Danilo Comminiello is an Associate Professor with the Department of Information Engineering, Electronics and Telecommunications (DIET) of Sapienza University of Rome, Italy.
His research focuses on the development of advanced neural networks and machine learning methods, with particular emphasis on generative models, multimodal representation learning, and adaptive learning systems. These methodologies are applied across diverse domains, including audio and multimedia, medical imaging and biomedical data, and time series analysis.
Danilo Comminiello is the elected Chair of the IEEE Machine Learning for Signal Processing Technical Committee. He is also the Chair of the IEEE Task Force on Computational Audio Processing. Danilo Comminiello serves as an Area Editor for IEEE Signal Processing Magazine and Associate Editor for IEEE Transactions on Neural Networks and Learning Systems. 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 has served as General Chair of the 33rd IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2023), September 17-20, 2023, Rome, Italy, and of the INNS International Joint Conference on Neural Networks (IJCNN 2025), June 30 - July 5, 2025, Rome, Italy.