Lab Members

Laurence Court, Ph.D.
Associate Professor - Radiation Physics and Imaging Physics departments

Ph.D. in Physics (digital mammography), University College London, United Kingdom (1995)
B.Sc. in Physics with Medical Physics, University College London, United Kingdom (1992)

After completing his doctorate on digital mammography system design in the UK, Laurence received a fellowship from the Daiwa Anglo-Japanese Foundation, and moved to Japan for work experience with Sony.  He then stayed in Japan for six years, ending up working in the Digital X-ray System Development Group at Canon Inc.

He then took a two-year postdoctoral fellow position with Lei Dong, Ph.D., at MD Anderson, where he worked on a brand new CT-on-rails image-guidance system, before joining Brigham & Women’s Hospital / Dana-Farber Cancer Center (Harvard Medical School) as a staff physicist. There, he had a variety of roles, including setting up the physics aspects of the head and neck IMRT service and leadership of two new satellite locations.

In 2010, Laurence was hired back at MD Anderson, where he joined the Physics Infrastructure Group. In addition to his clinical responsibilities, he now runs a research group of 24 faculty, staff and graduate students. His current research interests are (1) the use of images to quantify or predict treatment response (tumors and normal tissue), and (2) approaches to improve the availability of cancer treatments in low- and middle-resource regions of the world.

For more information, please visit his MD Anderson profile.

Lifei Joy Zhang, Ph.D.
Manager, Scientific Computing Research - Radiation Physics

Ph.D. in Information Processing, Chinese Academy of Sciences, China (2003)
M.S. in Electrical Engineering, Institute of Chinese Aerospace, China (2000)
B.S. in Electrical Engineering, Luoyang Institute of Technology, China (1997)

Joy’s research interests focus on applying computer science techniques into radiation therapy research and transferring research outcome into clinical applications for the goal of improving the quality of patient care. In the past, she designed and developed an online high-resolution targeting and positioning system (CAT) to make it possible for radiation therapists to accurately and efficiently target and position patients during daily treatments. To facilitate data exchange robustly among the different treatment planning systems (TPS), she implemented TPS data conversion software so researchers can easily exchange data from one TPS to another TPS. She has also researched patient’s intra-fractional and inter-fractional changes during the course of treatment, investigated the necessity and eligibility of adaptive image-guided radiotherapy (ART) and further implemented ART infrastructure in the department. Aiming to improve efficiency and accuracy of clinical practice, she has designed and implemented many clinical-oriented softwares such as high-resolution DRR generator, PET SUV convertor, OBI Add-Iso software, 4DCT viewer, beam-specific PTV software and small animal treatment planning system. She routinely provides support for projects from of both clinicians and graduate students.

The current focus of her work is the development of the Radiation Planning Assistant, including algorithm development and system integration.

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

Ph.D. in Electrical Engineering, Lehigh University, PA (2006)
M.S. in Electrical Engineering, University of Science and Technology of China, Hefei, China (2001)
B.S. in 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 as a senior 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 an Assistant Professor at MD Anderson.

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, texture features 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.

Deborah Mann
Program Manager - Radiation Physics

Deborah joined the Radiation Physics department in 2011 and the Court Lab in 2017.  She serves as a point of contact and link between lab members, internal departments and external parties including vendors and collaborating institutions. She manages administrative needs, analyzes and improves office processes and policies, and ensures that the lab operates smoothly.

Callistus Nguyen, Ph.D.
Senior Data Scientist - Radiation Physics

Ph.D. in Biomedical Engineering, Virginia Tech - Wake Forest University, School of Biomedical Engineering and Sciences, VA (2017)
M.S. in Biomedical Engineering, Virginia Tech - Wake Forest University, School of Biomedical Engineering and Sciences, VA (2014)
B.S. in Biophysics, Wake Forest University, NC (2010)

Callistus earned his Ph.D. in Biomedical Engineering with a concentration in Medical Physics. His research focused on developing a predictive maintenance methodology for linear accelerators by utilizing statistical process control techniques on RapidArc performance parameters. He completed his postdoctoral training at MD Anderson, where he worked on projects related to the application of radiomics on cancer treatment and prevention. In 2018, he joined MD Anderson as a Research Engineer and developed the tools, workflow and documentation to support automation research and translate such work into the clinic. In 2021, he became a Computational Scientist.

His major research is to provide technical support for clinical research and developmental projects by developing new algorithms, communicating with the industry partners to improve computational infrastructure, and implementing new software for dose computations, treatment planning, measurements and image processing. He also applies computer science techniques into radiation therapy research and transfers research outcomes into clinical applications for the goal of improving the quality of patient care. He routinely provides support for projects from both clinicians and graduate students.

Wenhua Cao, Ph.D.
Assistant Professor - Radiation Physics

Ph.D. in Industrial Engineering, University of Houston, TX (2011)
B.S. in Transportation Engineering, South China University of Technology, Guangzhou, China (2003)

Wenhua was trained in operations research and optimization. After obtaining his Ph.D., he became a research assistant professor at the University of Houston. He developed various methods for optimizing proton therapy during his collaboration with physicists from MD Anderson before joining MD Anderson in 2016. He started developing novel optimization approaches to manage physical and biological uncertainties in proton therapy that led to new clinical trials. His current research focuses on particle therapy, automated treatment planning and modelling of radiation-induced toxicities.

