In 2020, she earned her Bachelor’s degree in Computer Engineering from the University of Florence, discussing a thesis entitled “PRNU-based source identification in the era of computational photography”. In this work she analyzed photos taken by various latest generation smartphones, studying the differences and problems related to the use of PRNU for source identification in this context.

In 2021, she received a Research fellowship at the CSP Lab (Communications and Signal Processing) of the University of Florence. The title of the project was: “Development of image forensic techniques for the detection of toolchains”. The study was included within the research project UNCHAINED (Uncovering media manipulation chains through container and content detectable traces), which was carried out in collaboration with the Defence Advanced Research Projects Agency (DARPA).

Continuing her academic journey, she completed her Master’s degree in Computer Engineering at the University of Florence in 2023, with a thesis entitled “Cone Beam Computed Tomography ChArUco-Based Motion Compensation from Optical Frames”. The thesis consisted on the analysis and development of a workflow for the compensation of motion artifacts in CBCT images. The project was carried out in collaboration with the company Imaginalis S.r.l., as part of an apprenticeship period.

Since November 2023, she has been pursuing a PhD in Smart Computing at the University of Florence. Her research activity is centered on applying deep learning models to address quality issues in medical imaging, with a specific focus on developing explainable decision support systems.

Publications

• Lorenzo Berlincioni, Luca Cultrera, Chiara Albisani, Lisa Cresti, Andrea Leonardo, Sara Picchioni, Federico Becattini, and Alberto Del Bimbo, "Neuromorphic Event-based Facial Expression Recognition.", IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) - Workshops, 2023
• Chiara Albisani, Massimo Iuliani, and Alessandro Piva, "Checking PRNU Usability on Modern Devices.", IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021