Challenges and Opportunities in Data Analysis (Or: Applying Theoretical Computer Science to Big Data)
Data is everywhere, but it is rarely obvious how best to use it to inform the decisions that we make. This talk will cover highlights from my work addressing the following questions:
*How do we summarize and learn from data to inform our decisions? *What if the data is personal or sensitive? *What if we can only afford to store a tiny fraction of the data? *Can we offload our data processing to the cloud, and obtain a formal guarantee that the answers returned by the cloud are correct?
Bio: Justin is currently a Research Scientist at Yahoo Labs, New York City. Previously, Justin was a Microsoft Research Fellow at the Simons Institute for the Theory of Computing. He received his Ph.D. from the Theory of Computation group at Harvard University in 2013, and his B.S. in Computer Science from Yale in 2009.