Deepthi Raghunandan aspires to build flexible and smart data analysis systems. She believes that unburdening the data analyst can make way for great insights in a diverse number of fields. To this end Deepthi is a PhD candidate researching and building interactive programming systems for data scientists with Professor Niklas Elmqvist and Assistant Professor Leilani Battle. She is an intern at NASA Goddard’s Advanced Software Technology Group to support NASA Scientists derive insights from their Earth System Models. Before entering the PhD program she spent four years as a SDET and SDE at Microsoft, actively working on client side software in the Windows Phone and Skype for Business divisions, where she learned that providing a good user experience requires more than designing a good UI. She also spent two years working on a start-up project, which planted the motivational seeds to apply machine learning towards her solutions. She is a proud Terp! She graduated from the University of Maryland with undergraduate degrees in Computer Science and Economics.