Medicine & Biomedical Engineering Candidate | Armenise-Harvard Fellow
📍 Center for Genomic Medicine, Massachusetts General Hospital / Harvard Medical School & University of Pavia

I work at the interface of cellular physiology, computational genomics, and translational neurology, focusing on patient-derived human iPSC-neuron disease models, pre-mRNA alternative splicing, and evidence-structure synthesis.

• SYNAPTIK — Evidence-structure analysis and multi-class genomic reconciliation (literature mining, SpliceAI, gnomAD constraint, ClinVar, DepMap) for patient-derived iPSC-neuron research. Built to detect single-lab publication bias and resolve cross-layer contradictions before committing to wet-lab differentiation assays.
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• Biological Systems: Patient-derived human iPSC-derived neurons (NGN2 induction, dual-SMAD differentiation), synaptic phenotype assays (SYN1/PSD95 puncta quantification, mEPSC electrophysiology).
• Computational Genomics: Pre-mRNA alternative splicing, SpliceAI, nonsense-mediated decay (NMD), variant prioritization, CRISPR prime-editing pegRNA assay validation.
• Languages & Frameworks: Python, R, SQLite, Biopython, automated CI/CD testing.

Collaborations with wet labs and computational biologists working on human iPSC models, neurogenetics, and splicing are always welcome. Feel free to open an issue or start a discussion on SYNAPTIK!