Jann works on integrating techniques and insights from machine learning into the econometric toolbox. His research brings together microeconometric methods, statistical decision theory, and mechanism design to clarify the use of flexible prediction algorithms in causal inference and data-driven decision-making. He is particularly interested in the role of human and machine decisions in replicable and robust inferences from big data.
Jann holds a PhD in economics from Harvard University. Previously, Jann obtained a master’s degree in public policy from the Harvard Kennedy School. His background is in mathematics with a focus on probability theory and combinatorics, which he studied at the University of Cambridge (Part III of the Mathematical Tripos) and the Technical University of Munich. Jann also studied and worked in Hangzhou, China and Ouagadougou, Burkina Faso.
Base Data and Decisions is a first-year MBA course in statistics and regression analysis. The course is taught using a flipped classroom model that combines extensive online materials with a lab-based classroom approach. Traditional lecture...
This year-long course takes a hands-on approach to learning about conducting research in Operations, Information and Technology. It will cover a broad spectrum of cutting-edge research in OIT from conceiving an idea to formulating a research...