paulo, which included a minor in Statistical Economics (Econometrics); a thesis on Support Vector Machines (SVMs) from an optimization perspective, including kernel methods and Python implementation, with full remarks Máquinas de vetores de suporte: Classificação, Regressão, Kernels e Otimização (link, in Portuguese); and guided studies on Image Classification methods and the Brouwer Topological Degree.

Additionally, I have over five years of professional experience as a data scientist, applying advanced machine learning (ML) techniques across various domains, including finance and healthcare. This involved implementing probabilistic ML models for various applications. Most recently, I’ve been working at FAU’s Image and Data Exploration (IDEA) Lab, optimizing text-conditioned diffusion models for pelvic MRI images, using FAU’s High-Performance GPUs.

Interests

My areas of interest include Functional Analysis, PDEs, Nonlinear Optimization, Dynamical Systems, Modelling, Finance, AI, and applied mathematics in general.