Yonatan Gur's primary research interests include the intersection of revenue management and service operations, with a focus on data-driven learning and performance optimization under uncertain, dynamic environments. The main field of applications that he studies is online services, and in particular ones provided in online advertising markets, including ad auction platforms, recommendation services, and social networks. These markets present a competitive landscape that is often characterized by extreme complexity, uncertainty, and non-stationarity, together with the necessity of making numerous decisions in very short time scales.
Yonatan Gur is an Assistant Professor of Operations, Information and Technology at Stanford University’s Graduate School of Business. Prior to joining Stanford in 2014 he received his PhD in Decision, Risk, and Operations from Columbia Business School. He also holds a B.Sc. degree from the School of Physics and Astronomy and an M.Sc. from the School of Mathematical Sciences, Tel Aviv University.
Operations refer to the processes through which businesses produce and deliver products or services. Managing operations well is necessary in order for these processes to be completed in a timely manner, consume minimal resources and costs, and...
In most real-world problems, decision-makers often face uncertainty with respect to the underlying models that drive the rewards/costs associated with potential strategies. The uncertainty in the problem can be modeled in a number of ways (e.g.,...
Operations refer to the processes through which businesses produce and deliver products or services. Managing operations well is necessary in order for these processes to be completed in a timely manner, consume minimal resources and costs, and...
This course focuses on basic managerial issues arising in the operations of both manufacturing and service industries. The objectives of the course are to familiarize students with the problems and issues confronting operations managers and to...
In most real-world problems, decision-makers often face uncertainty with respect to the underlying modelsnnthat drive the rewards/costs associated with potential strategies. The uncertainty in the problem can bennmodeled in a number of ways (e.g...
