Flavia Esposito

Flavia Esposito is a Tenure-Track Researcher (RTT) in Numerical Analysis at the Department of Mathematics at University of Bari "Aldo Moro", where she is a member of the MIDAS research group.

Her research interests focus on mathematical foundations for Artificial Intelligence, with particular emphasis on optimization methods for machine learning and low-rank techniques for the analysis of real-world data. Her work combines optimization, numerical linear algebra, and machine learning, with applications in environmental sciences and biomedical data analysis. Her research activity includes dimensionality reduction methods, matrix decompositions, and hyperparameter optimization strategies, with the goal of understanding the mathematical structure underlying complex datasets and developing efficient methodologies for large-scale problems.

She is actively involved in the organization of national and international conferences and workshops in the fields of numerical analysis, optimization, and data science (please refer to Events page). She has hosted visiting researchers at University of Bari Aldo Moro (please refer to Collaborations page)and has participated in and coordinated several research projects in collaboration with national and international partners, focusing on low-rank methodologies, and data-driven applications in environmental and biomedical sciences (please refer to Projects page).  Among these, she serves as local Principal Investigator for the project “Repurposing marine products for the development of functional foods and bioactives to improve human health and coastal community sustainability”, developed in collaboration with Memorial University of Newfoundland MBI Project.

Academic e-mail: flavia.esposito at uniba dot it 

Academic address: Room 24, Department of Mathematics, University of Bari Aldo Moro, via E. Orabona 4, 70125 Bari, Italy

• Mathematical Models and Numerical Methods for Omics Data Analysis, Dottorato di ricerca in Informatica e Matematica, UniBa (AY 2024-2025);

• Low-rank Approaches for Data Analysis: Models, Numerical Methods and Applications, Remagen University, Germany(AY 2022-2023);

• Low-rank Approaches for Data Analysis: Models, Numerical Methods and Applications, Dottorato di ricerca Computer Science and Engineering , University of Bologna (AY 2022-2023);

• Metodi Numerici per la Bioinformatica, CdL Magistrale Bioinformatica, UniBa (AYs 2023-2024);

• Fondamenti di Matematica per l'Analisi dei Dati, CdL Magistrale Bioinformatica, UniBa (AYs 2022-2023, 2023-2024, 2024-2025, 2025-2026);

• Laboratorio di Programmazione e Calcolo CdL Triennale in Chimica, UniBa (AYs 2021-2022, 2022-2023);

• Metodi Numerici per la Data Science CdL Triennale in Matematica,UniBa (AYs 2020-2021, 2021-2022, 2022-2023, 2023-2024, 2024-2025, 2025-2026), Materials;

• OFA CdL Triennale in Matematica, UniBa (AY 2020-2021);