Department of Industrial Engineering
University of Houston
Date: Friday, Jan 24, 2020
Time: 1 - 1:50 pm
Location: D3 W122
Abstract: Cancer is one of the leading causes of death in the United States. Radiation Therapy (RT) is an effective treatment option for cancer patients. In radiation therapy, a patient undergoes a series of treatment sessions over several weeks. The clinical goal of radiation therapy is to maximize the tumor damage while minimizing toxic effects on surrounding healthy tissues during the course of treatment. Every step of radiation therapy is subject to some types of uncertainties, which may compromise the quality of treatment. Therefore, it is desired to develop an optimization approach to meet prescription requirements and tackle the uncertainties in radiation therapy. I will discuss some existing challenges in radiation therapy treatment planning and robust optimization role in addressing uncertainties in this problem.
Biography: Saba Ebrahimi is a fourth-year Ph.D. student in Industrial Engineering at University of Houston. Her doctoral research is about radiation therapy treatment planning under uncertainties. In her dissertation, she focuses on combining optimization methods and machine learning techniques to find the optimal radiation therapy treatment plan for cancer patients that can improve patient’s survival. She also works as a research and teaching assistant at Department of Industrial Engineering, University of Houston