Dottorando in Ingegneria Informatica E Dei Sistemi , 37o ciclo (2021-2024)
Dipartimento di Automatica e Informatica (DAUIN)
Assegnista di Ricerca
Dipartimento Interateneo di Scienze, Progetto e Politiche del Territorio (DIST)
Docente esterno e/o collaboratore didattico
Dipartimento di Automatica e Informatica (DAUIN)
Profilo
Dottorato di ricerca
Argomento di ricerca
Automatic hardware-aware design and optimization of deep learning models
Tutori
Presentazione della ricerca
Interessi di ricerca
Biografia
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
- Form to collect the information relevant for the PhD Quality Awards (2024)
- PhD quality award at DATE 2024 PhD Forum https://date24.date-conference.com/awards (2024)
- Best Paper Award for the “Application” track achieved at DATE 2024 conference https://date24.date-conference.com/awards (2024)
- 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)
Didattica
Insegnamenti
Corso di laurea magistrale
- Energy management for IoT. A.A. 2024/25, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso
- Energy management for IoT. A.A. 2023/24, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso
- Energy management for IoT. A.A. 2022/23, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso
Corso di laurea di 1° livello
- Tecniche di programmazione. A.A. 2022/23, INGEGNERIA INFORMATICA. Collaboratore del corso
Pubblicazioni
Pubblicazioni più recenti Vedi tutte le pubblicazioni su Porto@Iris
- Risso, Matteo; Daghero, Francesco; Motetti, BEATRICE ALESSANDRA; JAHIER PAGLIARI, ... (In stampa)
Optimized Deployment of Deep Neural Networks for Visual Pose Estimation on Nano-drones. In: ERF 2024 | European Robotics Forum, Rimini (IT), March, 13 - 15, 2024
Contributo in Atti di Convegno (Proceeding) - Motetti, Beatrice Alessandra; Crupi, Luca; Elshaigi, Mustafa Omer Mohammed Elamin; ... (2024)
Adaptive Deep Learning for Efficient Visual Pose Estimation Aboard Ultra-Low-Power Nano-Drones. In: Design, Automation and Test in Europe Conference, 2024, Valencia (ESP), 25-27 March 2024, pp. 1-6. ISSN 1530-1591. ISBN: 978-3-9819263-8-5
Contributo in Atti di Convegno (Proceeding) - Risso, M.; Xie, C.; Daghero, F.; Burrello, A.; Mollaei, S.; Castellano, M.; Macii, E.; ... (2024)
HW-SW Optimization of DNNs for Privacy-Preserving People Counting on Low-Resolution Infrared Arrays. In: Design, Automation and Test in Europe Conference and Exhibition, DATE 2024, Valencia (ESP), 25-27 March 2024, pp. 1-6. ISSN 1530-1591. ISBN: 978-3-9819263-8-5
Contributo in Atti di Convegno (Proceeding) - Aliffi, G. E.; Baixinho, J.; Barri, D.; Daghero, F.; Di Carolo, N.; Faraone, G.; Grosso, ... (2024)
AMBEATion: Analog Mixed-Signal Back-End Design Automation with Machine Learning and Artificial Intelligence Techniques. In: Design, Automation and Test in Europe Conference and Exhibition, DATE 2024, Valencia (ESP), 25-27 March 2024, pp. 1-6. ISSN 1530-1591. ISBN: 978-3-9819263-8-5
Contributo in Atti di Convegno (Proceeding) - Motetti, Beatrice Alessandra; Risso, Matteo; Burrello, Alessio; Macii, Enrico; Poncino, ... (2024)
Joint Pruning and Channel-wise Mixed-Precision Quantization for Efficient Deep Neural Networks. In: IEEE TRANSACTIONS ON COMPUTERS, vol. 73, pp. 2619-2633. ISSN 0018-9340
Contributo su Rivista