Tucker Netherton, Ph.D., D.M.P.
Assistant Professor - Radiation Physics

Tucker received his Doctorate of Medical Physics degree and completed a clinical residency in therapeutic medical physics at Vanderbilt University in 2016. Pursuing further education, he entered the Ph.D. program at The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences with Dr. Laurence Court as his advisor. His early graduate work was centered around the commissioning of new external beam treatment devices. His thesis focused on applying machine and deep learning to vertebral body labeling and automatic treatment planning for spinal radiotherapy.

In May of 2021, he became an Assistant Professor in the Radiation Physics Department at MD Anderson Cancer Center within the head and neck, lymphoma, melanoma, and sarcoma service. His research involves developing tools to 1) expedite clinical processes for automatic medical image segmentation of normal and cancerous tissues, 2) predict treatment planning errors that pose risks to patient care, and 3) aid decision making in radiotherapy treatment planning.

He currently serves as a faculty researcher on the Radiation Planning Assistant team and specializes in applications of machine and deep learning to treatment planning and image segmentation. Tucker is passionate about research, clinical work and graduate education.

Christine Chung, M.S., C.M.D.
Research Dosimetrist - Radiation Physics

M.S. in Radiologic Sciences, The University of Texas MD Anderson Cancer Center (2021)
B.S. in Medical Dosimetry, The University of Texas MD Anderson Cancer Center (2019)
B.S. in Biology, The University of Texas at Austin (2013)

Christine’s past research experience was in translational and clinical research in gynecologic oncology at MD Anderson, and her past clinical experience was as a medical dosimetrist at MD Anderson’s Proton Therapy Center. Her current research focuses on developing high-quality automated treatment plans for new anatomical sites for use in the Radiation Planning Assistant and Varian ePeerReview projects.

Raphael Douglas
Senior Research Assistant - Radiation Physics

B.S. in Physics, Davidson College, NC (2017)

Raphael's undergraduate research focused on using automation to eliminate mode-hopping in a Coherent 899-21 Ring Laser. Currently, he is working on testing the Radiation Planning Assistant software for quality assurance and assisting with the various deep-learning projects within the lab.

Pavel Govyadinov, Ph.D.
Data Scientist - Radiation Physics

Ph.D. in Computer Science (Visualization), University of Houston, TX (2019)
M.S. in Computer Information Technology (Parallel Computing), University of Oregon (2014)
B.S. in Physics, University of Oregon (2011)

Pavel earned his Ph.D. with research focusing on segmentation, visualization and analysis of microvascular data. Post-graduation, Pavel was accepted as a postdoctoral fellow for the National Library of Medicine’s Program in Biomedical Informatics and continued the fellowship for the maximum allowed two years in a project focusing on exploiting graph structures to generating synthetic simplified-but-realistic microvascular data for next generation bio-printing.

In 2022, Pavel joined MD Anderson Cancer Center as a computational scientist and concentrates his research on developing method to improve the quality and robustness of the RPA platform through exploitation of synthetic data using his previous research and industry experience.

Jean Guma-De La Vega
Research Assistant I - Radiation Physics

B.S. in Mathematics with minor in Computer Science, Pace University, NY (2021)

With a background in mathematics and computer science, Jean's interests lie in their general application within the various fields of physics. Currently, Jean is working on assisting in tasks within the deep-learning projects in the lab.

Meena Khan, C.M.D.
Research Dosimetrist - Radiation Physics

B.S. in Medical Dosimetry, The University of Texas MD Anderson Cancer Center (2005)

Meena is a Certified Medical Dosimetrist with clinical experience in photons and protons.  She has worked on several treatment planning systems in different environments.  Her current interest within the group focuses on the development of RapidPlan models for all treatment planning sites.

Alexandra (Alex) Leone, M.B.S.
Research Assistant II - Radiation Physics

M.B.S. in Biomedical Sciences, Nova Southeastern University, FL (2021)
B.S. in Physics, The University of Alabama (2020)

Alex's research interests focus on the intersection of patient care and predicting patient outcomes to radiotherapy treatment. Her current project includes developing a score card to evaluate physician’s treatment plans.

Raymond Mumme
Senior Research Assistant - Radiation Physics

B.S. in Physics and Chemistry, University of Notre Dame, IN (2015)

Raymond's past research at CERN involved optimizing Monte Carlo dosimetry calculation methods in treatment planning for thyroid cancer. His current projects involve stress-testing and aiding in the development of various deep learning models for automated segmentation of structures throughout the body for use by the RPA website and the clinic. He specializes in morphological image processing, data quality assurance, image conversion and troubleshooting.

