Team

NowTemporal computation in spiking networks

Founded the lab; works where dynamical-systems theory meets neuromorphic engineering.

NowEnergy-efficient inference on neuromorphic chips

Builds and benchmarks spiking models on low-power hardware.

NowDendritic nonlinearities as computational primitives

Asks what a single neuron can compute before a network ever forms.

NowPredictive coding in recurrent cortical models

Studies how cortical circuits anticipate their own input.

NowPlasticity rules for continual learning

Designs learning rules that don't forget yesterday in order to learn today.

NowSpike-timing codes for sequence learning

Reads meaning out of when neurons fire — not just whether they do.

NowLow-power hardware for on-device learning

Brings learning off the cloud and onto the edge.

Keeps the lab running — grants, travel, and everything in between.