Jing is a PhD student in the Department of Civil and Systems Engineering (CaSE), the Center for Systems Science and Engineering (CSSE), the Data Science and AI Institute (DSAI), and the Malone Center for Engineering in Healthcare (Malone) at Johns Hopkins University. Her research focuses on large-scale optimization, decision-making under uncertainty, and machine learning, with applications in healthcare delivery and medical physics. She develops data-driven robust optimization frameworks for healthcare operations and radiotherapy planning, including nurse scheduling and downstream inventory management.
We study healthcare scheduling across the patient care pathway, from surgery to post-discharge home care. The first project focuses on operating room scheduling with ward inpatient capacity constraints. Elective surgery […]
Most inventory models address demand uncertainty but give limited attention to lead time uncertainty, particularly endogenous lead time uncertainty, and often ignore stockpile policies and large-scale disruptions. We propose a […]
This work focuses on brain stereotactic radiosurgery for patients with multiple metastases to identify a single “isocenter” location, the point the machine rotates around as it delivers radiation from many […]