Neuromorphic Optimisation Research
Advancing Neuromorphic and Computational Intelligence towards scalable, energy-efficient optimisation
About NeurOptim
NeurOptim explores how Neuromorphic Computing and Computational Intelligence can give rise to a new generation of optimisation algorithms. We study spiking-based search mechanisms, scalable SNN architectures, and hardware-aware development frameworks that enable low-power, low-latency optimisation at large scale.
We aim to define the foundations of neuromorphic optimisation and provide open tools, models, and insights for the scientific community.
Spiking Neural Networks
Designing spiking-based optimisation mechanisms using event-driven computation, biologically inspired neuron models, and scalable SNN architectures.
Neuromorphic Hardware
Developing hardware-aware frameworks that adapt NeurOptimisers to the constraints and capabilities of modern neuromorphic platforms.
Open Research
Providing open frameworks, models, and reproducible experimental pipelines to support the emerging field of neuromorphic optimisation and encourage community-driven development.
Upcoming Events
Tools & Resources
NEVO: Neuromorphic EVolutionary Optimisation
NEVO uses a Nengo-simulated Basal Ganglia circuit to adaptively select optimisation operators at runtime, bridging neuromorphic computing with metaheuristic search....
NeurOptimiser
NeurOptimiser is a neuromorphic optimisation framework in which metaheuristic search emerges from asynchronous spiking dynamics.
NeurOptimiser Dataset
Experiment codes and datasets for the NeurOptimiser framework, including BBOB benchmark results with linear and Izhikevich spiking neuron models.
Recent Publications
Get Involved
Interested in neuromorphic optimisation? Explore our open-source tools, access our datasets, or reach out to collaborate.
