The COVID-19 pandemic has exposed vulnerabilities in global supply chains, leading to
economic damage and product shortages caused by demand surges and supply …

We study the allocative challenges that governmental and nonprofit organizations face when
tasked with equitable and efficient rationing of a social good among agents whose needs …

Motivated by the need for a robust policy in the face of environment shifts between training
and the deployment, we contribute to the theoretical foundation of distributionally robust …

Study objective We aimed to build prediction models for shift-level emergency department
(ED) patient volume that could be used to facilitate prediction-driven staffing. We sought to …

An on-demand workforce can greatly benefit a traditional call center by allowing it to adjust
its service capacity on demand quickly. Despite its conceptual elegance, the …

The performance of decision policies and prediction models often deteriorates when applied
to environments different from the ones seen during training. To ensure reliable operation …

Motivated by the growing availability of advanced demand forecast tools, we study how to
use future demand information in designing routing strategies in queueing systems under …

To optimize nurse staffing in the emergency department (ED), Hartford Hospital has been
collaborating with academics and consultants to schedule nurse shifts over each six-week …

Amidst critical levels of nurse shortages, we partnered with Indiana University Health (IUH)
to pioneer a novel suite of advanced data and decision analytics to support a new model of …

Scant research has delved into the non-clinical facets of artificial intelligence (AI),
concentrating on leveraging data to enhance the efficiency of healthcare systems and …