Nicolò Bellarmino is a Researcher at the Department of Control and Computer Science (DAUIN), Politecnico di Torino, where he also serves as an External Lecturer and Teaching Assistant. His work is centered on machine learning applications in electronic design automation, particularly in microcontroller performance screening and reliability assessment of deep learning hardware. His research interests include machine learning for embedded systems, feature selection, neural network testing, and reliability engineering. He employs techniques such as evolutionary algorithms, transfer learning, and fault injection to develop efficient and robust methodologies for semiconductor testing and DNN accelerator validation. The recent publications highlight a strong focus on data-efficient and automated approaches for performance prediction and reliability assessment, leveraging foundation models, unsupervised learning, and hierarchical modeling. These works span journals and top-tier conferences in computer-aided design, electronics, and machine learning. He has no listed scientific awards in the provided text. Bellarmino actively contributes to teaching in the Computer Engineering and Aerospace Engineering programs, collaborating on courses such as Systems Programming, System and Device Programming, and Future of Work. He is a member of the CAD - Electronic CAD & Reliability Group (DAUIN), contributing to cutting-edge research in EDA and hardware reliability. No grants or advising roles are mentioned.
