Research area
Neural Computation
We explore biologically inspired computation and the mathematical foundations — algorithms, theory, and neuromorphic ideas — that underpin next-generation intelligence.
Overview
Nature computes differently than our machines. Our neural computation group studies brain-inspired architectures, neuromorphic principles, and models of cognition, alongside the algorithmic and theoretical foundations that cut across all of our work. This is the connective tissue of the lab: the mathematics of learning, computation, and information that links quantum, AI, and robotics research together.
Focus areas
- Neuromorphic & spiking models
- Theoretical foundations of learning
- Models of cognition & memory
- Algorithms & computational theory
- Energy-efficient computation
Projects in this area
Other research areas
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