Â鶹ӳ»­

Laurence Court, Ph.D.
Professor?¨C 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 .

Jinzhong Yang, Ph.D.
Assistant Professor ¨C 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.

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 .

Tucker Netherton, Ph.D., D.M.P.
Assistant Professor?¨C 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 MD Anderson Cancer Center UTHealth Houston 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 2021, he became an assistant professor in Radiation Physics at MD Anderson?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.

For more information, please visit?.

Lifei Joy Zhang, Ph.D.
Manager, Scientific Computing Research ¨C 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 a small animal treatment planning system. She routinely provides support for projects from 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.

Callistus Nguyen, Ph.D.
Senior Data Scientist ¨C 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.

Kristina Smith
Associate Program Manager ¨C Radiation Physics

Kristina joined the department of Radiation Physics in 2018 and became part of the Court Lab in 2020, where she now leads quality and regulatory efforts for the FDA-cleared RPA medical device. Kristina oversees the Quality Management System (QMS), ensuring compliance with FDA and ISO 13485 standards, and manages risk assessments, audits, regulatory submissions, complaint handling and CAPA oversight. She works closely with cross-functional teams to support the safe, effective and compliant use of the RPA in clinical settings worldwide.

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

M.S. in Radiologic Sciences, Â鶹ӳ»­ MD Anderson Cancer Center (2021)
B.S. in Medical Dosimetry, Â鶹ӳ»­ MD Anderson Cancer Center (2019)
B.S. in Biology, Â鶹ӳ»­ 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 ¨C 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 ¨C 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 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.

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

B.S. in Medical Dosimetry, Â鶹ӳ»­ 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.

Saurabh Nair, M.S.
Assistant Data Scientist ¨C Radiation Physics

M.S. in Biomedical Engineering, Â鶹ӳ»­ 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 ¨C 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.

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.