As a PhD student at IEO (Pier Giuseppe Pelicci Lab) I have the opportunity to lead different projects in the cancer evolution and single-cell lineage tracing field. During this period, I gained extensive knowledge of single-cell and multi-omics analysis frameworks working as data and ML engineer, developer (R, python, Nextflow) and data analyst. The results of this work were published in impactful scientific journals and/or presented at international conferences/workshops. My duties included grant writing, collaboration with external groups and the the supervision of other junior analysts and thesists.

During my MS Internship in Daniela Besozzi Group, I applied different statistical and mathematical modeling approaches to explore T-cell Acute Lymohoblastic Leukaemia (T-ALL) inter-and intra-patient heterogeneity. In particular, we leveraged a 12 patients, 8 million cells, 45-immune related protein markers mass cytometry dataset to characterize cell states associated with different chemo-therapy responses to the inhibition of Gluco-corticoid Receptor. Then, we derived a fuzzy-logic based simulator of the gene-gene interactions underlying this response to generate novel hypothesis for combinatorial therapy.

During my BSc Intership in the Angelo Poletti Lab, I had the opportunity to master the Inducted Pluripotents Stem Cell (iPS) technology for Amyotrophic Lateral Sclerosis (ALS) disease modeling and drug reporpusing. Specifically, we tested the pharmacological effect of colchicine (a trascriptional inducer of the HSPB8 chaperone, a key component of chaperone-mediated autophagy) on iPS-derived motor-neurons, refining previously published results of the lab.