My work as a Data Science Research Associate aims at designing and applying mathematical models of spatial metabolomics data (mass spectrometry imaging).Currently, I am responsible for data acquisition optimisation for DESI-MS imaging and the integration of multi-modal spatial data.
I have been awarded a pre-Bologna Laurea degree (eq. to MSc) in Physics (with specialisation in Theoretical Physics) at the Universita' Degli Studi di Bari, Italy. As member of Prof. Roberto Bellotti group, I have worked on applied machine learning for the automatic segmentation of the human hippocampus from structural MRI scans, as part of the Alzheimer's Disease research programme.
As a PhD student, under the supervision of Prof. Robert C Glen and Prof. Jeremy K. Nicholson, I have worked on robust signal processing pipelines for the pre-processing of DESI-MS imaging data, and the application of unsupervised learning techniques to understand the molecular heterogeneity of cancer.
I have continued my research work on DESI-MS imaging data in Prof. Zoltan Takats group. In particular, I have introduced a molecular colocalization approach for DESI-MS imaging data. During this period, I have also started designing and developing optimisation procedures aimed at integrating quality control and analytical references in DESI-MS imaging experiments, to quantify and disentangle the biological from the technical variability of the measured signals.
During 2020, I have worked at the Francis Crick Institute in Dr Paola Scaffidi lab, where I have applied unsupervised learning on scRNA-seq data to model the functional role of the epigenetic regulatory network in cancer resistance and plasticity.
et al., 2022, Mass recalibration for desorption electrospray ionization mass spectrometry imaging using endogenous reference ions, Bmc Bioinformatics, Vol:23, ISSN:1471-2105
et al., 2021, Holistic characterization of a salmonella typhimurium infection model using integrated molecular imaging., Journal of the American Society for Mass Spectrometry, Vol:32, ISSN:1044-0305, Pages:2791-2802
et al., 2021, Direct on-swab metabolic profiling of vaginal microbiome host interactions during pregnancy and preterm birth, Nature Communications, Vol:12, ISSN:2041-1723
et al., 2022, Rapid Assessment of Vaginal Microbiota Host Interactions During Pregnancy and Preterm Birth by Direct On-Swab Desorption Electrospray Ionization Mass Spectrometry, SPRINGER HEIDELBERG, Pages:53-53, ISSN:1933-7191