Co-design of algorithms and spike-based neuromorphic sensing & computing architectures in mixed-signal and emerging CMOS devices for edge AI.
A crucial aspect of my research focuses on developing novel microelectronic architectures (see Figure) that can support brain-inspired models of computations. Together with those, I am researching bioinspired sensing principles and event-based sensing, with event-based cameras and, very recently, I have been introducing the concept of event-based radars. Event-based sensing solves the problem of redundant data by encoding sensory information (e.g., video, audio, radar) in spikes streams. These sensors are bio-inspired in that they mimic the temporal encoding of biological sensors (retinas and cochleas). They also have the advantage of being compatible with neuromorphic spike-based devices, thus, enabling the exploration of brain-inspired models of sensing & computation and sensor fusion in real-world conditions.
Prototype devices designed, fabricated, and tested during my research career, from my Ph.D. till 2023; they all are spike-based sensing (event-based cameras, DAVIS) and computing de- vices (neuromorphic processors with spiking neurons). Below is a selected list of publications, one for each device, in chronological order.
Selected publications
2022 Yuming He, Federico Corradi, Chengyao Shi, Stan van der Ven, Martijn Timmermans, Jan Stuijt, Paul Detterer, Pieter Harpe, Lucas Lindeboom, Evelien Hermeling, et al. An implantable neuromorphic sensing system featuring near-sensor computation and send-on-delta transmission for wireless neural sensing of peripheral nerves. IEEE Journal of Solid-State Circuits, 57(10):3058–3070, 2022
2021 Jan Stuijt, Manolis Sifalakis, Amirreza Yousefzadeh, and Federico Corradi. μbrain: An event-driven and fully synthesizable architecture for spiking neural networks. Frontiers in neuroscience, page 538, 2021
2019 Chenghan Li, Luca Longinotti, Federico Corradi, and Tobi Delbruck. A 132 by 104 10μm-pixel 250μw 1kefps dynamic vision sensor with pixel-parallel noise and spatial redundancy suppression. In 2019 Symposium on VLSI Circuits, pages C216–C217. IEEE, 2019
2018 Alessandro Aimar, Hesham Mostafa, Enrico Calabrese, Antonio Rios-Navarro, Ricardo Tapiador-Morales, Iulia-Alexandra Lungu, Moritz B Milde, Federico Corradi, Alejandro Linares-Barranco, Shih-Chii Liu, et al. Nullhop: A flexible convolutional neural network accelerator based on sparse representations of feature maps. IEEE transactions on neural networks and learning systems,
30(3):644–656, 2018.
2017 Diederik Paul Moeys, Federico Corradi, Chenghan Li, Simeon A Bamford, Luca Longinotti, Fabian F Voigt, Stewart Berry, Gemma Taverni, Fritjof Helmchen, and Tobi Delbruck. A sensitive dynamic and active pixel vision sensor for color or neural imaging applications. IEEE transactions
on biomedical circuits and systems, 12(1):123–136, 2017
2016 Federico Corradi and Giacomo Indiveri. A neuromorphic event-based neural recording system for smart brain-machine-interfaces. IEEE transactions on biomedical circuits and systems, 9(5):699–709, 2015
2015 Ning Qiao, Hesham Mostafa, Federico Corradi, Marc Osswald, Fabio Stefanini, Dora Sumislawska, and Giacomo Indiveri. A reconfigurable on-line learning spiking neuromorphic processor comprising 256 neurons and 128k synapses. Frontiers in neuroscience, 9:141, 2015
2014 Federico Corradi, Chris Eliasmith, and Giacomo Indiveri. Mapping arbitrary mathematical functions and dynamical systems to neuromorphic vlsi circuits for spike-based neural computation. In 2014 IEEE International Symposium on Circuits and Systems (ISCAS), pages 269–272. IEEE, 2014.