Vittorio Zampinetti

Vittorio Zampinetti's picture

Ph.D. candidate in Matematica Pura E Applicata , 37th cycle (2021-2024)
Department of Mathematical Sciences (DISMA)

Profile

PhD

Research topic

Statistical inference for tumor DNA sequencing data

Tutors

Research interests

Probability
Statistics

Biography

I develop machine learning methods and algorithms with a mathematical and statistical approach, and test their application to DNA sequencing data (both single-cell and bulk) from patients with cancer. My predominantly engineering background, with a focus on data science, merges with my passion for probabilistic models. This research involves the definition and analysis of Bayesian inference algorithms such as Variational Inference, as well as maximum likelihood methods (EM), which enable the reconstruction of cancer evolutionary trees from high-dimensional and inherently noisy data. Additionally, I develop efficient methods for sampling trees and generate synthetic data for testing implementations before the application on real data.

Teaching

Teachings

Master of Science

MostraNascondi A.A. passati