Research

Research Interests

Vito Paolo Pastore's research interests lie primarily in the fields of machine learning and computer vision. His work focuses on designing and implementing algorithms that apply machine learning to problems in computer vision and biological systems. This includes deep learning techniques for image classification, scene analysis, and image segmentation. Currently, his research is focused on learning with imperfect data, especially in the field of unsupervised learning, self-supervised learning, and model debiasing with applications to medical, biological data, and industrial research.

Funded Projects

Next Waterfront (2024) POR-FESR Liguria
VPP is PI for the University of Genova in the Next Waterfront project, with the objective to design a deep learning model for evaluating water quality by exploiting plankton acquisitions, camera videos, and sensors.