Objective
As digital computing approaches its limits, a paradigm shift is needed to push the boundaries of computation. Neuromorphic computing, an analog computing paradigm inspired by the human brain, offers a promising alternative. Implementing mathematical models such as artificial neural networks directly in neuromorphic hardware holds tremendous potential: it can drastically reduce energy consumption while enabling faster inference when compared to digital architectures. Yet, a major bottleneck is the lack of dedicated algorithms for training analog circuits from data. Traditional methods such as backpropagation are unsuitable, as they require different circuits for training and inference, thus introducing energy-costly data transfer between circuits.
I propose a novel systems theory for learning in analog circuits, inspired by ideas from the literature on energy-based models, pioneered by Hopfield, Hinton and others. My approach is to cast the learning problem as the feedback interconnection of continuous-time circuit dynamics with an optimization algorithm. Using this framework, I will develop novel energy-based learning algorithms, capable of training circuits from input-output data. The developed algorithms are fully distributed, thus enabling efficient training of large-scale circuits, as well as robust to uncertain circuit elements, therefore accounting for device-to-device variations in neuromorphic hardware.
My preliminary results on resistive circuits already demonstrate the potential of this approach. Building on this foundation, the project will establish a comprehensive system-theoretic framework, capable of handling nonlinear and dynamic circuits with (mem)ristive and capacitive elements, as well as more general dissipative networks. This fundamental research project has the potential to significantly advance the theory of physics-based learning. The proposed theory will be supported by efficient computational tools and tested in neuromorphic hardware.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering analogue electronics
- natural sciences mathematics applied mathematics dynamical systems
- natural sciences mathematics applied mathematics mathematical model
- natural sciences computer and information sciences artificial intelligence computational intelligence
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC - HORIZON ERC Grants
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2026-STG
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
9712CP Groningen
Netherlands
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.