PROJECTS

• (03/2021-07/2021) Numerical methods for the Sylvester's matrix equation: The purpose of this project was to study the algorithms used to solve the Sylvester's equation. In particular, I had to study and implement on Matlab the Bartels-Stewart's algorithm, optimizing it in specific cases.
  
• (03/2021-06/2021) Non-negative Matrix Factorization with Sparsness Constrains: Project carried out during the course of Computational Mathematics. Main goal was to study techniques for the non-negative matrix factorization adding sparsness constrains, implementing the algorithms on Matlab.
  
• (09/2021-12/2021) Numerical methods for solving the Three-Body problem and the Robertson's problem: Project carried out during the course of Numerical Methods. Our aim was to study and implement on Matlab algorithms in order to solve ODEs.
  
• (11/2022-01/2023) Filter Feature Selection Methods: Python project where I have studied and implemented feature selection methods, focusing on the analysis and efficiency of their application on different datasets.
• (10/2022-09/2023) Least squares methods for Sylvester-like linear matrix equations: The purpose of my Master Thesis is to study the Sylvester-like linear matrix equations, such as generalized Sylvester equation A1XB1+A2XB2=C and the T-Sylvester equation AX^T+XB^T=C, in the large scale settings. In particular I have studied the corresponding least squares problems with rectangular coefficient matrices. We have implemented a truncated matrix-oriented version of the LSQR method and compared it to the more known truncated Conjugate Gradient.