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If you are working on generative AI with an information theoretic approach, you may be interested in taking a look at our recent work on: Mutual information estimation – NeurIPS 2024 [...]

I am happy to deliver a tutorial on Statistical Learning with Generative Models for Communications at IEEE ICC 2023 on June 1st, 2023. Machine learning is gaining more and more interest in [...]

Optimal data detection and decoding in known channels is a well studied topic whose solution is given by the maximum a posteriori probability (MAP) criterion, which is optimal in a minimum error [...]

Learning the statistics of physical phenomena has been a long-time research objective. The advent of machine learning methods has offered effective tools to tackle such an objective in several [...]

Very honored to have received the Best Paper Award at IEEE ISPLC 2021 together with Nunzio Letizia. Very encouraging to keep working on novel neural channel capacity estimators and capacity [...]

The channel capacity ! Any engineer or scientist working on communication technology is fascinated by the challenge of designing technology that allows to reliably send information at the maximum [...]

Tremendous progress has been made in the development of generative networks that are capable of mimicking real data. The most exemplary approach is represented by GANs that have shown to work [...]

  How will we communicate in the future ? I shared some thoughts in a recent interview for Ad Astra – The magazine for science and culture of the University of Klagenfurt. You can read [...]

I was awarded the Chair of Excellence 2019-20 at Universidad Carlos III Madrid, Spain, and given the opportunity to cooperate in the domain of connectivity and signal processing for smart [...]

Unmanned aerial vehicles (UAVs), referred also as to drones, find application in many fields. In my recent keynote at the IEEE Intellect 2019 Conference, I gave an overview of key applications [...]