Matteo Risso

Dottorando in Ingegneria Informatica E Dei Sistemi , 37o ciclo (2021-2024)
Dipartimento di Automatica e Informatica (DAUIN)

Docente esterno e/o collaboratore didattico
Dipartimento di Automatica e Informatica (DAUIN)


Dottorato di ricerca

Argomento di ricerca

Automatic hardware-aware design and optimization of deep learning models


Presentazione della ricerca


Interessi di ricerca

Controls and system engineering
Data science, Computer vision and AI
Life sciences


I hold a Bachelor's degree in Physical Engineering and a Master's degree in Electronic Engineering from Politecnico di Torino in Italy, awarded in 2018 and 2020, respectively. Currently, I am immersed in my Ph.D. journey, specializing in Computer Engineering at the same institution.
My academic journey has always been fueled by a relentless curiosity and a passion for technology. I am deeply fascinated by Machine Learning and Deep Learning, and I thrive on the challenges of Design Automation and the intricacies of building Energy-Efficient Embedded Systems. I believe that these fields hold the keys to shape a smarter and better world for everyone, where technology goes hand in hand with the good.
I like to define myself as a technology enthusiast, driven by a boundless curiosity and an insatiable hunger for knowledge. I always do my best to not only work hard but also work smart. I always strive to be a valuable team player, collaborating effectively to achieve shared goals.

Premi e riconoscimenti

  • Each month, TC selects a “Featured Paper of the Month” to highlight a new technological or theoretical breakthrough with potential for high impact in the field. All accepted TC papers are eligible for consideration by a selection committee. The highlighted paper is available free of charge for the month on TC’s homepage. Authors of featured papers are invited to provide supplemental multimedia contents in multiple languages to promote their ideas openly to a broad audience. (2023)



Corso di laurea magistrale

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Corso di laurea di 1° livello

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Gruppi di ricerca


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