Stanford University
Showing 521-540 of 670 Results
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Richard Shan
Affiliate, Rad/Integrative Biomedical Imaging Informatics at Stanford
BioRichard Shan is an AI researcher focused on mechanistic interpretability and retrieval-augmented generation. His work centers on building pipelines to evaluate and optimize reasoning in large language models, including novel architectures for feature identification and correctness evaluation. He develops applied systems that combine AI with linguistics, such as a modular refreshable Braille device and computational methods for reconstructing ancient languages. Outside of technical work, Richard enjoys playing frisbee.
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Luyao Shen, MD
Clinical Associate Professor, Radiology
Current Research and Scholarly InterestsGU and Gyn clinical imaging
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Vipul Sheth, MD, PhD
Assistant Professor of Radiology (Body MRI)
Current Research and Scholarly InterestsMy interests are in the development and translation of imaging technologies geared toward disease detection and characterization to better guide prognosis, treatment, and improve outcomes. I’m interested in supporting the development of MRI guided focal therapy methods which can personalize treatment and reduce the risk of morbidity from more invasive therapies.
Clinical Interests
- MRI for diagnosis of pelvic floor disorders
- MRI and PET/MRI to pelvic malignancies and lymph node staging.
- Whole Body MRI
- MRI guided procedures including biopsies, cryoablation, and high intensity focused ultrasound.
Translational Research Interests
- Development and translation of magnetic resonance imaging technologies to improve both diagnostics and therapeutics
- Molecular imaging and characterization of the tumor microenvironment
- Ultrashort echo time MRI applications in the body
- Developing synergistic MRI methods to complement PET in potential applications for PET/MRI -
Linxi Shi
Sr Res Scientist-Physical, Rad/Radiological Sciences Laboratory
BioI am a medical physicist and imaging scientist with over a decade of experience in CT imaging, algorithm development, and AI-driven reconstruction. I earned my Ph.D. in Medical Physics from the Georgia Institute of Technology, where I developed novel artifact corrections and reconstruction algorithms for cone beam computed tomography, focusing on applications in breast cancer diagnosis and image-guided radiation therapy.
Following my doctoral studies, I completed a postdoctoral fellowship with the Stanford Cancer Imaging Training (SCIT) Program. Currently, I serves as a Senior Research Scientist in the Radiological Sciences Laboratory at Stanford University. My research focuses on developing advanced clinical translational x-ray and CT imaging systems, including algorithm design for tomographic reconstruction, artifact correction, and image processing for various imaging modalities. -
Zahra Shokri Varniab
Postdoctoral Scholar, Radiology
BioZahra Shokri Varniab, MD, studied medicine at Tehran University of Medicine Sciences, Iran, and earned her medical degree in 2021. Her goal in novel cellular and molecular imaging is to develop novel in vivo imaging approaches to visualize, characterize and quantify molecular and cellular processes involved in developing brain tumors. She intends to utilize non-invasive imaging techniques to assess tumor microenvironment to understand their role in cancer, develop a method for determining tumor profiles, and also using brain MR Imaging to assess treatment response. She hopes cancer to be history.
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Pratham Preet Singh
Graduate, Medicine, Radiology
BioPh.D. Kinesiology
University of Toronto – Toronto, ON
Sept 2021 – Aug 2026 (Expected)
M.Sc. Biomedical Engineering (Specialization in Wearable Technology)
University of Calgary – Calgary, AB
Jan 2019 – Jan 2021
B.Eng. With Distinction, Biomedical Engineering (Co-op); B.A., Business Administration
University of Guelph – Guelph, ON
Sept 2012 – Dec 2017 -
Shashi Singh
Postdoctoral Scholar, Radiology
BioDr. Shashi Bhushan Singh is a Postdoctoral Scholar in the Department of Radiology at Stanford University, where he has been contributing to Professor Heike E. Daldrup-Link’s laboratory since 2023. His research focuses on clinical and translational molecular imaging, with a particular emphasis on developing and applying artificial intelligence algorithms for the automated detection and monitoring of pediatric cancers, including lymphoma and sarcomas, using PET and MRI.
