Manca, E., Urbinati, L., Casu, M.R., "An End-to-End Flow to Deploy and Accelerate TinyML Mixed-Precision Models on RISC-V MCUs," in review process, doi: 10.36227/techrxiv.173161032.20267860/v1

Urbinati, L., "Accelerating Quantized DNNs with Dedicated Hardware Accelerators and RISC-V Processors Using Precision-Scalable Multipliers," Doctoral Thesis, Politecnico di Torino, 2024.

Manca, E., Urbinati, L., Casu, M.R., "STAR: Sum-Together/Apart Reconfigurable Multipliers for Precision-Scalable ML Workloads," 2024 Design, Automation & Test in Europe Conference & Exhibition (DATE), Valencia, Spain, 2024, pp. 1-6.

Urbinati, L., Casu, M.R., "High-Level Design of Precision-Scalable DNN Accelerators Based on Sum-Together Multipliers," in IEEE Access, vol. 12, pp. 44163-44189, 2024, doi: 10.1109/ACCESS.2024.3380472.

Štitić, B, Urbinati, L., Di Guglielmo, G., Carloni, L. and Casu, M.R., "Enhanced Machine-Learning Flow for Microwave-Sensing Systems for Contaminant Detection in Food," in IEEE Transactions on AgriFood Electronics, doi: 10.1109/TAFE.2024.3421238.

Štitić, B, Urbinati, L., Di Guglielmo, G., Carloni, L. and Casu, M.R., "Enhanced Machine-Learning Flow for Microwave-Sensing Systems to Detect Contaminants in Food," 2023 IEEE Conference on AgriFood Electronics (CAFE), Torino, Italy, 2023, pp. 40-44, doi: 10.1109/CAFE58535.2023.10291198.

Manca, E., Urbinati, L., Casu, M.R., "Accelerating Quantized DNN Layers on RISC-V with a STAR MAC Unit," Proceedings of SIE 2023. SIE 2023. Lecture Notes in Electrical Engineering, vol 1113. Springer, Cham. https://doi.org/10.1007/978-3-031-48711-8_6.

Urbinati, L., Casu, M.R., "Design-Space Exploration of Mixed-precision DNN Accelerators based on Sum-Together Multipliers," 2023 18th Conference on Ph.D Research in Microelectronics and Electronics (PRIME), Valencia, Spain, 2023, pp. 377-380, doi: 10.1109/PRIME58259.2023.10161835.

Urbinati, L., Casu, M.R., "A Reconfigurable Depth-Wise Convolution Module for Heterogeneously Quantized DNNs," 2022 IEEE International Symposium on Circuits and Systems (ISCAS), Austin, TX, USA, 2022, pp. 128-132, doi: 10.1109/ISCAS48785.2022.9937753.

Urbinati, L., Casu, M.R., "A Reconfigurable 2D-Convolution Accelerator for DNNs Quantized with Mixed-Precision," Applications in Electronics Pervading Industry, Environment and Society. ApplePies 2022. Lecture Notes in Electrical Engineering, vol 1036. Springer, Cham. https://doi.org/10.1007/978-3-031-30333-3_27.

Urbinati, L., Casu, M.R., "A Reconfigurable Multiplier/Dot-Product Unit for Precision-Scalable Deep Learning Applications," Proceedings of SIE 2022. SIE 2022. Lecture Notes in Electrical Engineering, vol 1005. Springer, Cham. https://doi.org/10.1007/978-3-031-26066-7_2.

Ricci, M. et al., "Machine-Learning-Based Microwave Sensing: A Case Study for the Food Industry," in IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 11, no. 3, pp. 503-514, Sept. 2021, doi: 10.1109/JETCAS.2021.3097699.

Urbinati, L., Ricci, M., Turvani, G., Vasquez, J.T., Vipiana, F. and Casu, M.R., "A Machine-Learning Based Microwave Sensing Approach to Food Contaminant Detection," 2020 IEEE International Symposium on Circuits and Systems (ISCAS), Seville, Spain, 2020, pp. 1-5, doi: 10.1109/ISCAS45731.2020.9181293.

Gnoli, L. et al., "Fault Tolerant Photovoltaic Array: A Repair Circuit Based on Memristor Sensing," 2019 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT), Noordwijk, Netherlands, 2019, pp. 1-4, doi: 10.1109/DFT.2019.8875467.

Urbinati, L., "Detection of food contaminants with Microwave Sensing and Machine Learning," Master's Thesis, Politecnico di Torino, 2019.

Urbinati, L., "Progetto di un circuito di interfaccia basato su tecnologia NFC per nodi sensori a bassissimo consumo," Bachelor's Thesis, Università di Bologna, 2017.