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Dan Nguyen, Ph.D.

Dan Nguyen, Ph.D.

Associate Professor

School
Medical School
Department
Radiation Oncology
Graduate Programs
Biomedical Engineering
  • Biography

    Download Curriculum Vitae

    Dan Nguyen, Ph.D., is a scientist with expertise in radiation therapy treatment planning, deep learning, and optimization techniques and algorithms. He completed his Ph.D. in Biomedical Physics in 2017 at the University of California Los Angeles (UCLA), where he worked extensively on 4π Radiotherapy, Fluence Map Optimization, and Direct Aperture Optimization techniques under the guidance and mentorship of Dr. Ke Sheng.

    Dr. Nguyen was recruited to the Division of Medical Physics and Engineering, Department of Radiation Oncology at UT Southwestern in 2017 as a faculty member. He was a founding member of the multiple-investigator lab called the Medical Artificial Intelligence and Automation (MAIA) Laboratory, which was focused to innovate, develop, and apply artificial intelligence technologies to empower clinicians—especially those with less experience or limited resources—for improved patient care. He works very closely with Dr. Steve Jiang in researching and applying deep learning technologies to various facets of radiotherapy, including treatment planning, medical imaging, and outcome prediction.

  • Education
    Undergraduate
    University of Texas-Austin (2012), Physics
    Graduate School
    Uni of California (UCLA) (2015), Biomedical Physics
    Graduate School
    Uni of California (UCLA) (2017), Biomedical Physics
  • Research Interest
    • Artificial Intelligence
    • Deep Learning
    • Optimization Techniques and Algorithms
    • Radiation Therapy
  • Publications
    Progressive auto-segmentation for cone-beam computed tomography-based online adaptive radiotherapy
    Zhao H, Liang X, Meng B, Dohopolski M, Choi B, Cai B, Lin MH, Bai T, Nguyen D, Jiang S Physics and Imaging in Radiation Oncology 2024 Jul 31
    Performance deterioration of deep learning models after clinical deployment: a case study with auto-segmentation for definitive prostate cancer radiotherapy
    Wang B, Dohopolski M, Bai T, Wu J, Hannan R, Desai N, Garant A, Yang D, Nguyen D, Lin MH, Timmerman R, Wang X, Jiang SB Machine Learning: Science and Technology 2024 Jun 5
    Multimodal radiotherapy dose prediction using a multi-task deep learning model
    Maniscalco A, Mathew E, Parsons D, Visak J, Arbab M, Alluri P, Li X, Wandrey N, Lin MH, Rahimi A, Jiang S, Nguyen D Medical physics 2024 Jun 51 3932-3949
    Segmentation of liver and liver lesions using deep learning
    Fallahpoor M, Nguyen D, Montahaei E, Hosseini A, Nikbakhtian S, Naseri M, Salahshour F, Farzanefar S, Abbasi M Physical and Engineering Sciences in Medicine 2024 Jun 47 611-619
    Deep learning based automatic segmentation of the Internal Pudendal Artery in definitive radiotherapy treatment planning of localized prostate cancer
    Balagopal A, Dohopolski M, Suk Kwon Y, Montalvo S, Morgan H, Bai T, Nguyen D, Liang X, Zhong X, Lin MH, Desai N, Jiang S Physics and Imaging in Radiation Oncology 2024 Apr 30
    Simulation and pre-planning omitted radiotherapy (SPORT): a feasibility study for prostate cancer
    Zhuang T, Parsons D, Desai N, Gibbard G, Keilty D, Lin MH, Cai B, Nguyen D, Chiu T, Godley A, Pompos A, Jiang S Biomedical Physics and Engineering Express 2024 Mar 10
    Can input reconstruction be used to directly estimate uncertainty of a dose prediction U-Net model?
    Huet-Dastarac M, Nguyen D, Longton E, Jiang S, Lee J, Montero AB Medical physics 2024
    Single patient learning for adaptive radiotherapy dose prediction
    Maniscalco A, Liang X, Lin MH, Jiang S, Nguyen D Medical physics 2023 Dec 50 7324-7337
    Intentional deep overfit learning for patient-specific dose predictions in adaptive radiotherapy
    Maniscalco A, Liang X, Lin MH, Jiang S, Nguyen D Medical physics 2023 Sep 50 5354-5363
    Reinforcement learning for radiation therapy planning and image processing
    Nguyen D, Shen C, Jia X, Jiang S 2023 Aug 87-97
  • Professional Associations/Affiliations
    • American Association of Physicists in Medicine (2013)