Flavia Esposito

Flavia Esposito is a Research Fellow at the Department of Mathematics at University of Bari "Aldo Moro" (RTD-A in Numerical Analysis).

My research interests focus on mathematics for data science. I work in the MIDAS group since 2014 and our research topics range from dimensionality reduction techniques and matrix decompositions to optimization with the study of hyperparameter tuning in machine learning problems. Our main goal is to understand the mathematics behind data analysing it in different application domains such as bioinformatics and enviromental field.

She has been recently awarded as local PI for the project: "Repurposing marine products for the development of functional foods and bioactives to improve human health and coastal community sustainability" in collaboration with Prof. Raymond Thomas https://mbiproject.ca/.

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

Journals

• Bi-level algorithm for optimizing hyperparameters in penalized nonnegative matrix factorization. Del Buono N., Esposito F., Selicato L.,Zdunek R. , Applied Mathematics and Computation 457, 128184, 2023

• A Decision-tree Approach to Stratify DLBCL Risk Based on Stromal and Immune Microenvironment Determinants. GM Zaccaria, MC Vegliante, G Mezzolla, M Stranier, G Volpe , N Altini, G Gargano, SA Pappagallo, A Bucci, F Esposito, G Opinto, F Clemente, A Negri, P Mondelli, MS De Candia, V Bevilacqua, A Guarini, S Ciavarella. A,HemaSphere 7 (4), 2023

• Cluster of resistance-inducing genes in MCF-7 cells by estrogen, insulin, methotrexate and tamoxifen extracted via NMF". A Boccarelli, N Del Buono, F Esposito, Pathology-Research and Practice 242, 154347, 2023.

• Role of lipidomics in assessing the functional lipid composition in breast milk. Ganeshalingam M, Enstad S, Sen S, Cheema S, Esposito F and Thomas R (2022) Front. Nutr. 9:899401. doi: 10.3389/fnut.2022.899401

• NR1H3 (LXRα) is associated with pro-inflammatory macrophages, predicts survival and suggests potential therapeutic rationales in diffuse large b-cell lymphoma. Vegliante, MC, Mazzara, S, Zaccaria, GM, De Summa, S, Esposito, F, et al. Hematol Oncol. 2022; 1- 12. https://doi.org/10.1002/hon.3050

• Colorectal cancer in Crohn's disease evaluated with genes belonging to fibroblasts of the intestinal mucosa selected by NMF. Boccarelli A., Del Buono N., and Esposito F.. Pathology-Research and Practice 229 (2022): 153728.

• A Review on Initialization Methods for Nonnegative Matrix Factorization: Towards Omics Data Experiments, Esposito, F. Mathematics 2021, 9, 1006. https://doi.org/10.3390/math9091006

• A New Ensemble Method for Detecting Anomalies in Gene Expression Matrices, Selicato, L.; Esposito, F.; Gargano, G.; Vegliante, M.C.; Opinto, G.; Zaccaria, G.M.; Ciavarella, S.; Guarini, A.; Del Buono, N.  Mathematics 2021, 9, 882. https://doi.org/10.3390/math9080882

• Electronic case report forms generation from pathology reports by ARGO, automatic record generator for onco-hematology. Zaccaria, G.M., Colella, V., Colucci, S., Clemente F., Pavone F., Vegliante MC, Esposito F. et al. Sci Rep 11, 23823 (2021). https://doi.org/10.1038/s41598-021-03204-z

• Analysis of fibroblast genes selected by NMF to reveal the potential crosstalk between ulcerative colitis and colorectal cancer. Boccarelli A, Del Buono N., and Esposito F.. Experimental and Molecular Pathology 123 (2021): 104713.

• An NMF-Based Methodology for Selecting Biomarkers in the Landscape of Genes of Heterogeneous Cancer-Associated Fibroblast Populations. F. Esposito, Boccarelli A, N. Del Buono. Bioinformatics and Biology Insights. January 2020. doi:10.1177/1177932220906827

• The influence of music therapy on preoperative anxiety in pediatric oncology patients undergoing invasive procedures. F. Giordano; B. Zanchi; C. Rutigliano; F. De Leonardis; F. Esposito; N. Brienza; N. Santoro, The Arts in Psychotherapy, Volume 68, 101649,https://doi.org/10.1016/j.aip.2020.101649 , ISSN: 0197-4556, 2020.

