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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 [...]

Some years ago a novel filter bank modulation technique was conceived: Cyclic Filter Bank Modulation (CB-FMT) [1]-[2]. The main principles, efficient realization and equalization in double [...]

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 [...]

Path planning is a fundamental component for the control of autonomous vehicles (AVs), e.g., for unmanned aerial vehicles (UAVs). There exist a plethora of path planning methodologies, each [...]

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 [...]

Realizing Motus Perpetuus has struggled scientists for centuries who strived to build ideal no-energy loss mechanisms. I’d like to mention Foucault’s pendulum that was used to prove [...]

We are pursuing a research endeavor starting from scratch: design, control, and prototyping of new unmanned aerial vehicles. In my team, we are working in this new fascinating domain, mixing [...]