Lab Members

Caroline Chung, M.D., M.S., F.R.C.P.C., C.I.P.

View Dr. Chung's faculty profile

Principal Investigator
Associate Professor, Radiation Oncology, Division of Radiation Oncology
Vice President, Chief Data Officer
CChung3@MDAnderson.org

Dr. Chung is vice president and chief data officer and director of Data Science Development and Implementation of the Institute of Data Science in Oncology (IDSO) at MD Anderson Cancer Center. She is a clinician-scientist and an associate professor in Radiation Oncology and Diagnostic Imaging. She has a clinical practice focused on CNS malignancies and a computational imaging lab focused on quantitative imaging and modeling to detect and characterize tumors and toxicities of treatment to enable personalized cancer treatment. Motivated by challenges observed in her own clinical and research pursuits, Dr. Chung has developed and leads institutional efforts to enable quantitative measurements for clinically impactful utilization and interpretation of data through a collaborative team science approach, including the Tumor Measurement Initiative (TMI) at MD Anderson. Internationally, Dr. Chung leads several multidisciplinary efforts to improve the generation and utilization of high quality, quantitative data to drive research and impact clinical practice, including her role as Vice Chair of the Radiological Society of North America (RSNA) Quantitative Imaging Biomarker Alliance (QIBA), Co-Chair of the Quantitative Imaging for Assessment of Response in Oncology Committee of the International Commission on Radiation Units and Measurements (ICRU) and National Academies of Sciences, Engineering, and Medicine (NASEM)-appointed committee addressing Foundational Research Gaps and Future Directions for DigitalTwins. Beyond her clinical, research and administrative roles, Dr. Chung enjoys serving as an active educator and mentor with a passion to support the growth of participation in STEM, including her role as chair of Women in Cancer, a not-for-profit organization that is committed to advancing cancer care by encouraging the growth, leadership and connectivity of current and future oncologists, trainees and medical researchers. 

Andrew Elliott, Ph.D.
Data Scientist
Andrew.Elliott@MDAnderson.org

Dr. Elliott’s research focuses on developing methodologies and algorithms for medical image analysis. He is testing different machine learning and other computational algorithms for the imaging core lab within the ROSI Advanced Imaging Initiative. 

Bikash Panthi, Ph.D. 
Postdoctoral Fellow 
BPanthi@MDAnderson.org 
 
Dr. Panthi’s research delves into advanced image processing techniques, radiomics and machine learning to distill meaningful information from medical images. His focus centers on utilizing these techniques to identify predictive biomarkers and imaging attributes that facilitate precise evaluation of treatment responses in cancer patients, aiming to enhance diagnostic accuracy and patient care. 

Eleni Konstantinopoulou, Ph.D.
Research Laboratory Coordinator

Dr. Konstantinopoulou has a diverse background in biomedical imaging and image analysis. In the Chung Lab, she provides supervision and technical management of ongoing research projects and operations, whilst ensuring compliance with federal, state and institutional regulations. Additionally, Dr. Konstantinopoulou implements best practices for project/data management, guided by current technological trends, and the future technologies that may become available to support the ever-evolving research needs of the Chung Lab. 

Hesham Alghodhaifi, Ph.D. 
Postdoctoral Fellow
HAlghodhaifi@MDAnderson.org 
 
Leveraging artificial intelligence to advance cancer research is at the core of Dr. Alghodhaifi's work. He develops computational pipelines and statistical models to improve cancer diagnosis, prognosis, treatment and early detection. His research focuses on identifying new biomarkers that can predict cancer progression and response to therapies. Additionally, Dr. Alghodhaifi implements novel machine learning techniques to extract insights from medical imaging data. The overarching goal is to harness the predictive power of AI to unlock new knowledge and enhance patient outcomes in oncology. Through multidisciplinary research at the intersection of machine learning, statistics, and radiomics, he aims to translate AI capabilities into real-world clinical impact. 

Holly Langshaw
Research Assistant I
HELangshaw@MDAnderson.org

Ms. Langshaw operates and scripts RayStation and engages in administrative work for the lab. She also curates and maintains lab databases and helps facilitate collaborative data sharing.

Michael Rooney, M.D. 
Resident 
MKRooney@MDAnderson.org 
 
Dr. Rooney is a resident in the Clinical Radiation Oncology program at MD Anderson. He is interested in data science, mechanistic modelling of treatment responses and toxicities, and methods for causal inference using observational data. In the Chung Lab, Dr. Rooney’s primary areas of interest are related to quantitative imaging biomarkers and digital twins to personalize therapeutic strategies. 

Sara Thrower, Ph.D.
Assistant Professor 

Victoria White
Clinical Data Abstractor 
VHWhite@MDAnderson.org 

Ms. White works to abstract information from patient records and collaborates with the Tumor Measurement Initiative (TMI) to advance cancer treatment. She annotates and contours MRI images for use in TMI automation (including normal tissue anatomy and tumor regions), manages image databases to obtain patient records, and maintains appropriate documentation regarding protocols and data. Her research interests include finding non-invasive and innovative treatments for cancer and degenerative diseases, as well as pharmaceutical discovery science to further extend patient longevity. 

Wasif Talpur, M.D.
Clinical Research Program Coordinator 
WTalpur@mdanderson.org 

 Dr. Talpur is a medical graduate in his fourth year at MD Anderson and second in the Chung Lab. His primary focus of research is studying quality of life outcomes in patients with primary brain tumors. He currently works on enrolling and data gathering for patients on the GBM Adaptive and NASA cognitive clinical trials.