Julie Ivy

Industrial and Systems Engineering

  • Phone: 919.513.1683
  • Office: 4347 Fitts-Woolard Hall

Julie Ivy is a professor in the Edward P. Fitts Department of Industrial and Systems Engineering and Fitts Faculty Fellow in Health Systems Engineering. She previously spent several years on the faculty of the Stephen M. Ross School of Business at the University of Michigan. She received her B.S. and Ph.D. in Industrial and Operations Engineering at the University of Michigan. She also received her M.S. in Industrial and Systems Engineering with a focus on Operations Research at Georgia Tech. She is the president of the Health Systems Engineering Alliance (HSEA) Board of Directors. She is an active member of the Institute of Operations Research and Management Science (INFORMS), Dr. Ivy served as the 2007 Chair (President) of the INFORMS Health Applications Society and the 2012 – 13 President for the INFORMS Minority Issues Forum. Her research interests are mathematical modeling of stochastic dynamic systems with an emphasis on statistics and decision analysis as applied to health care, public health, and humanitarian logistics. This research has made an impact on how researchers and practitioners address complex societal issues, such as health disparities, public health preparedness, hunger relief, student performance, and personalized medical decision-making and has been funded by CDC, NSF, Clinton Health Access Initiative, and the UNC Cancer Center.

Research Interests

Ivy’s primary research interests are in the mathematical modeling of stochastic dynamic systems with an emphasis on statistics and decision analysis as applied to health care, manufacturing, and service environments. The focus of her research is decision-making under conditions of uncertainty with the objective of improving the decision quality. Dr. Ivy’s research program seeks to develop novel concepts of maintenance and monitoring policies and associated scientific theories and apply them specifically to two important application domains: industrial and medical decision making. She has an extensive background in stochastic modeling, in particular the application of partially observable Markov decision processes (POMDPs) and Markov decision processes (MDPs). Dr. Ivy’s medical decision-making research relates to studying the cost-effectiveness of mammography screening, dynamic breast cancer screening policy development, false-positive prediction as a function of breast cancer screening policy, the impact of comorbidity on breast cancer patient outcomes modeling birth delivery choice as a function of long term consequences such as pelvic floor dysfunction, patient-centered pharmaceutical inventory management, and public health preparedness. In addition to her research in medical decision-making, Dr. Ivy also works in the area of humanitarian logistics particularly as it relates to hunger relief and equitable food distribution. Her research has been funded by the NSF and the Centers for Disease Control.

Education

DegreeProgramSchoolYear
Ph.D.DoctorateUniversity of Michigan1998
MSUniversity of MichiganGeorgia Institute of Technology1992
BSBachelor of ScienceUniversity of Michigan1991

Honors and Awards

  • 2020 | WORMS Award for the Advancement of Women in OR/MS, INFORMS
  • 2020 | Alumni Association Outstanding Research Award, NC State University
  • 2016 | Moving Spirit Award, INFORMS
  • 2012 | C. A. Anderson Outstanding Faculty Award, ISE Department at NC State University

Discover more about Julie Ivy

 

Publications

Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty
Howerton, E., Contamin, L., Mullany, L. C., Qin, M., Reich, N. G., Bents, S., … Lessler, J. (2023), NATURE COMMUNICATIONS, 14(1). https://doi.org/10.1038/s41467-023-42680-x
Quantifying association and disparities between diabetes complications and COVID-19 outcomes: A retrospective study using electronic health records
Paramita, N. L. P. S. P., Agor, J. K., Mayorga, M. E., Ivy, J. S., Miller, K. E., & Ozaltin, O. Y. (2023), PLOS ONE, 18(9). https://doi.org/10.1371/journal.pone.0286815
Resiliency within the Socio-Ecological System of a Large Food Bank Network: Preparing, mitigating, responding, and recovering from Hurricane Florence
Hasnain, T., Walton, T. N., Odubela, K., McConnell, S., Davis, L., Ivy, J., … Mpere, E. (2023), INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION, 88. https://doi.org/10.1016/j.ijdrr.2023.103580
AN APPROACH TO POPULATION SYNTHESIS OF ENGINEERING STUDENTS FOR UNDERSTANDING DROPOUT RISK
Dorris, D., Ivy, J., & Swann, J. (2022), 2022 WINTER SIMULATION CONFERENCE (WSC), pp. 677–688. https://doi.org/10.1109/WSC57314.2022.10015440
COULD EARLIER AVAILABILITY OF BOOSTERS AND PEDIATRIC VACCINES HAVE REDUCED IMPACT OF COVID-19?
Rosenstrom, E. T., Ivy, J. S., Mayorga, M. E., & Swann, J. L. (2022), 2022 WINTER SIMULATION CONFERENCE (WSC), pp. 1092–1103. https://doi.org/10.1109/WSC57314.2022.10015236
Checklists in Healthcare: Operational Improvement of Standards using Safety Engineering-Project CHOISSE-A framework for evaluating the effects of checklists on surgical team culture
Perera, G. N., Hey, L. A., Chen, K. B., Morello, M. J., McConnell, B. M., & Ivy, J. S. (2022), APPLIED ERGONOMICS, 103. https://doi.org/10.1016/j.apergo.2022.103786
Modeling the Impact of Nonpharmaceutical Interventions on COVID-19 Transmission in K-12 Schools
Zhang, Y., Mayorga, M. E., Ivy, J., Lich, K. H., & Swann, J. L. (2022), MDM POLICY & PRACTICE, 7(2). https://doi.org/10.1177/23814683221140866
Optimizing the First Response to Sepsis: An Electronic Health Record-Based Markov Decision Process Model
Rosenstrom, E., Meshkinfam, S., Ivy, J. S., Goodarzi, S. H., Capan, M., Huddleston, J., & Romero-Brufau, S. (2022, July 22), DECISION ANALYSIS, Vol. 7. https://doi.org/10.1287/deca.2022.0455
Organizational decision-making during COVID-19: A qualitative analysis of the organizational decision-making system in the United States during COVID-19
Johnson, K., Biddell, C. B. B., Hecht, H. K. K., Lich, K. H. H., Swann, J., Delamater, P., … Patel, M. D. D. (2022, November 18), JOURNAL OF CONTINGENCIES AND CRISIS MANAGEMENT, Vol. 11. https://doi.org/10.1111/1468-5973.12437
The SMART Framework: Selection of Machine Learning Algorithms With ReplicaTions-A Case Study on the Microvascular Complications of Diabetes
Swan, B. P., Mayorga, M. E., & Ivy, J. S. (2022), IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 26(2), 809–817. https://doi.org/10.1109/JBHI.2021.3094777

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Julie Ivy