B.S.E., Operations Research and Financial Engineering, Princeton University, 2009
M.S., Management Science and Engineering, Stanford University, 2011
Ph.D., Management Science and Engineering, Stanford University, 2014
Assistant Professor, Dept. of Industrial and Systems Engineering, University of Minnesota
Scientific & Professional Societies
Institute for Operations Research and Management Science (INFORMS)
Society for Medical Decision Making (SMDM)
Diana Negoescu’s research focuses on the application of operations research and management science to medical and health policy decision-making problems. She is particularly interested in personalized medical decision-making and healthcare models for problems where patient characteristics are partially unknown or evolving over time, and where decision makers are risk-averse, or face constraints on the resources they can use or the actions they can take. She has developed mathematical models to help manage chronic diseases such as multiple sclerosis or Crohn’s disease at the individual patient level, as well as mitigate the impact of infectious disease epidemics such as HIV, tuberculosis, or measles at a larger scale, population level.
The research is focused on the application of operation research methods to health policy analysis and medical decision-making. Uses statistical learning, stochastic modeling, and optimization techniques to mathematically model disease progression at the individual patient level or disease epidemics at the population level, and optimize interventions for improved patient health outcomes and reduced costs.
Bill and Melinda Gates Foundation Grand Challenges Explorations Grant For Groundbreaking Research in Global Health and Development – PI on a $100,000 grant to improve the timeliness of infant vaccinations in Uganda through network transportation providers, November 2017- April 2019
NUS-Global Asia Institute NIHA Research Grant : Designing Incentives to Improve Tuberculosis Treatment Adherence in Resource Constrained Settings, Co-Investigator (PI: Joel Goh, S$163,570.00), February 2019 – January 2021
Instructor, IE 3011 Optimization I (undergraduate) 2014, 2015, 2016, 2017,2018
Instructor, IE 3521 Statistics, Quality and Reliability (undergraduate) 2015, 2016
Instructor, IE 5080/ 8536 Methods and Models for Health Policy Analysis and Medical Decision Making (graduate) 2017, 2019
Honors and Awards
Finalist, INFORMS Pierskalla Award, recognizing research excellence in the field of healthcare management science, San Francisco, CA, 2014
Finalist, Society of Medical Decision Making Lee Lusted Award for outstanding student presentations of research at the Annual Meeting, Baltimore, MD, 2014
Honorable Mention, Doing Good with Good OR Student Competition, NFORMS Annual Meeting, San Diego, CA, 2009
Negoescu, D.M., K. Bimpikis, M. L. Brandeau and D. A. Iancu. “Dynamic learning of patient response rates: An application to treating chronic diseases,” Management Science, 2017, 1-20
Negoescu, D. M., Z. Zhang, H. C. Bucher, and E. Bendavid, for the Swiss HIV Cohort Study; “Differentiated Human Immunodeficiency Virus RNA monitoring in resource-limited settings: An economic analysis”, Clinical Infectious Diseases, 2017, 64(12), 1724–1730
Negoescu, D. M., D. K. Owens, M. L. Brandeau, and E. Bendavid. “Balancing immunological benefits and cardiovascular risks of antiretroviral therapy: When is immediate treatment optimal?” Clinical Infectious Diseases, 2012, 55(10), 1392-1399
Winetsky, D. E., D. M. Negoescu, O. Almukhamedova, E. DeMarchis, A. Dooronbekova, D. Pulatov, N. Vezhnina, B. Zhussupov, D. K. Owens, and J. D. Goldhaber-Fiebert. “Screening and rapid molecular diagnosis of tuberculosis in prisons in Russia and Eastern Europe: A cost-effectiveness analysis,” PLoS Medicine, 2012, 9(11):e1001348.
Negoescu, D. M., P.I. Frazier, and W.B. Powell. “The knowledge-gradient algorithm for sequencing experiments in drug discovery,” INFORMS Journal on Computing, 2011, 23(3), 246-263.