Andrea Schiano di Colella

Personal Introduction

Andrea’s background is in physics. He studied in Italy at the University of Naples “Federico II”, where he obtained a BSc in Physics and a MSc in Theoretical physics. His research will focus on the development of deep learning based protocols for accurate autonomous microscopy.

Project Introduction

Development of a deep-learning-based toolbox tailored for microscopic images using the DeepTrack2 platform, as well as performing an effectively track the life cycle of various materials, monitor their transformations, and pinpoint their composition at different stages. To ensure that the developed tools are versatile enough for deployment in both research settings within the network and subsequent production environments, a robust set of neural network models (unsupervised, self-supervised, and supervised) capable of analysing microscopic images with high accuracy will be considered. Additionally, a comprehensive understanding of the life cycle of various materials, achieved by analysing their transformations and compositions at different stages.