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My interests are in computing with neural circuits (in silico), and on reverse engineering the fruit fly (Drosophila melanogaster) brain (in vivo).

My work on computing with neural circuits is centered on Neural Computing Engines and on Massively Parallel Neural Computation. I pioneered formal theoretical methods of spectrotemporal and spatiotemporal neural encoding/decoding, functional identification of spiking neural circuits and architectures and, dendritic stimulus processing and spike processing. My research group implemented massively parallel neural computation algorithms in the analog domain (graded potentials) and in the spike domain on clusters of GPUs. Some of the code developed by these projects is already available for free downloads on the Internet.

My in vivo work on Reverse Engineering the Fruit Fly Brain primarily addresses sensory processing in the early olfactory system of the Drosophila. In my sensory processing research I led a team of two graduate students who developed the first airborne odor delivery system that is both reproducible and precise; this enabled a far more accurate representation of time-varying odor stimuli in the olfactory sensory neurons and projection neurons than achievable with earlier techniques. I also initiated the Neurokernel Project, an open scalable software framework for emulation and validation of fruit fly brain models on multiple GPUs.

More detailed information is available under Bionet Research.