Sony Europe [Oct 2022 - Now] [Zürich, Switzerland]
Neuromorphic computing with event-based communication, asynchronous processing and spike-based computing.
Bio-Inspired Circuits and Systems Lab, University of Groningen [Oct 2020 - Sep 2022] [Groningen, Netherlands]
Algorithmic modeling of brain-inspired learning and memory with local synaptic plasticity mechanisms in spiking neural networks.
Exploring novel computational primitives for temporal patterns recognition.
Hardware implementation on the Intel Loihi neuromorphic chip.
EDGE-eBRAIN Team, LEAT Lab, Université Côte d'Azur [Oct 2017 - Sep 2020] [Sophia Antipolis, France]
Exploration of brain-inspired computing with self-organizing neuromorphic architectures.
Supervised by Prof. Benoît Miramond.
Institute of Technology, Université Côte d'Azur [Oct 2017 - Sep 2020] [Nice, France]
Lecture: Introduction to deep learning (5 hours).
Practical sessions: Electronics (60 hours).
Practical sessions: Programming (140 hours).
EDGE-eBRAIN Team, LEAT Lab, Université Côte d'Azur [Apr 2017 - Sep 2017] [Sophia Antipolis, France]
Neuromorphic architectures: A comparison between machine-learning and neuroscience approaches for FPGA/ASIC hardware implementations.
Bio-Inspired Circuits and Systems [Oct 2020 - Sep 2022] [Groningen, Netherlands]: Co-supervising the research on brain-inspired learning using spiking neural networks with Prof. Elisabetta Chicca.
Matthew Yedutenko [Oct 2022 - June 2022] [Zurich, Switzerland]: Bio-inspired vision for fast and robust autonomous navigation.
Alejandro Pequeño-Zurro - Visiting PhD student [Apr 2022 - Sep 2022] [Groningen, Netherlands]: Training the Time Difference Encoder (TDE) for keyword spotting at the edge.
Fernando M. Quintana Velázquez - Visiting PhD student [Oct 2021 - Sep 2022] [Groningen, Netherlands]: Confronting event-based three-factor local learning techniques for FPGA-based on-chip training of spiking neural networks.
Caterina Caccavella - Master thesis [Mar 2023 - Sep 2023] [Zurich, Switzerland]: Low-power inference with EVS, neuromorphic processors and SNNs.
Tales Braig - Master project [Apr 2022 - Sep 2022] [Groningen, Netherlands]: Self-organizing spiking neural networks for post-labeled unsupervised learning of event-based patterns.
Mohamed Sadek Bouanane - Master thesis [Sep 2021 - Sep 2022] [Groningen, Netherlands]: Exploration of spiking neurons leakages and network recurrences for spike-based spatio-temporal pattern recognition.
Julian Lopez Gordillo - Master thesis [Jan 2021 - Jan 2022] [Groningen, Netherlands]: Local unsupervised learning of multi-sensory event-based data with spiking neural networks.
Ton Juny Pina - Master thesis [Jan 2021 - Dec 2021] [Groningen, Netherlands]: Keyword spotting with the Time Difference Encoder (TDE).
Marino Rasamuel - Master thesis [Apr 2018 - Sep 2018] [Sophia Antipolis, France]: Dynamic neural fields for embedded attentional process.
Ulkar Alakbarova - Master project [Jun 2017 - Jul 2017] [Sophia Antipolis, France]: FPGA-based hardware design of a multi-layer perceptron.
Yann Zavattero - Bachelor project [Mar 2019 - Jun 2019] [Sophia Antipolis, France]: Efficient object recognition and tracking using eembedded artificial neural networks on the Intel Movidious chip.
Loïc Cordone [December 2022] [Université Côte d'Azur, France]: Performance of spiking neural networks on event data for embedded automotive applications.
Mohamed Sadek Bouanane [July 2022] [University of Boumerdes, Algeria]: Exploration of spiking neurons leakages and network recurrences for spike-based spatio-temporal pattern recognition.
Julian Lopez Gordillo [Jan 2022] [University of Groningen, Netherlands]: Local unsupervised learning of multi-sensory event-based data with spiking neural networks.
Ton Juny Pina [Dec 2021] [University of Groningen, Netherlands]: Keyword spotting with the Time Difference Encoder (TDE).
Istituto Italiano di Tecnologia, University of Groningen, Politecnico di Torino, University of Zurich, University of Basel, Silicon Austria Labs, Intel Labs [Jun 2021 - Jun 2022] [Groningen, Netherlands]
Explore the potential of an end-to-end neuromorphic system for tactile perception with event-based communication (sensor level), asynchronous processing on Loihi (hardware level) and spike-based computing (algorithmic level) for the physical interaction of robots with their environment.
University of Groningen, University of Seville, Intel Labs [Oct 2020 - Oct 2021] [Groningen, Netherlands]
Implement the Time Difference Encoder (TDE) on Loihi for various spatio-temporal pattern recognition applications at the edge.
University of Zurich, ETH Zurich, Université Catholique de Louvain, National University of Singapore, Université Côte d'Azur [May 2019 - Aug 2020] [Sophia Antipolis, France]
Collect a dataset of EVS+EMG for hand gesture classification to explore the potential of SNNs and neuromorphic hardware for multimodal inference at the edge.
Université Côte d'Azur, University of Lorraine, University of Bordeaux, University of Applied Sciences of Western Switzerland [Mar 2018 - Sep 2020] [Sophia Antipolis, France]
Algorithmic modeling of brain-inspired self-organization with structural and synaptic plasticity mechanisms for FPGA-based cellular neuromorphic implementations.
Université Côte d'Azur: LEAT Lab, I3S, Inria and LJAD [Apr 2017 - Sep 2017] [Sophia Antipolis, France]
Neural Computing (NeuComp) project: Algorithmic modeling, simulation, verification and hardware implementation of spiking neural networks.
Lulea Tekniska Universitet, RISE Research Institutes of Sweden, University of Groningen, Technische Universität München, Ericsson, SEB Leasing Oy, Infineon, University of Manchester [Apr 2022] [Groningen, Netherlands]
Gemini targets self-managed cloud to edge systems with hybrid AI based on neuromorphic and digital components. We use the notion of edge and digital twin to seamlessly connect neuromorphic systems and to enable their services to be provided digitally in the cloud edge continuum.
Not funded (score of 3.5 / 5.0).
King’s College London, University of Groningen, Technische Universitat Ilmenau, Intel Labs, Helmholtz-Zentrum Berlin, Technical University of Denmark [May 2021] [Groningen, Netherlands]
Design and demonstrate prototype neuromorphic circuits and systems that integrate novel spike-based Bayesian algorithms, advanced memristive devices and locally adaptive sensors to implement real-time audio processing applications in noisy environments.
Not funded (score of 4.3 / 5.0).
Frontiers in Neuroscience - Neuromorphic Engineering [4 papers].
Frontiers in Neurorobotics [1 paper].
PeerJ Computer Science [1 paper].
Informatics in Medicine Unlocked [1 paper].
IEEE AICAS Conference [2 papers].
IEEE Sensors Applications Symposium [2 papers].