Current students

The research project aims to investigate emerging technologies such as artificial intelligence and quantum computing to address valuable industrial telecommunication problems and align the two technologies. I compare artificial intelligence methods for controlling typical telecommunication systems, such as high power amplifiers characterized by a complex parameter space, whose deviations from the optimal setting require continuous adjustments. Specifically, I exploit machine learning methods, such as online learning and deep learning techniques. Then, I address the diagnostics of network data by comparing artificial intelligence and monitoring methods, with particular attention for anomaly detections. I prepare the physical and virtual background to embed anomaly detection algorithms on a quantum computer so to host a network data problem. In such context, I exploit artificial intelligence methods, with particular emphasis on recent reinforcement learning algorithms, to ease and optimize the quantum computation and assess the alignment of the two technologies. Addressing typical quantum compiling fundamental problems by artificial intelligence methods, such as the compilation of circuits on gate model quantum computers and embedding on adiabatic quantum computers, could enable the exploiting of quantum computation on a larger class of use-case scenarios. Finally, I adapt the most promising network anomaly problem to a quantum computer by combining the findings of the previous years.