Burhaneddin Sandikçi studies decision-making problems under uncertainty with special interest in problems in medical decision making and health care operations. He is particularly interested in the mathematical modeling and analysis of such problems. He employs the methodologies of Markov decision processes (MDPs), partially observed MDPs, stochastic programming, and simulation in his research. Samples from his most recent work include: (i) equilibrium analysis of the use of marginal organs for transplantation to help alleviate the burden of organ shortages, which leads to easily implementable policy incentives that increase the equilibrium utilization of organs while also improving the social welfare; (ii) modeling and analysis of the use of breast density information and supplemental tests (e.g., ultrasound and MRI) in screening for breast cancer; numerical results demonstrate that incremental benefits of supplemental tests over digital mammography are limited for the overall population except for patients with high risk of breast cancer including patients with extremely dense breasts; and (iii) the development of an embarrassingly parallel general bounding method for multistage stochastic programs.
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The University of Chicago
Booth School of Business
Chicago, IL 60637