About
I come from a pretty small village in the south of Italy. Since I was a kid, I have been interested in science and computers.
I moved to Torino for my studies. Here I did my Ph.D. in electronics engineering, under the supervision of Professor Luciano Lavagno and Professor Mario R. Casu, working on high level synthesis of digital circuits and deep learning acceleration on FPGAs.
Now I am working as GPUAI compiler engineer at Qualcomm.
I have two beautiful cats, Artù and Merlino. I love them. A lot.
My main areas of interest are:
- deep learning.
- computer architecture.
- compilers.
- programming languages.
- computer science (still trying to finish a proper algorithms and data structures course since 2020).
Career
- Staff GPUAI Engineer, Qualcomm, Mar 2026 - ongoing.
- Senior AI/ML Processor Architect, NXP, Apr 2025 - Feb 2026.
- Senior AI/ML Processor Engineer, NXP, Oct 2024 - Apr 2025.
- AI/ML Processor Engineer, NXP, Jan 2024 - Oct 2024.
- Ph.D. in Electrical, Electronic and Telecommunications Engineering,
Politecnico di Torino, Nov 2020 - Dec 2023.
- Visiting researcher in Charlotte Frenkel’s laboratory, Feb 2023 - Sep 2023.
- Master of Science in Electronic Engineering, Microelectronics, Politecnico di Torino, 2017-2020. Grade: 110/110, Summa Cum Laude.
- Bachelor of Science in Electronic Engineering, Politecnico di Torino, 2014-2017. Grade: 108/110.
Publications
2025
- The neurobench framework for benchmarking neuromorphic computing algorithms and systems, Yik et al., Nature Communications, 16, 1545.
- SILVIA: Automated Superword-Level Parallelism Exploitation via HLS-specific LLVM Passes for Compute-Intensive FPGA Accelerators, Giovanni Brignone, Roberto Bosio, Fabrizio Ottati, Claudio Sansoè, and Luciano Lavagno, ACM Transactions on Reconfigurable Technology and Systems, 18(2).
- eIQ Neutron: Redefining Edge-AI Inference with Integrated NPU and Compiler Innovations, Lennart Bamberg, Filippo Minnella, Roberto Bosio, Fabrizio Ottati, Yuebin Wang, Jongmin Lee, Luciano Lavagno, and Adam Fuks (arXiv preprint).
2023
- To Spike or Not To Spike: A Digital Hardware Perspective on Deep Learning Acceleration, Fabrizio Ottati, Chang Gao, Qinyu Chen, Giovanni Brignone, Mario R. Casu, Jason K. Eshraghian, and Luciano Lavagno, IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 13(4), 1015–1025.
Credits
The ONM logo has been designed by Gregor Lenz for the Open Neuromorphic organisation.