Jingxi L. Weng, Ph.D.
CLINICAL ASSISTANT PROFESSOR
Jingxi L. Weng is not currently accepting new patients. For assistance finding a UC Davis doctor, please call 800-2-UCDAVIS (800-282-3284).
Locations and Contact
UC Davis Comprehensive Cancer Center
UC Davis Comprehensive Cancer Center
4501 X St.
Sacramento, CA 95817
Philosophy of Care
Dr. Weng believes that high-quality radiation therapy requires a combination of precision, patient safety, and close collaboration among physicians, physicists, dosimetrists, radiation therapists, and other members of the care team. His goal is to apply rigorous physics and technology to ensure that each patient receives safe, accurate, and individualized treatment.
Clinical Interests
Dr. Weng’s clinical interests include advanced radiation therapy techniques, image-guided and adaptive radiation therapy, motion management, and treatment planning. He is particularly interested in improving treatment accuracy and safety through advanced imaging, quality assurance, and emerging radiation therapy technologies.
Research/Academic Interests
Dr. Weng’s research focuses on the application of artificial intelligence and advanced medical imaging to radiation therapy. His interests include deep learning for medical image and motion prediction, MRI-guided radiation therapy, respiratory motion management, image-guided and adaptive radiation therapy, and AI-based radiation treatment planning and dose prediction.
Division
Radiation Oncology
Undergraduate School
B.S. Applied Physics, Nankai University, China, 2017
Other School
M.S. Medical Physics, Duke University, 2019
Other School
Ph.D., Medical Physics, University of Florida, 2024
Residency
Therapeutics Medical Physics, University of Florida, 2024-2026
1. Weng J, Anas M, Smith KE, Samant SS. A 4D convLSTM model for volumetric prediction of abdominal motion using cine-MR imaging, Pending Submission
2. Weng J, Bhupathiraju SHV, Samant T, Dresner A, Wu J, Samant SS. Convolutional LSTM Model for cine image prediction of abdominal motion. Physics in Medicine & Biology. 2024;69(8).
3. Weng J, Wildman-Tobriner B, Buda M, et al. Deep learning for classification of thyroid nodules on ultrasound: validation on an independent dataset. Clin Imaging. 2023;99:60-66.
4. Saha A, Harowicz MR, Grimm LJ, Weng J, et al. Dynamic contrast-enhanced magnetic resonance images of breast cancer patients with tumor locations. The Cancer Imaging Archive. 2021.
5. Lafata KJ, Corradetti MN, Gao J, Jacobs CD, Weng J, et al. Radiogenomic analysis of locally
advanced lung cancer based on CT imaging and intratreatment changes in Cell-Free DNA. Radiology: Imaging Cancer. 2021;3(4).