Andrew J. Schaefer
Affiliations: | 2000-2015 | Industrial engineering | University of Pittsburgh, Pittsburgh, PA, United States |
| 2015- | Computational and Applied Mathematics | Rice University, Houston, TX |
Area:
stochastic integer programming, optimization in organ allocation, optimal cancer therapies, and healthcare systemsWebsite:
https://www.cmor-faculty.rice.edu/~andrew.schaefer/Google:
"Andrew J. Schaefer"Parents
Sign in to add mentor| George L. Nemhauser | grad student | 2000 | Georgia Tech | |
| (Airline crew scheduling under uncertainty.) | ||||
Children
Sign in to add trainee| Oguzhan Alagoz | grad student | 2004 | University of Pittsburgh |
| Osman Y. Ozaltin | grad student | 2011 | University of Pittsburgh (Computer Science Tree) |
| Temitayo Ajayi | grad student | 2020 | Rice University (MPROTree) |
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Publications
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| Ajayi T, Hosseinian S, Schaefer AJ, et al. (2023) Combination Chemotherapy Optimization with Discrete Dosing. Informs Journal On Computing. 36: 434-455 |
| Ng SP, Ajayi T, Schaefer AJ, et al. (2019) Surveillance imaging for patients with head and neck cancer treated with definitive radiotherapy: A partially observed Markov decision process model. Cancer |
| Ng SP, Pollard C, Berends J, et al. (2019) Usefulness of surveillance imaging in patients with head and neck cancer who are treated with definitive radiotherapy. Cancer |
| Cornuéjols G, Schaefer A. (2015) Special issue of Mathematical Programming, Series B, dedicated to the international symposium on mathematical programming, Pittsburgh, July 2015 Mathematical Programming. 151: 1-2 |
| Kabiri M, Jazwinski AB, Roberts MS, et al. (2014) The changing burden of hepatitis C virus infection in the United States: model-based predictions. Annals of Internal Medicine. 161: 170-80 |
| Nabors S, Bountourelis T, Schaefer A, et al. (2011) Cost impact of blocking: predictability of ICU patient throughput and cost variance using process modeling Critical Care. 15: 460 |
| Alagoz O, Hsu H, Schaefer AJ, et al. (2010) Markov decision processes: a tool for sequential decision making under uncertainty. Medical Decision Making : An International Journal of the Society For Medical Decision Making. 30: 474-83 |
| Rajgopal J, Wang Z, Schaefer A, et al. (2009) Effective management policies for remnant inventory supply chains Iie Transactions (Institute of Industrial Engineers). 41: 437-447 |
| Alagoz O, Bryce CL, Shechter S, et al. (2005) Incorporating biological natural history in simulation models: empirical estimates of the progression of end-stage liver disease. Medical Decision Making : An International Journal of the Society For Medical Decision Making. 25: 620-32 |
| Shechter SM, Bryce CL, Alagoz O, et al. (2005) A clinically based discrete-event simulation of end-stage liver disease and the organ allocation process. Medical Decision Making : An International Journal of the Society For Medical Decision Making. 25: 199-209 |