Department of Information Engineering, Electronics and Telecommunications (DIET)
Sapienza University of Rome
Via Eudossiana n°18, 00184 Rome, Italy
Building B (RM032), Floor 1, Room 116
Tel.: 0644585816 (int. 25816)
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 the design and analysis of modern artificial intelligence algorithms, including neural networks and machine learning methods, deep generative models, and adaptive learning systems, with application to several fields, from audio to images, from medical to sensor signals.
He is the principal investigator of the L3DAS Project (Learning 3D Audio Sources).
Danilo Comminiello is an IEEE Senior Member and an elected member of the IEEE Machine Learning for Signal Processing Technical Committee. He serves as an Associate Editor for IEEE Transactions on Neural Networks and Learning Systems 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.
Danilo Comminiello is the General Co-Chair of the 33rd IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2023), September 17-20, 2023, Rome, Italy.
Teaching: The beginning of the course of Machine Learning for Signal Processing 2022/2023 has been postponed to the 2nd of March 2023. Please look at the course webpage for further details.
Special Event: I am really thrilled and honored to announce that the 33rd IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2023) will be held in Rome, Italy, 17-20 September 2023. On behalf of the whole Organizing Committee, I would like to warmly invite you to participate in the IEEE MLSP 2023!
Please visit the website for all the information: https://2023.ieeemlsp.org.
Special Event: The L3DAS Team and I are glad to announce the 3rd edition of the L3DAS CHALLENGE on Learning 3D Audio Sources for Audio-Visual Extended Reality at IEEE ICASSP 2023 🤯🤩🎧
Further details on tasks, datasets, and instructions to participate can be found on the L3DAS website: www.l3das.com/icassp2023.