School of Medicine
Showing 21-40 of 53 Results
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Md Tauhidul Islam
Assistant Professor of Radiation Oncology (Radiation Physics)
Current Research and Scholarly InterestsMy research focuses on developing computationally efficient and clinically reliable AI methods for biomedical imaging and high-dimensional molecular data, with an emphasis on cancer and neurological disease. The Islam Lab designs novel representations and learning frameworks that improve deep learning performance in data-constrained biomedical settings, including methods that transform tabular omics data into spatially meaningful representations.
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Nataliya Kovalchuk
Clinical Professor, Radiation Oncology - Radiation Physics
BioEducation:
2002 - B.S., Physics, Drohobych State University, Ukraine
2004 - M.S., Physics, Minnesota State University, Mankato, MN
2008 - Ph.D., Applied Physics, University of South Florida (H. Lee Moffitt Cancer Center and Research Institute), Tampa, FL
2010 - Medical Physics Residency, Mayo Clinic, Rochester, MN
Academic Appointments:
2010 - 2015 - Instructor, Harvard Medical School, Massachusetts General Hospital/Boston Medical Center, Department of Radiation Oncology, Boston, MA
2015 - 2019 - Clinical Assistant Professor, Stanford University, Department of Radiation Oncology, Stanford, CA
2019 - 2024 - Clinical Associate Professor, Stanford University, Department of Radiation Oncology, Stanford, CA
2019 - 2024 - Adjunct Associate Professor, MD Anderson Cancer Center/University of Texas, Houston, TX
2024 - present - Clinical Professor, Stanford University, Department of Radiation Oncology, Stanford, CA
2024 - present - Adjunct Professor, MD Anderson Cancer Center/University of Texas, Houston, TX -
Ruijiang Li
Associate Professor of Radiation Oncology (Radiation Physics)
Current Research and Scholarly InterestsMy lab's research is focused on the development of imaging and molecular biomarkers to improve cancer detection, diagnosis, prognostication, and prediction of therapy response. Our ultimate goal is to translate these biomarkers into clinical practice to guide optimal management and therapeutic decisions for precision cancer medicine.
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Zhongxiao Li
Postdoctoral Scholar, Radiation Physics
BioZhongxiao Li is a postdoctoral researcher in Professor Ruijiang Li's lab at Stanford Medicine. His research focuses on computational biology and bioinformatics, particularly the development of deep learning methods for computational pathology and spatial transcriptomics/proteomics. Previously, his work has included developing machine learning models for histopathological image analysis, understanding gene regulation, and analyzing biological sequences.
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Lianli Liu
Clinical Assistant Professor, Radiation Oncology - Radiation Physics
Current Research and Scholarly InterestsAI-driven medical imaging for accelerated imaging speed and improved image quality, including:
Accelerated imaging for in-treatment patient monitoring and post-treatment patient follow up;
Functional imaging for treatment response evaluation and prediction.
Optimizing clinical quality assurance workflow through AI, including:
Radiation beam data modeling for efficient commissioning;
Model-based error detection for accurate dosimetry. -
Xiangde Luo
Postdoctoral Scholar, Radiation Physics
BioXiangde Luo is a postdoctoral researcher in Professor Ruijiang Li’s lab at Stanford Medicine, where he specializes in computational pathology. His work centers on developing AI‑driven methods for imaging biomarker discovery and precision oncology. Previously, he has developed some deep learning models to enable annotation‑efficient learning and advance biomedical image analysis. For a comprehensive overview of my research, please visit my Google Scholar profile: https://scholar.google.com/citations?hl=en&user=dD4HLS4AAAAJ. If you’d like to learn more or discuss potential collaborations, please don’t hesitate to get in touch.
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Sakib Mostafa
Postdoctoral Scholar, Radiation Physics
BioI am a Postdoctoral Research Fellow at Stanford University with a background in computational genomics and deep learning. My research focuses on developing AI-powered tools for genomic analysis, with a particular interest in cancer classification, pangenomes, and genotype imputation. Previously, I worked as a Research Officer at the National Research Council of Canada, contributing to large-scale sequencing projects and machine learning interfaces for biologists. I am passionate about bridging domain biology with cutting-edge computational methods to solve complex biological questions and drive innovation in precision agriculture and healthcare.
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Rohollah Nasiri
Postdoctoral Scholar, Radiation Physics
Current Research and Scholarly InterestsMy current research focuses on developing tumor-on-a-chip models for preclinical radiation therapy research.
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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
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.
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Lawrie Skinner
Clinical Associate Professor, Radiation Oncology - Radiation Physics
BioLawrie Skinner, PhD DABR is a therapeutic medical physicist with clinical expertise in external beam radiation therapy, including advanced motion management techniques and MRI-guided radiation therapy.
Research interests generally revolve around developing novel devices for advanced clinical practice. Examples include personalized 3D printed electron beam collimators, rotating couch overlays for total body radiation therapy, and radiotransparent audio visual communication and immersion displays.
Dr skinner also has a research background in synchrotron x-ray scattering, neutron scattering, molecular dynamics and Monte Carlo computational modelling.
