Danilo Comminiello is an Associate Professor at Sapienza University of Rome, where he is part of the ISPAMM Lab. His research focuses on machine learning and neural networks, with emphasis on generative models, adaptive systems, and hypercomplex representations. He has published over 150 works in leading venues (Neural Networks, TNNLS, TSP, TASLP, IJCNN, ICASSP, ICLR) and coedited the book Adaptive Learning Methods for Nonlinear System Modeling. He has served as General Chair of IJCNN 2025 in Rome and as Chair of the IEEE SPS MLSP Technical Committee. His work bridges neural network theory and applications in audio, biomedicine, and signal processing, advancing INNS's mission of fostering neural network science and innovation. |
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