• Orthogonal Joint Sparse NMF for Microarray Data Analysis, N. Del Buono, F. Esposito, N. Gillis, Journal of Mathematical Biology, 79: 223. https://doi.org/10.1007/s00285-019-01355-2 ISSN: 0303-6812, 2019

• Improving knowledge on the activation of bone marrow fibroblasts in MGUS and MM disease through the automatic extraction of genes via a Nonnegative Matrix Factorization approach on gene expression profiles, A. Boccarelli, F. Esposito, N. Del Buono, A. Vacca, M. Coluccia, Journal of Translational Medicine Journal of translational medicine, 16(1):217https://doi.org/10.1186/s12967-018-1589-1 , ISSN: 1479-5876, 2018.

Book Chapter

• Improving Color Image Binary Segmentation Using Nonnegative Matrix Factorization. C Castiello, N Del Buono, F Esposito, International Conference on Computational Science and Its Applications, 623-640, 2023

• Detecting Anomalies in Marine Data: A Framework for Time Series Analysis. N Del Buono, F Esposito, G Gargano, L Selicato, N Taggio, G Ceriola, LOD 2022 (7th International Conference on machine Learning, Optimization and Data science),2022

• Machine Learning Approaches for Predicting Crystal Systems: A Brief Review and a Case Study. G Settembre, N Corriero, N Del Buono, F Esposito, R Rizzi, LOD 2022 (7th International Conference on machine Learning, Optimization and Data science),2022

• Toward a New Approach for Tuning Regularization Hyperparameter in NMF, Del Buono N., Esposito F., Selicato L. In: Nicosia G. et al. (eds) Machine Learning, Optimization, and Data Science. LOD 2021. Lecture Notes in Computer Science, vol 13163. Springer, Cham. https://doi.org/10.1007/978-3-030-95467-3_36

• Methods for Hyperparameters Optimization in Learning Approaches: an overview, N. Del Buono, F. Esposito and L. Selicato, International Conference on Machine Learning, Optimization, and Data Science LOD2020, LNCS, 2020,

• Investigating initialization techniques for Nonnegative Matrix Factorization: a survey and a case of study of microarrays,  N. Del Buono e F. Esposito, Series in Applied Sciences: Volume 2. Mathematical Modelling, Numerical and Data Analysis, ISBN 978-88-3369-044-5, 2019.

• On some practical issues related to Nonnegative Matrix Factorization in Microarray Data Analysis context, N. Del Buono and F. Esposito, Series in Applied Sciences: Volume 1. Mathematical Modelling, Numerical and Data Analysis, pag 109-130, ISBN 978-88-3369-044-5 ,doi: 10.17605/OSF.IO/KR2J3 , 2018

• Q-matrix Extraction from Real Response Data Using Nonnegative Matrix Factorizations, G. Casalino, C. Castiello, N. Del Buono, F. Esposito, C. Mencar, O. Gervasi et al. (Eds.): ICCSA 2017, Part I, LNCS 10404,  2017,DOI: 10.1007/978-3-319-62392-4_15 , ISSN: 0302-9743, 2017

• Breast cancer’s microarray data: pattern discovery using Nonnegative Matrix Factorizations, N. Del Buono, F. Esposito, F. Fumarola, A. Boccarelli, and M. Coluccia, LCNS, Second International Workshop on Machine learning, Optimization and big Data - MOD 2016 , Editors: G. Giuffrida, G.Nicosia, P.Pardalos, LNCS, 10122, Springer,DOI: 10.1007/978-3-319-51469-7_24  ISSN: 0302-9743, 2016

Conference Proceedings

• Low rank approaches for the analysis of real data from pre to post processing. Esposito F., Selicato L., Del Buono N., PROCEEDINGS OF SIMAI 2020+ 21 (2021).

• Anomalies detection in gene expression matrices: Towards a new approach. Del Buono N., Esposito F., Selicato L., Vegliante MC. 12th International Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2021-Part of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2021. SciTePress, 2021.

• Nonnegative Matrix Factorization models for knowledge extraction from biomedical and other real world data, F. Esposito, N. Del Buono, and L. Selicato, PAMM 20.1 (2021): e202000032.

• A. Scarcelli, R. Borzone, F. Esposito, P. Camassa, M. Di Gioia, C. Marzocca, M. Rizzi, M. Terlizzi, A. Amato, A. Giove, R. Dario, M. Popolizio, T. Politi, V. Di Lecce, M. Ricci, (2020), RADON Project: From Children’s Game to Intelligent Personal Dosimeter, 2020 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT)

Thesis

• Nonnegative Matrix Factorizations for Knowledge Extraction from Biomedical and other real world data. F. Esposito, Department of Computer Science, University of Bari Aldo Moro, Italy PhD thesis, 2019

• 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);

• Fondamenti di Matematica per l'Analisi dei Dati, CdL Magistrale Bioinformatica (AY 2022-2023);

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

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

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