
Ph.D. candidate in Ingegneria Informatica E Dei Sistemi , 38th cycle (2022-2025)
Department of Control and Computer Engineering (DAUIN)
Profile
PhD
Research topic
New computational paradigms for neuromorphic hardware
Tutors
Research presentation
Research interests
Biography
My primary objective is to develop computational frameworks that facilitate the integration of neuromorphic tools with conventional hardware. In order to achieve this objective, a series of simple neuromorphic models (SNMs) have been developed, designed to perform a range of general-purpose tasks in a manner compatible with neuromorphic hardware. These models have been applied to a variety of applications, including audio processing, optimisation problems, benchmarking, and computer vision.
Throughout my research, I engaged in close collaboration with the teams at SmartData, Politecnico di Torino and Telluride Neuromorphic Cognition Engineering with the objective of developing innovative techniques in the field of neuromorphics. This was achieved by employing insights derived from the study of biological systems to develop real-world applications, while simultaneously leveraging cutting-edge hardware and software technologies.
This experience has significantly enhanced my technical proficiency in computational analysis and reinforced my commitment to the application of neuromorphic technologies.
Teaching
Teachings
Bachelor of Science
- Informatica. A.A. 2023/24, INGEGNERIA AEROSPAZIALE. Collaboratore del corso
Research
Research groups
Publications
Latest publications View all publications in Porto@Iris
- Pignari, Riccardo; Fra, Vittorio; Macii, Enrico; Urgese, Gianvito (In stampa)
Exploring Spiking Neuron Model behaviours through the Analysis of Parameter Space. In: ECML PKDD 2024 - "Deep Learning meets Neuromorphic Hardware" workshop, Vilnius, 09/09/2024 - 14/09/2024. ISSN 1865-0929
Contributo in Atti di Convegno (Proceeding) - Pignari, Riccardo; Fra, Vittorio; Urgese, Gianvito; Knight, James C.; D'Angelo, Giulia (2025)
Spiking motion direction through object motion sensitivity. In: 2025 IEEE International Conference on Development and Learning (ICDL) Prague, Prague (CZ), 16/09/2025
Contributo in Atti di Convegno (Proceeding) - Forno, Evelina; Pignari, Riccardo; Fra, Vittorio; Macii, Enrico; Urgese, Gianvito (2025)
Path Integral Quantum Annealing Optimizations Validated on 0-1 Multidimensional Knapsack Problem. In: IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING. ISSN 2168-6750
Contributo su Rivista - Xiao, Zhili; Akl, Mahmoud; Leugring, Johannes; Olajide, Omowuyi; Malik, Adil; Dennler, ... (2025)
ON-OFF neuromorphic ISING machines using Fowler-Nordheim annealers. In: NATURE COMMUNICATIONS, vol. 16, pp. 1-13. ISSN 2041-1723
Contributo su Rivista - Pignari, Riccardo; Fra, Vittorio; Macii, Enrico; Urgese, Gianvito (2023)
Constraint Satisfaction Problems solution through Spiking Neural Networks with improved reliability: the case of Sudoku puzzles. In: 9th SmartData@PoliTO Workshop – SmartData@PoliTO meets AI-H@PoliTO, Loano (IT), 24/09/2023-26/09/2023
Contributo in Atti di Convegno (Proceeding)