Daniel Neil received his B.S. degree in Biomedical Computation from Stanford and minored there in Chinese and Japanese. He completed his master’s degree in the Neural Systems and Computation program from the Institute of Neuroinformatics and is currently pursuing his Doctoral degree at the INI. Formerly, he was a research assistant in Kwabena Boahen’s Brains in Silicon Laboratory at Stanford and helped to build Neurogrid (the lowest-power neuron supercomputer), and worked as a technical consultant in the San Francisco Bay Area. He is also a co-founder of Ponder (www.pondertalks.com), a site to discover intellectual events.
Currently, his research interests focus on discovering scalable architectures for advanced machine learning, with a focus on deep neural networks. Specifically, he focuses on analyzing and building neuron models and hardware architectures that support efficient processing of deep neural networks, convolutional neural networks, and recurrent neural networks.