Danilo Comminiello

Department of Information Engineering, Electronics and Telecommunications (DIET)
Sapienza University of Rome

Via Eudossiana n°18, 00184 Rome
Building B (RM032), Floor 1, Room 116

Tel.: 0644585816 (int. 25816)
E-mail: danilo.comminiello@uniroma1.it
Office hours: by appointment

Danilo Comminiello is an Associate Professor with the Department of Information Engineering, Electronics and Telecommunications (DIET) of Sapienza University of Rome, Italy.

His research interests concern circuits and algorithms for machine learning and artificial intelligence, with particular focus on audio, acoustic and speech signal processing.

Danilo Comminiello is an IEEE Senior Member and an elected member of the IEEE Machine Learning for Signal Processing Technical Committee. He served as an Associate Editor for IEEE Transactions on Circuits and Systems I: Regular Papers and he is one of the editors of the book Adaptive Learning Methods for Nonlinear System Modeling (D. Comminiello and J. C. Principe, eds.), Elsevier 2018.

Latest News

Course: The course of GENERATIVE DEEP LEARNING will start on June 6, 2022!!! Attendance modality is hybrid in presence/remote. Please take a look at the course webpage and please register on the course Classroom with access code rg2mczw.

Special Event: I am co-organizing with Michele Scarpiniti, Jen-Tzung Chien and Konstantinos Drosos, a special session on "Audio and Speech Enhancement: Emerging Trends in Deep Learning" at the 2022 IEEE World Congress on Computational Intelligence (WCCI 2022), which will be held in Padua, Italy, on 18 - 23 July 2022. The strict deadline for paper submission is January 31, 2022.
Further information can be found in the following Call for Papers.

Special Event: The L3DAS Team and I are glad to announce the 2nd edition of the L3DAS CHALLENGE on Machine Learning for 3D Audio Signal Processing at IEEE ICASSP2022 🤯🤩🎧

Further details on tasks, datasets, instructions to participate, registration and awards can be found on the L3DAS website: www.l3das.com/icassp2022.

Award: The course of Generative Deep Learning, offered within the PhD Course in Information and Communication Technology (ICT), has been awarded the TensorFlow Faculty Award 2021.