Luca Urbinati

Ph.D. candidate in Ingegneria Elettrica, Elettronica E Delle Comunicazioni , 36th cycle (2020-2023)
Department of Electronics and Telecommunications (DET)



Thesis title

Accelerating Quantized DNNs with Dedicated Hardware Accelerators and RISC-V Processors Using Precision-Scalable Multipliers

Research topic

Embedded Machine Learning


Research interests

Big Data, Machine Learning, Neural Networks and Data Science
VLSI theory, design and applications


Luca URBINATI reveived his M.Sc. Degree in Electronic Engineering in 2019 from the Politecnico di Torino.
He is a first year Ph.D. student in the Department of Electronics and Telecommunications (DET) at the same university, under the supervision of Prof. M. R. CASU.
His research activity is focused on implementing Artificial Intelligence (AI) algorithms in edge devices through an HW-SW co-design approach.
1) L. Urbinati, M. Ricci, G. Turvani, J. A. T. Vasquez, F. Vipiana and M. R. Casu, "A Machine-Learning Based Microwave Sensing Approach to Food Contaminant Detection," 2020 IEEE International Symposium on Circuits and Systems (ISCAS), Sevilla, 2020, pp. 1-5, doi: 10.1109/ISCAS45731.2020.9181293
2) L. Gnoli et al., "Fault Tolerant Photovoltaic Array: A Repair Circuit Based on Memristor Sensing," 2019 IEEE International Symposium on DFT, Noordwijk, Netherlands, 2019, pp. 1-4, doi: 10.1109/DFT.2019.8875467

Awards and Honors

  • Best Student Paper Award at 2023 Conference on AgriFood Electronics (CAFE) for the paper entitled "Enhanced Machine-Learning Flow for Microwave-Sensing Systems to Detect Contaminants in Food" for which I was a co-author. (2023)
  • Young Fellows Poster Presentation Award at 2020 Design automation conference (DAC) for one of the best students’ poster presentations as a 2-minutes elevator pitch. I was presenting my Master's Thesis work entitled: “Detection of food contaminants with Microwave Sensing and Machine Learning”. (2023)
  • GOLD LEAF award at 2023 International Conference on PhD Research in Microelectronics and Electronics (PRIME) for ranking among the top 10% of the best papers with my work entitled “Design-Space Exploration of Mixed-precision DNN Accelerators based on Sum-Together Multipliers”. (2023)



Master of Science

MostraNascondi A.A. passati


PoliTO co-authors

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