Francesco Manigrasso

PhD Student in Ingegneria Informatica E Dei Sistemi , 36th cycle (2020-2023)
Department of Control and Computer Engineering (DAUIN)

Docente esterno e/o collaboratore didattico
Department of Control and Computer Engineering (DAUIN)



Research topic

Robust machine learning models for high dimensional data interpretation


Research interests

Machine Learning
Artificial intelligence


The integration of symbolic knowledge representation and learning has the potential to improve traditional deep learning models adding capabilities in terms of inference, reasoning, and representation of high-level concepts. The present research proposal concerns techniques that incorporate deep learning and statistical relational learning (neuro-symbolic models) for the interpretation of multi-dimensional data, such as images.

By allowing the incorporation of prior knowledge in the training process, neuro-symbolic applications can enhance multiple image analysis tasks in various real-life scenarios. The additional possibility to represent the model uncertainty is particularly relevant when coping with limited training data.

Starting from different computer vision tasks like image classification, the research aims at comparing the neural-symbolic architectures with traditional convolutional neural network in terms of accuracy, generalizability, and interpretability.

Awards and Honors

  • PhD Quality Awards 2023 (2023)



Master of Science

MostraNascondi A.A. passati

Bachelor of Science

  • Informatica. A.A. 2021/22, INGEGNERIA AEROSPAZIALE. Collaboratore del corso
  • Informatica. A.A. 2022/23, INGEGNERIA INFORMATICA. Collaboratore del corso
MostraNascondi A.A. passati


Latest publications View all publications in Porto@Iris