Andrea Ceschini was born in 1996. He received his Management Engineering degree (M.Sc.) with Honors from the University of Rome “La Sapienza” (Italy), in 2020. In the same year, he obtained the Professional Engineer Qualification. Currently, he is studying for the Ph.D. degree in Information and Communications Technologies from the same university. He is performing his research at the Dept. of Information Engineering, Electronics and Telecommunications (DIET). His research interests include Quantum Machine Learning algorithms on Noisy Intermediate-Scale Quantum (NISQ) devices, Machine Learning techniques for prediction of energy time series, neural circuit models and systems, signal processing algorithms on big data. His ongoing activities concern the development of novel quantum and quantum-inspired Neural Networks for time series modelling, Quantum Transfer Learning as well as the implementation of hybrid quantum-classical Deep Learning models in the energy and remote sensing domains
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