There are open positions for both Master’s and Bachelor’s students.

Available Topics

• Explainable Deep Learning Architectures modelling for physiological and behavioural data analysis (i.e EEG, ECG) in medical scenarios. Clike here for more info.

Master Degree

• G. Cancello Tortora, “Analyzing brain data for robust emotion recognition via conceptual decomposition based on autoencoder”, MS in Artificial Intelligence and Data Engineering, University of Pisa, a.y. 2022-23.
• F. Marabotto, “Explainable emotion recognition via a novel loss function based on informed contrastive learning”, MS in Artificial Intelligence and Data Engineering, University of Pisa, a.y. 2022-23.
• L. Turchetti, “Sleep stage recognition supported by instances-based explanation via contrastive learning”, MS in Artificial Intelligence and Data Engineering, University of Pisa, a.y. 2022-23.
• P. Calabrese, “Explainable Artificial Intelligence Approaches for Industrial Data Science”, MS in Artificial Intelligence and Data Engineering, University of Pisa, a.y. 2022-23.
• M. Martorana, A Novel Feature Importance Measure To Explain The Quality Level Prediction In - Smart Manufacturing, MS in Artificial Intelligence and Data Engineering, University of Pisa, a.y. 2021-22.
• N. Mota, “Concept-wise architecture with topology learning for explainable emotion classification” MS in Computer Engineering, a.y. 2021-22.
• F. Ritorti, Design and testing of a loss function for distance-based representation learning to recognize emotions via EEG data, MS in Artificial Intelligence and Data Engineering, a.y. 2021-22.