Dr. Ivy’s primary research interests are in the mathematical modeling of stochastic dynamic systems with 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 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.
