I am a Faculty Assistant at Academic City University, with research interests in NeuroAI, specifically neural decoding, bio-inspired architectures, and computational models of intelligence. I’m interested in what computational models actually reveal about how the brain works, and what neuroscience might change about how we design learning systems, not just inspire them.
I also work as a Founding Engineer, guiding technical direction and delivery, having previously worked for several years as an independent software engineer. My background is in Computer Science from the University for Development Studies.
Some representative lines of work include:
- Comparing how a vanilla RNN, a Dale's law-constrained RNN, and a published spiking neural network organize a context-dependent decision task internally, testing whether biological constraints change representational geometry and population dynamics, not just task performance.
- Examining whether default mode network activity can distinguish social from non-social video stimuli more accurately than early visual areas (V1–V2), using linear decoding of BOLD signals.
- An interactive lab exploring neural dynamics from first principles, from single-neuron biophysics to population-level activity.