Aaron Gilad Kusne works in the Materials for Energy and Sustainable Development Group at NIST. His research focuses on data-mining for rapid analysis of massive materials science databases. He is developing data-mining techniques to accelerate the discovery of advanced materials. These new data-mining techniques integrate solid state physics, lattice and symmetry analysis, and information theory. The data-mining techniques are run both offline and online during sample characterization to provide live guidance to the experimentalist and improve data collection. Techniques of interest include (but are not limited to) sparse kernel machines, latent variable analysis, and Bayesian analysis.