Yonatan Gur's primary research lies in the intersection of revenue management and service operations, with a focus on (i) developing principles and practical methods of data-driven learning and sequential optimization in dynamic and strategic environments; and (ii) study the implications of these on service provision in online marketplaces and platforms, including ad auction platforms, recommendation systems, and social networks. Such markets present competitive landscapes characterized by complexity, uncertainty, and non-stationarity. These features drive new operational challenges that are fundamental for increasing revenue streams as well as for maintaining long-run sustainability in many online services.
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...
