学术报告第201329期

报告题目：   Road from Engineering to Radiation  Oncology

报 告 人：   Hao Zhang   助理教授（美国威斯康辛州立大学）  

报告时间：  12月30日15：00

报告地点： 南一楼中311会议室

CV:  Hao Zhang obtained his PhD  in Industrial and Systems Engineering in 2008 from University of  Wisconsin-Madison with a concentration in applying Operations Research/Numerical  Methods to Radiation Oncology. After the completion of his graduate work, he  spent 3 years in the department of Radiation Oncology at University of Maryland  School of Medicine as a post-doctoral research fellow. He joined the department  as a research faculty in 2011. As a junior research faculty, Dr. Zhang has  published 12 total peer-reviewed journal papers including 7 first-author papers,  one book chapter and 68 abstracts and conference proceedings. He holds 3  patents. He was one of the two junior researchers received “AAPM Research Seed  Funding Initiative” Awards to support his research in radiotherapy in 2011. His  recent work using machine learning techniques to predict pathologic response of  locally advanced esophageal cancer with PET/CT features received “Best In  Physics” Award and “John S. Laughlin Science Council Research Symposium” Award  from AAPM in 2012. This work was later featured on MedicalPhysicsWeb and SNMMI  SmartBrief. He is the principal investigator or co-investigator for 4 research  grants with a total amount of $1.23 million.

Abstract:   It has been recommended that healthcare systems engineering can lead the way to  a revolution analogous to that of manufacturing and distribution over recent  decades. One of the healthcare areas in which we can make immediate impact is  cancer research. Mathematical programming, optimization algorithms,  discrete-event simulation and machine learning techniques are tools that have  been widely used in systems engineering and Operations Research applications. In  this talk, Dr. Zhang will demonstrate the utilization of these tools in  Radiation Oncology for treating cancer patients. Dr. Zhang will use his career  path from engineering to radiation oncology as an example to lead the  discussions.