The NMI Lab strives to create computing systems that work more like the brain, by combining the fundamental and the applied. Specifically, our long-term research goal is to emulate high-level, cognitive function in dedicated neuromorphic hardware systems.
The lab's approach is to study neural circuits as computational substrates implementing a class of machine learning algorithms, and to design brain-inspired (neuromorphic) architectures that efficiently implement these algorithms.
Outcomes from this research range from brain-computer interfaces to goal-directed and adapting robotic systems.
Frontiers in Neuroscience. Synaptic sampling machines are the best performing spike-based unsupervised learners to date!