Joined the Information Processing & Communications Lab, within the Intelligent Systems and Networks group, uder the supervision of Prof. Deniz Gunduz, where I do research on Reinforcement/Federated Learning and Information Theory.

Conducting research on machine learning and wireless communications with the SIGNET research group. I'm also involved in different projects on Intelligent Internet of Things and Deep Reinforcement Learning for information dissemination in vehicular's networks (with Toyota North America).

At InstaDeep, London (UK), I conducted research on Deep Reinforcement Learning, in particular on Maximum Entropy RL and on the Control as Inference framework. 

Conducting research on machine learning and wireless communications with the SIGNET research group. I'm also involved in different projects on Intelligent Internet of Things and Deep Reinforcement Learning for information dissemination in vehicular's networks (with Toyota North America).

Exchange program (1 year) at the Ecole Polytechnique Fédérale de Lausanne - EPFL, Lausanne (Switzerland), where I completed                master courses on Machine Learning, Information Theory, Graph and Distributed algorithms. 

I developed my master thesis in collaboration with Learn to Forecast, a machine learning startup located at the EPFL Innovation Park, Lausanne (Switzerland). By exlpoiting diffusion processes on graphs and simplicial complexes, I developed a novel method to embed nodes, edges and higher order cliques into low-dimensional spaces. 

Brand new master degree in ICT Engineering where I studied Wireless Communications and Networks, Machine Learning and Data Analysis, Stochastic Processes and Network Science. Graduated Summa cum Laude.

Completed theoretical courses on Mathematical Analysis, Linear Algebra, Physics, Probability and fundamentals of Computer Science, Electronics and Control Theory. For my bachelor thesis I studied stochastic models for DNA sequences analysis. Final mark 110/110.