Lab Members

Jinzhong Yang, Ph.D.
Assistant Professor - Radiation Physics

Ph.D. - Electrical Engineering, Lehigh University, PA (2006)
M.S. - Electrical Engineering, University of Science and Technology of China, Hefei, China (2001)
B.S. - Electrical Engineering, University of Science and Technology of China, Hefei, China (1998)

Jinzhong earned his Ph.D. in Electrical Engineering with research focusing on the fundamental algorithm development of image registration and fusion methodologies. He completed his postdoctoral training at University of Pennsylvania, where he developed deformable image registration methods to analyze diffusion tensor images for brain disorder diagnosis. In 2008, he joined MD Anderson Cancer Center as a Sr. Computational Scientist and concentrated his research on atlas-based segmentation and deformable image registration to improve radiation treatment planning and image-guided adaptive radiotherapy. In 2015, he became a Research Assistant Professor and in 2019 a tenure-track Assistant Professor of Radiation Physics at MD Anderson. He is the physics lead of the MR-Linac program at MD Anderson since 2020.

His major research interest is the development of novel image segmentation and deformable registration approaches for radiation oncology applications. He is also interested in radiation treatment related geometric and dosimetric uncertainties, quantitative imaging biomarker for radiation treatment outcome modeling and prediction (Radiomics) and novel imaging methodologies and applications in radiotherapy.

For more information, please visit his MD Anderson profile.

Yao Ding, Ph.D.
Assistant Professor – Radiation Physics

Prior to joining MD Anderson, Yao completed a Ph.D. in Radiological Sciences (clinical MRI physics) at the UT Southwestern Medical Center at Dallas in 2012. He then took a five-year postdoctoral fellow position in Imaging Physics and developed multi-parametric MR imaging methodologies and applications in radiotherapy. In 2017, he transferred to Radiation Department providing MR physics support as a Research Scientist and a Research Instructor. In 2022, he became a Clinical Assistant Professor in the Physics Infrastructure Core Group.

In addition to his clinical responsibilities on routine MR physics and Therapeutic Radiation Physics, his research interest is the development of novel image-guided techniques for radiation treatment based on the individual patient’s response, with the goal of improving oncologic outcomes and reducing toxicity to normal tissues. This involves the integration of multi-parametric MR imaging methodology development, imaging biomarkers identification and characterization and treatment outcomes assessment.

Mustefa Mohammedsaid, M.S., MR RT
Radiation Therapist – Radiation Oncology

M.S. – Radiologic Sciences, MD Anderson (2019)
B.S. – Radiation Therapy, MD Anderson (2011)

Mustefa has been a radiation therapist at MD Anderson for more than 16 years. As a certified radiation therapist and MRI technologist, he has been working on several MRLinac research projects.

As part of MD Anderson’s global outreach effort, he has lectured and clinically trained radiation therapists in developing countries.
 

Yao Zhao, M.S.
Graduate Research Assistant

M.S. - Medical Physics, Duke University, NC (2019)
B.S. - Physics, Lanzhou University, China (2016)

Yao’s research interests are focused on the development of deep learning techniques for radiation therapy treatment planning. His M.S. research was applying deep learning methods to augment CBCT image quality. His current research focuses on developing deep learning tools to facilitate the online plan adaptation for MR-guided stereotactic ablative radiotherapy (SABR) of head and neck cancer

Xinru Chen
Graduate Research Assistant

M.S. - Medical Physics, Duke University, NC (2020)
B.S. - Nuclear Engineering, Tsinghua University, China (2012)

Xinru is interested in radiomics and deep learning-based techniques in radiotherapy. His M.S. research focused on quantitative lung ventilation radiomics. He is currently working on synthetic CT generation, auto-segmentation and cardiac toxicity prediction.