She received her Ph.D. in Experimental High Energy Physics from MIT in 2010. Her main research is in experimental particle physics, including searches for new physics in the neutrino sector with particle-accelerator-based and/or large underground neutrino experiments. The discovery and study of rare processes with the next generation of neutrino detectors requires continuous and efficient processing of data streams with rates of up to multiple terabytes per second. Her current research includes data processing hardware design and exploration of digital data processing techniques for high data rate environments, and more recently she has been exploring the implementation of machine learning algorithms on field-programmable gate arrays.