Dr. Singh is involved in projects encompassing AI-driven multimodal pediatric lymphoma detection, automation of the Deauville score, and prediction of post-chemotherapy responses in pediatric osteosarcoma. He also investigates the impact of iron-oxide nanoparticles on tumor-associated macrophages in osteosarcoma and Ewing sarcoma, using MRI.
Prior to joining Stanford, Dr. Singh worked as a physician in Nepal from 2019 to 2021, gaining extensive clinical experience across a wide range of disease conditions. He subsequently served as a research scholar at the Hospital of the University of Pennsylvania (2021–2023) under the mentorship of Professor Abass Alavi. During this time, he conducted PET/CT research using a variety of radiotracers in hematological malignancies, aging, musculoskeletal disorders, neurological and psychiatric conditions, as well as infectious, inflammatory, and cardiovascular diseases.
Outside of his professional work, Dr. Singh enjoys exploring local restaurants and beaches in the Bay Area, going for long drives, hiking, and playing sports, including volleyball, cricket, and soccer. -
Bruno Passebon Soares, MD
Associate Professor of Radiology (Pediatric)
BioDr. Soares is an Associate Professor of Radiology at Stanford University School of Medicine and serves as the Section Chief of Pediatric Neuroradiology at Lucile Packard Children’s Hospital at Stanford since June 2023.
Born in Brazil, Dr. Bruno P. Soares obtained his medical degree from the Federal University of Rio de Janeiro and completed his residency in Diagnostic Radiology at the Federal University of Sao Paulo. After one year as a Research Fellow at the University of California San Francisco (UCSF), Dr. Soares completed clinical fellowships in Diagnostic Neuroradiology, Pediatric Radiology, and Pediatric Neuroradiology at UCSF, in addition to a clinical fellowship in PET/CT at the Dana-Farber Cancer Institute of Harvard Medical School in Boston. Dr. Soares holds a subspecialty certificate in Neuroradiology from the American Board of Radiology (ABR).
From July 2013 to July 2016, Dr. Soares was an Assistant Professor in the Division of Neuroradiology at Emory University in Atlanta. From August 2016 to November 2018, he worked at the Johns Hopkins University in Baltimore as an Assistant Professor in the Division of Pediatric Radiology and Neuroradiology. From December 2018 to May 2023, Dr. Soares worked at the University of Vermont Medical Center as Associate Professor of Radiology, Division Chief of Neuroradiology, Vice-Chair of Imaging Research, and Co-Director of the MRI Center for Biomedical Imaging.
Dr. Soares has published more than 85 peer-reviewed articles and has been the recipient of the Research Fellow Grant from the Society for Pediatric Radiology and of the Rad_Britestar Award from the Johns Hopkins Department of Radiology. The recognition for his teaching includes the 2013 Outstanding Clinical Fellow / Instructor Teaching Award from the UCSF Department of Radiology, the 2017 Teacher of Year Award from the Johns Hopkins Division of Pediatric Radiology, and the 2017 ASNR International Outreach Professor Program in Ghana.
Dr. Soares currently serves as an Editorial Board Member of Neuroradiology and of the Journal of Neuroimaging, and has served as an Editorial Board Member of the American Journal of Roentgenology (AJR) and of the American Journal of Neuroradiology (AJNR). Dr. Soares served for six years as a member of the ABR Neuroradiology Core Exam Committee, receiving ABR Volunteer Service Awards in 2022 and 2024.
His research has focused on neonatal and pediatric brain imaging. He is currently focused on developing semi-automated algorithms to quantify normal and abnormal brain development, and applying deep learning algorithms for detection of subtle cerebral abnormalities in children with epilepsy. -
Hyongsok Tom Soh
W. M. Keck Foundation Professor of Electrical Engineering, Professor of Radiology (Diagnostic Sciences Laboratory) and of Bioengineering
BioDr. Soh received his B.S. with a double major in Mechanical Engineering and Materials Science with Distinction from Cornell University and his Ph.D. in Electrical Engineering from Stanford University. From 1999 to 2003, Dr. Soh served as the technical manager of MEMS Device Research Group at Bell Laboratories and Agere Systems. He was a faculty member at UCSB before joining Stanford in 2015. His current research interests are in analytical biotechnology, especially in high-throughput screening, directed evolution, and integrated biosensors.
