Federica Porta

Federica Porta is an Associate Professor at the Department of Physical, Computer and Mathematical Sciences, University of Modena and Reggio Emilia. Her academic career focuses on numerical analysis, optimization, and stochastic gradient methods, particularly in machine learning and image restoration.

Her research interests include:

• Numerical Analysis and Statistics for Computer Engineering
• Numerical Optimization for Artificial Intelligence
• Stochastic Gradient Descent with Variance Control
• Deep Image Prior Frameworks
• Regularization Techniques for Biomedical Imaging

Federica's recent publications (2021–2025) demonstrate expertise in hybrid gradient projection methods, adaptive learning rate selection, and deep learning applications for image segmentation and classification. She collaborates extensively with researchers like Giorgia Franchini, Valeria Ruggiero, and Luca Zanni, applying these methods to both convex and non-convex optimization problems.

She teaches courses such as Numerical Analysis and Statistics for Computer Engineering, Numerical Analysis for Mathematics, and Numerical Optimization for Artificial Intelligence. Her teaching emphasizes MATLAB/Python implementation of numerical methods, convergence properties, and computational complexity analysis.

Contact: federica.porta@unimore.it | Office: Mathematics Building, Via Campi 213/b