Francesco Daghero

Francesco Daghero serves as a Research Fellow at the Interuniversity Department of Territorial Sciences, Planning and Policies (DIST) of the Polytechnic University of Turin, maintaining active teaching roles across multiple engineering disciplines. His institutional email (francesco.daghero@polito.it) confirms primary affiliation with Politecnico di Torino, where he has collaborated on:

• Master's Degree Course in Operating Systems for Embedded Systems (2021/22, Computer Engineering)
• Computer Science courses in Management Engineering (2023/24, 2022/23)
• Computer Science courses in Aerospace Engineering (2021/22, 2020/21)

His research bridges computer and electrical engineering through machine learning applications in semiconductor design and hardware optimization. Core focus areas include:

• Embedded systems and edge computing architectures
• ML-driven VLSI layout prediction and feasibility analysis
• Deep learning acceleration for ultra-low-power devices
• Compiler techniques for heterogeneous edge hardware

Analysis of his 2024-2025 publications reveals a cohesive research trajectory targeting hardware-software co-design challenges. Key trends include applying ML to analog-digital integration problems, optimizing convolution operations for resource-constrained environments, and developing gradient-aware IC matching algorithms—demonstrating significant contributions to semiconductor manufacturing and efficient AI deployment.

Scientific awards: No honors, fellowships, or medals were documented in source materials.

Advising and grants: The provided texts contain no information regarding student supervision, research funding, or grant acquisition activities.