Curriculum
Danilo Comminiello received the M.Sc. degree in Telecommunication Engineering in 2008 from Sapienza University of Rome, Italy. From 2007 to 2008, he was an Intern Service Engineer at Ericsson Telecomunicazioni S.P.A. in Rome, with the Radio Access Network area. In 2008 he undertook the Ph.D. degree in Information and Communication Engineering, accomplished in 2012, with the Department of Information Engineering, Electronics and Telecommunications (DIET) at Sapienza University of Rome, Italy. During his doctoral and post-doctoral studies, he has collaborated on various research projects with several Italian and foreign companies, some of which, including Fondazione Ugo Bordoni, have contributed to the funding of his studies through research grants. In 2010/2011, he was a Visiting PhD Student with the Department of Signals Theory and Communications of the Universidad Carlos III de Madrid, Spain, under the supervision of Prof. Jerónimo Arenas-García. From 2012 to 2016, after receiving the PhD degree, he was a Postdoctoral Research Fellow with the DIET at Sapienza University of Rome, Italy. During this period, he has given several seminar lectures and exercises for the following courses: “Digital Audio Signal Processing”, “Circuits and Algorithms for Signal Processing”, “Adaptive Algorithms and Parallel Computing” and “Neural Networks”.
From November 2016 to November 2019, Danilo Comminiello was a Tenure-Track Assistant Professor, and since November 2019 he is an Associate Professor with the Department of Information Engineering, Electronics and Telecommunications (DIET) of Sapienza University of Rome, where he teaches "Circuit Theory" (B.Sc. in Communications Engineering), "Machine Learning for Signal Processing" (M.Sc. in Electronic Engineering), "Neural Networks" (M.Sc. in Artificial Intelligence and Robotics, co-teaching with Prof. Simone Scardapane), "Generative Deep Learning" (PhD Program in Information and Communication Technology). He is a member of the research group of Intelligent Signal Processing and MultiMedia (ISPAMM) with the DIET.
His research interests concern the design and analysis of modern artificial intelligence and machine learning algorithms. In particular, Danilo Comminiello is active in the research on innovative learning methods, which are able to process data autonomously by exploiting the information driven by data. Such methodologies include neural networks, deep learning methods, deep generative models, adaptive algorithms and nonlinear filters, among others.
Danilo Comminiello is the recipient of the Outstanding Reviewer Award for maintaining the prestige of the 44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK, May 2019. He received the Best Manuscript Award at the IEEE International Symposium on Circuits and Systems (ISCAS), Austin, TX, 2022. He was also the recipient of the Franco Ferrero Award for the best article published in the proceedings of the AISV (Italian Association of Voice Sciences) Conference for two consecutive years in 2012 and 2013. He was also the recipient of the award for the "I Concorso Regionale per Tesi di Laurea e di Dottorato Riservato ai Laureati Lucani 2017" for the Best Doctoral Thesis obtained in the years 2007-2012 by students from Basilicata region.
Danilo Comminiello is a Senior Member of the "Institute of Electrical and Electronics Engineers" (IEEE), and a Member of the "Audio Engineering Society" (AES), of the "European Association for Signal Processing" (EURASIP), of the "International Neural Network Society" (INNS), of the "International Speech Communication Association" (ISCA), and of the "Italian Society of Neuronal Networks" (SIREN).
He is an elected Member and Vice-Chair of the IEEE Machine Learning for Signal Processing Technical Committee of the IEEE Signal Processing Society, Member of the IEEE Nonlinear Circuits and Systems Technical Committee of the IEEE Circuits and Systems Society. Danilo Comminiello is the Chair of the Task Force on Computational Audio Processing of the IEEE Computational Intelligence Society. He was also an elected Member of the Board of Directors of the Italian Section of the Audio Engineering Society (AES) for the years 2018-2020.
Danilo Comminiello is one of the editors of the book Adaptive Learning Methods for Nonlinear Modeling (D. Comminiello and J. C. Principe, eds.), Elsevier, 2018.
He serves as an Area Editor for IEEE Signal Processing Magazine and as an Associate Editor for IEEE Transactions on Neural Networks and Learning Systems. He has also served as an Associate Editor for IEEE Transactions on Circuits and Systems, I: Regular Papers, for Elsevier Digital Signal Processing and for Hindawi Complexity. Since 2009, he has served as a reviewer for the most important international journals and conferences in the areas of signal processing, circuits & systems and machine learning.
He has served as an Area Chair for "IEEE International Conference on Acoustics, Speech and Signal Processing" (ICASSP) and as a Technical Program Committee Member, Session Chair and Special Session Organizer for several international conferences, including: ICASSP, IJCNN, MLSP, EUSIPCO. He is also the organizer of the L3DAS Challenges series.
Danilo Comminiello is the General Chair of the "33rd IEEE International Workshop on Machine Learning for Signal Processing" (MLSP 2023), 17-20 September 2023 in Rome, Italy. He is also the General Chair of the "2025 INNS International Joint Conference on Neural Networks" (IJCNN 2025), 30 June - 5 July 2025, Rome, Italy.