Stanford University


Showing 121-140 of 177 Results

  • Jinghong Penny Peng

    Jinghong Penny Peng

    Clinical Instructor, Radiation Oncology - Radiation Physics

    Current Research and Scholarly Interests1. IMRT Treatment planning
    2. IGRT Radiation Therapy
    3. Real time prostate implant
    4. 4D CT and Respiratory Gating Radiation Therapy
    5. HDR for breast cancer and GYN cancer
    6. Xoft Electronic Brachytherapy

  • Guillem Pratx

    Guillem Pratx

    Associate Professor of Radiation Oncology (Radiation Physics)

    Current Research and Scholarly InterestsThe Physical Oncology Lab is interested in making a lasting impact on translational cancer research by building novel physical tools and methods.

  • Yushen Qian, MD

    Yushen Qian, MD

    Clinical Associate Professor, Radiation Oncology - Radiation Therapy

    BioDr. Qian is a board-certified radiation oncologist and a Clinical Associate Professor in the Stanford University School of Medicine, Department of Radiation Oncology.

    In his clinical practice, he sub-specializes in genitourinary (including prostate and bladder cancer) and Head and Neck malignancies, but also treats a broad spectrum of other disease subsites including lung/thoracic, gastrointestinal, brain, lymphoma, and breast tumors. For each patient, he develops a comprehensive, individualized, and compassionate care plan customized to individual needs. His goal is to deliver the most effective cancer treatment to help patients enjoy the best possible health and quality of life.

    In addition to his clinical practice, Dr. Qian serves as the Medical Director of Radiation Oncology at Stanford South Bay Cancer Center. He also serves as the Radiation Oncology Network Director of Clinical Research and has spearheaded opening of multiple NRG Oncology clinical trials at Stanford South Bay Cancer Center.

    Dr. Qian is also actively involved in the Stanford Radiation Oncology residency program. He created and oversees a monthly mentorship roundtable series to assist residents with multiple aspects of their clinical training and career progression.

    Outside of work, Dr. Qian enjoys spending time with his family and exploring the great outdoors of Northern California.

  • Chenhui Qiu

    Chenhui Qiu

    Affiliate, Radiation Oncology - Radiation Therapy

    BioChenhui Qiu majored in Biomedical Engineering (BME) and received his Ph.D. from Zhejiang University in September 2019.

    From January 2020 to December 2021, he worked as a Postdoctoral Researcher and Research Associate in the Department of Applied Mathematics, School of Mathematical Sciences, Zhejiang University.

    From August 2022 to October 2024, he was a Postdoctoral Scholar in the Department of Radiation Oncology at School of Medicine, Stanford University.

    From October 2024 to August 2025, he was a Postdoctoral Scholar in the Department of Pathology at School of Medicine, Stanford University.

    Since August 2025, he has been a Visiting Instructor/Postdoc in the Department of Radiation Oncology at School of Medicine, Stanford University.

    His research interests include (a) AI-enabled medical imaging and image analysis; (b) AI-powered cancer detection, diagnosis, and prognosis; (c) radiation oncology, radiology physics, dose calculation (Monte Carlo simulation); (d) treatment planning (inverse optimization), radiation dose delivery and measurement.

  • Elham Rahimy, MD

    Elham Rahimy, MD

    Clinical Assistant Professor, Radiation Oncology - Radiation Therapy

    BioDr. Rahimy is a radiation oncologist who treats patients with brain, spine, gastrointestinal, and metastatic tumors. She received her medical training at Yale, followed by residency at Stanford. She is a Clinical Assistant Professor with the Stanford Department of Radiation Oncology.

    Dr. Rahimy's technical expertise includes CyberKnife Radiosurgery and MRI-guided adaptive planning. She is also actively involved in radiation oncology research and clinical trials. Her interests include improving patient and resident education, and enhancing patient quality of life and survivorship. She leads quality initiatives as a Quality Physician Improvement Leader, and serves as the Medical Student Clerkship Director.

  • Yuan James Rao, MD

    Yuan James Rao, MD

    Associate Professor of Radiation Oncology (Radiation Therapy)

    BioDr. Yuan James Rao is an Associate Professor of Radiation Oncology, and Co-Director of Proton Therapy at Stanford University. In 2026, Dr. Rao co-led the team at Stanford that treated the world’s first pediatric and adult patients with ultra-compact upright proton therapy. Dr. Rao’s professional goal is to develop the world’s most advanced proton therapy program at Stanford University.

    Proton therapy is a remarkable form of radiation treatment that uses heavy charged particles (protons) accelerated to approximately two-thirds the speed of light. The unique physics of protons allows the radiation to stop within a defined distance in the body, whereas standard x-ray therapy continues to deposit radiation after treating the tumor (known as “exit dose”). By reducing exit dose, protons may reduce normal tissue exposure to radiation, which is particularly beneficial for children and young adults with cancer, and patients requiring a second course of radiation. Dr. Rao currently coordinates the Stanford Radiation Oncology Department’s clinical, research, and education efforts related to proton therapy.

    Dr. Rao’s clinical practice focuses on the care of patients with Head and Neck cancer, and Thoracic cancers. His goal is to provide the highest quality care to his patients, using the most appropriate technology. This may include proton therapy but also potentially other techniques such as intensity modulated radiation therapy (IMRT), stereotactic body radiation (SBRT), MR-guided radiotherapy, 3D conformal radiotherapy, or other technologies. Nearly all radiation technologies are available at Stanford University, and thus Dr. Rao and his Radiation Oncology colleagues are well positioned to choose the best treatment for every patient.

