Shenghao Wu

This paper introduces SNOPS, a method to automatically customize spiking network models to match large-scale neuronal recordings, revealing limitations of current models.

This paper introduces brainprints, interpretable MEG features that can identify individuals from anonymized MEG data across sessions and modalities.

YASS sorts spikes from multi-electrode arrays with > 500 electrodes using neural network detection and denoising, parallelized nonparametric Bayesian clustering, and matching-pursuit deconvolution, outperforming manual sorting on primate retina recordings.