Riccardo Pellini is a PhD student in Information Technology at the Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB) of Politecnico di Milano, under the supervision of Prof. Maurizio Ferrari Dacrema. His research is centered on advancing quantum algorithms by leveraging Machine Learning (ML) techniques for quantum circuits optimization and synthesis, aiming at improving both scalability and effectiveness of quantum algorithms. His main research topcis include:

• ML methods for quantum state preparation: benchmarking of ML-based algorithms and synthesis of quantum circuits for quantum state preparation, which is essential for practical applications of quantum computing.

• Representation Learning of quantum circuits: using GNNs to model and extract meaningful representations from quantum circuit structures, to have a deeper understanding of complex quantum systems.