Saurabh Nair, M.S.
Research Assistant II - Radiation Physics

M.S. in Biomedical Engineering, The University of Texas at Arlington (2021)
B. Tech. in Biomedical Engineering, DY Patil University, Navi Mumbai, India (2018)

Saurabh’s graduate research involved working in the optical imaging domain studying brain activation using functional near-infrared spectroscopy. His current research focuses on predicting the toxic effects of radiation therapy using machine learning models.

Josiane Pafeng, Ph.D.
Senior Data Scientist - Radiation Physics

Ph.D. in Geophysics, University of Wyoming (2017)
M.S. in Earth System Physics, International Centre for Theoretical Physics (ICTP), Trieste, Italy (2011)
Maitrise (1st year of M.S.) in Physics, University of Douala, Cameroon (2007)
B.S. in Physics, University of Douala, Cameroon (2006)

Josiane's Ph.D. research focused on using geophysical data (seismic and electromagnetic) and multi-physics analysis to integrate prestack waveform inversion and rock physics inversion for carbon dioxide (CO₂) reservoir characterization of a future CO₂ sequestration site. She later worked at ExxonMobil as a Geoscientist developing a modeling workflow for optimal seismic data quality of complex oil fields by integrating various types of geophysical tools and data. After that, she pivoted to become a Data Analyst at OhmConnect, a residential energy flexibility provider where she built data pipelines to simplify device data analytics and reporting of key metrics.She joined MD Anderson in June 2023 as a senior data scientist and focuses her work on implementing deep learning models for multiple dose levels prediction and integrating them into the Radiation Planning Assistant (RPA), for the goal of improving patient quality care in low- and middle-income countries.

Carlos Sjogreen, Ph.D.
Research Assistant II - Radiation Physics

Ph.D. in Physics, University of Houston, TX (2023)
M.Sc. in Physics, Universidad Nacional de Colombia, Colombia (2015)
Mechanical Engineer, Universidad Industrial de Santander, Colombia (2003)

In his master's research, Carlos studied nanotechnology, focusing on the characterization of oxygen nanobubbles in NaCl solutions. His research examines the interplay of nanobubble size, concentration, pH, and temperature over time. During his doctoral studies, Carlos addressed the challenges of delineating clinical target volumes (CTVs) for nasopharyngeal cancer radiotherapy. Responding to disease variability, he developed an auto-contouring tool that combines artificial intelligence, deep learning segmentation, and conventional programming tailored for the NRG-HN001 protocol. This tool also adapts to the RTOG-0225 protocol when needed.

Kristina Smith
Administrative Coordinator - Radiation Physics

Kristina joined the Radiation Physics department in 2018 and Court Lab in 2020. She serves as the administrative support for the Court lab.

Hana Baroudi, M.S.
Graduate Research Assistant

M.S. in Physics, American University of Beirut
B.S. in Physics, Beirut Arab University

Hana’s research interests include radiation therapy for breast cancer. She is currently working on automating the treatment process for breast cancer radiotherapy using machine learning tools. Hana is also interested in working on correlating breast radiotherapy induced toxicity to dosimetric and clinical predictors.

Xinru Chen, M.S.
Graduate Research Assistant

M.S. in Medical Physics, Duke University, NC (2020)
B.S. in 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 and auto-segmentation in MRI.

Daniel El Basha
Graduate Research Assistant

B.S. in Biomedical Engineering, University of Florida (2019)

Daniel is working towards a Ph.D. in medical physics at the MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences. His research interests are computational modeling and deep learning with applications toward addressing crippling diseases. He is currently working to specifically address the automation and optimization of prostate cancer treatment planning using deep learning models.

Skylar Gay
Graduate Research Assistant

B.S. in Physics, Houston Baptist University, TX (2020)

Skylar's research interest is in using deep learning to provide rapid radiotherapy planning and improve quality of life in low-resource clinical and palliative care settings. His current focus is on automating head-and-neck cancer treatment planning.

Barbara Marquez
Graduate Research Assistant

B.A. in Physics, Mount Holyoke College, MA (2019)

Barbara's research interests include leveraging automation to provide wide-spread access to a comprehensive treatment planning system for under-resourced countries. Her current project aims to automate and optimize peer review of contours for radiation therapy. Barbara is also interested in the enhancement of the full value of physics in radiation oncology practice.

Ramon Salazar, Ph.D.
Postdoctoral Fellow

Ph.D. in Experimental Particle Physics, University of Texas at Austin (2021)
B.S. in Physics, University of Texas at Austin (2010)

Ramon earned his Ph.D. in experimental particle physics with a focus on neutrinoless double beta decay searches. His graduate work involved the research, development, construction, and installation of two calibration systems designed for a detector searching for that specific decay, and he also participated in many of the detector building operations. His input into the calibration systems involved manipulating calibration sources, light emitting diodes, fiber optic cables, plastic scintillator blocks, and electrical circuits. In 2021, he became a postdoctoral research fellow at MD Anderson Cancer Center.

He is currently active in toxicity modeling research using machine learning approaches, and he is studying the effects on NTCP models from data obtained through deep learning segmentation of organs at risk.