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About the Instructor:
is an Economist in the Office of the Chief Economist in the AI + Research division of Microsoft. This group combines Economists with traditional Data Scientists to address difficult challenges facing Microsoft. He has worked across many products groups, including Office and Gaming, and on external engagements, including with the World Bank. He specializes in embedding Machine Learning into existing Econometric methods to both improve the quality of estimation/causal inference and to save time/reduce errors in model selection. He also works to open source generic tools to benefit the broader analytics community. He holds a PhD in Economics from the University of Maryland, a MA of Economics from the University of British Columbia, and a BS in Computer Science from Stanford University.