AREAS OF INTEREST
Data-driven and Robust Optimization
Large-Scale Optimization and Decomposition Algorithms
EXAMPLES OF RESEARCH TOPICS
Radiation Therapy Treatment Planning
Radiation therapy is one of the main treatment methods for cancer. The process of RT starts with a medical image (e.g., CT, MRI) of the patient's anatomy and computerized 3D-contours that delineate cancerous and healthy regions. The goal is to irradiate cancerous cells with high-energy radiation beams while minimizing the radiation to the healthy tissue. We use robust optimization to mitigate uncertainties in the patient's anatomical features throughout the treatment and find high-quality treatment plans that meet clinically-prescribed criteria while minimizing possible side effects. Radiation therapy optimization problems are extremely large-scale and solving them is computationally intensive. We develop specialized solution algorithms that can be employed to solve these problems efficiently.
Patients often have to wait a long time before receiving medical services of different types. This long waiting time may be of critical importance to some patients, depending on the urgency of care they need. The scheduling of patient appointments with different priority levels is therefore challenging, especially since the future arrival rates of patients and their priority levels are uncertain. We employ robust optimization to provide efficient multi-period multi-priority patient scheduling policies that aim to meet certain waiting time thresholds for patients in each priority level and minimize their excess waiting times.