    Dr. Rao trained at the prestigious Mallinckrodt Institute of Radiology at Washington University in St. Louis, and during residency was among the first physicians in the world to use the Mevion S250 proton therapy device and the ViewRay MRI-guided radiotherapy device. Dr. Rao has traveled to UCSF, MD Anderson, Johns Hopkins University, University of Pennsylvania, Medical University of Vienna, and University Medical Center Utrecht to learn about various advanced radiotherapy techniques including MR-guided radiotherapy, brachytherapy, and proton therapy.

    Prior to his role at Stanford, Dr. Rao was a physician at George Washington University in Washington, DC and held the positions of Associate Professor of Radiation Oncology and Biomedical Engineering (by courtesy), and Assistant Professor of Neurosurgery (by courtesy). He was also the founding Director of Brachytherapy, and implemented programs for gyn, head and neck, prostate, and skin radiation implants using high dose rate (HDR) techniques. He was honored as a Washingtonian Top Doctor for each of the years that he practiced in DC, and Dr. Rao has treated members of Congress with radiotherapy (public information).

    Dr. Rao is a prolific researcher with more than 50 peer-reviewed publications. He is an expert in proton therapy, head and neck cancer, thorax cancers, gyn cancers, GU cancers, brachytherapy, artificial intelligence, machine learning, image analysis and large database "big data." He is co-author of the ‘Endometrial Cancer’ chapter of the 8th edition of Perez and Brady’s Principles and Practice of Radiation Oncology, the world’s most widely used reference textbook in the field. He regularly gives invited talks nationally and internationally. Dr. Rao has been grant funded by the American Cancer Society.

    Dr. Rao is a respected educator and mentor, and has taught numerous engineering/physics students, medical students and residents; many of whom have gone on to become successful physicists, scientists, entrepreneurs, and physicians.

  • Bijie Ren

    Bijie Ren

    Visiting Instructor, Radiation Oncology - Radiation Physics

    BioBijie Ren is a quantitative biologist as well as a pro bono academic advisor for the SATORI Institute for Complexity and Emergence (SICE). Inspired by electrical engineering and synthetic biology courses at MIT, he developed a profound interest in integrating digital logic into synthetic biotechnology. He earned his Ph.D. in Quantitative Biology from UC San Diego and was a Postdoctoral Fellow at the Carnegie Institution for Science at Stanford University. His expertise lies at the intersection of AI and synthetic biology, built a high throughput cellOS to quickly Decode-Design-Recode novel species, with a specific focus on engineering microalgae to foster a better ocean ecosystem, discovery of anti-aging chemicals/peptides with new technology and real-world ground-truth data generation for virtual cell training and AlphaFold improvement. The whole pipeline can quickly help scientists to discover novel protein targets involved in aging process, design new chemical/peptide to target on these proteins and validate their effect in the wet lab to see if these molecules can extend single cell life span. The ingredients can be used for cosmetic, cosemtic injection, healthcare food and pharmacy sequentially. And with powerful cell factory and new synbio technology, he can reduce the R&D and manufacture cost by log scale.

    In his advisory role at SICE, he also collaborated with distinguished faculties from top universities to initiate local "Labrary", aiming to empower young students to succeed in both academia and industry.

  • Jason B. Ross, MD, PhD

    Jason B. Ross, MD, PhD

    Assistant Professor of Radiation Oncology (Radiation Therapy)

    Current Research and Scholarly InterestsMy laboratory studies studying normal, dysfunctional, and malignant stem cells in the context of aging, cancer, and cancer therapies.

  • Mohammad Shahrokh Esfahani

    Mohammad Shahrokh Esfahani

    Assistant Professor of Radiation Oncology (Radiation and Cancer Biology)

    Current Research and Scholarly InterestsMy laboratory develops computational and statistical methods to extract clinically actionable information from cancer genomic data, particularly circulating cell-free DNA. We combine cancer genomics, liquid biopsy, and machine learning to improve early cancer detection, characterize minimal residual disease, monitor treatment response, and understand therapeutic resistance across solid tumors and hematologic malignancies.

  • Junming Seraphina Shi

    Junming Seraphina Shi

    Postdoctoral Scholar, Radiation Biology

    BioI am a postdoctoral fellow at Stanford University, jointly mentored by Dr. Mohammad Shahrokh Esfahani and Dr. Md Tauhidul Islam. My research focuses on developing robust statistical machine learning methods for noninvasive, cost-effective cancer diagnostics, with applications in early detection, treatment monitoring, and precision oncology.

    I received my Ph.D. from UC Berkeley, where my dissertation centered on advancing biostatistical machine learning approaches for complex biomedical challenges. My work addressed causal inference for continuous treatments, bias and measurement patterns in ICU electronic health records, and deep learning–based biclustering and prediction of cancer-drug responses. Across these projects, I developed interpretable and scalable tools for analyzing high-dimensional, multimodal clinical data.

    At Stanford, I continue to build novel statistical learning frameworks tailored to real-world clinical needs—particularly through the analysis of liquid biopsy (cell-free DNA) and cancer imaging data. My current work aims to improve cancer detection and monitoring, with a focus on noninvasive, accessible, and clinically meaningful solutions to pressing challenges in oncology. I enjoy interdisciplinary collaborations and working across fields to drive innovation in biomedical research. Deeply committed to cancer research, I aim to bridge rigorous computational methodology with patient-centered impact by designing tools that are scalable, equitable, and translational.