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 a Full Professor of Electrical and Computer Engineering at the Department of Information Engineering, Electronics, and Telecommunications (DIET) at the University of Rome "La Sapienza," Italy. His research and teaching focus on Neural Networks, Machine Learning, Deep Learning, and AI for Signal Processing.

He obtained his Laurea degree in Electronic Engineering from Marche Polytechnic University in 1983 and later earned a Ph.D. in Electrical Engineering from the University of Bologna in 1994. His early research experience includes a visiting student position at the "Consiglio Nazionale delle Ricerche - Istituto O.M. Corbino" in Rome (1982-1983) on speech signal processing, and work at the "Ugo Bordoni" Foundation (1984-1986) on AI for continuous speech recognition and understanding. He was a researcher at the Department of Electronics and Automatics at Marche Polytechnic University from 1986 to 1993, later serving as an Assistant Professor (1994-1998). From 1999 to 2004, he was an Associate Professor at the INFOCOM Department of the University of Rome "La Sapienza," and since 2005, he has been a Full Professor at DIET.

Prof. Uncini has authored over 300 research papers in the fields of neural networks, deep learning, AI-driven signal processing, and optimization algorithms for circuit design. His current research focuses on advanced neural network architectures, non-linear adaptive filters, machine learning for signal processing, and AI-driven audio and array processing. His contributions to the field include innovations in blind signal processing, deep learning-based optimization techniques, and real-time adaptive systems for digital audio.

He is an active member of the global AI and signal processing community, serving as a committee member for the IEEE Machine Learning for Signal Processing Technical Committee (2000-2003), the IEEE Blind Signal Processing Technical Committee, and the Steering Committee of the Società Italiana Reti Neuroniche (SIREN). He is also affiliated with the Audio Engineering Society (AES), the IEEE, the International Neural Networks Society (INNS), and the Associazione Elettrotecnica ed Elettronica Italiana (AEI)