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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.

Teaching

  • A.A. 2022-2023, Lab. Sessions Course: Biomedical Signal Processing, ESAT, KU Leuven
  • A.A. 2023-2024, Lab. Sessions Course: Biomedical Signal Processing, ESAT, KU Leuven