AURELIO UNCINI

Course: MACHINE LEARNING 2025 - Communications Engineering

Start Date: February 26, 2025
Class Schedule:

• Wednesday: 08:15 - 12:00, Room 20 (SPV)
• Thursday: 08:15 - 12:00, Room 20 (SPV)

Course: DEEP LEARNING - Communications Engineering

Start Date: February 26, 2025

Class Schedule:

• Tuesday: 16:00 - 19:00, Room 20 (SPV)
• Wednesday: 17:00 - 19:00, Room 20 (SPV)

Course: DIGITAL AUDIO SIGNAL PROCESSING (DASP) - Communications Engineering

Start Date: September 2025 
Class Schedule (TBC):

• Wednesday: 08:00 - 10:00
• Thursday: 08:00 - 12:00

Aurelio Uncini is Full Professor of Electrical and Computer Engineering at the Department of Information Engineering, Electronics and Telecommunications (DIET), Sapienza University of Rome, Italy.

He received the Laurea degree in Electronic Engineering from Marche Polytechnic University and the Ph.D. degree in Electrical Engineering from the University of Bologna. Before joining Sapienza University of Rome, he carried out research activities at the Italian National Research Council (CNR), the Ugo Bordoni Foundation, and Marche Polytechnic University. He has been Full Professor at Sapienza University since 2005.

His research and teaching activities focus on neural networks, machine learning, deep learning, artificial intelligence, adaptive signal processing, and audio and array processing. His scientific contributions include neural and nonlinear adaptive systems, blind signal processing, machine learning for signal processing, digital audio processing, and optimization methods for intelligent systems.

He has authored or co-authored more than 300 scientific publications, including several books and book chapters, covering neural networks, machine learning, signal processing, and artificial intelligence.

He has served on several national and international scientific and technical committees, including IEEE technical committees in machine learning and blind signal processing. He is a member of professional and scientific associations including the IEEE, the Audio Engineering Society (AES), and the International Neural Network Society (INNS).