Stanford University
Showing 1-10 of 11 Results
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Shengtian Sang
Postdoctoral Scholar, Radiology
BioShengtian Sang is currently a post-doctoral scholar at the Laboratory of Artificial Intelligence in Medicine and Biomedical Physics in the department of Radiation Oncology at Stanford University. He received his Ph.D. degree from the College of Computer Science and Technology, Dalian University of Technology, Dalian, China. His current research interests are high-dimensional data mining, medical image computing, and machine learning. In his Ph.D. study, he worked on the biomedical literature-based discovery and data mining.
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Sushruta Surappa
Postdoctoral Scholar, Radiology
BioSushruta Surappa is a postdoctoral researcher at the Canary Center for Early Cancer Detection at Stanford University. His current research focuses on developing various MEMS-based tools for the separation and capture of extracellular vesicles for medical diagnostics. Sushruta received his MS (‘15) and PhD (‘21) degrees in Mechanical Engineering from Georgia Institute of Technology, where he developed a new class of nonlinear MEMS transducers with applications in wireless power transfer, sensing and energy harvesting. He is passionate about developing low-cost, miniature technologies for medical diagnostics and is a keen proponent of science communication.
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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 2020. 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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Shashi Singh
Postdoctoral Scholar, Radiology
BioAs a postdoctoral scholar at Stanford University's Department of Radiology (2023-Present), I am privileged to contribute to Dr. Heike E. Daldrup-Link's laboratory, focusing on clinical and translational molecular imaging research. My endeavors deal with the development and application of artificial intelligence algorithms aimed at automated detection and monitoring treatment response of pediatric cancers, such as lymphoma and sarcomas, using PET and MRI. This includes the application of AI in multimodal pediatric lymphoma detection, automating the Deauville score, and predicting the post-chemotherapy response in pediatric osteosarcomas using PET and MRI. I am also studying the effects of iron-oxide nanoparticles on tumor-associated macrophages in osteosarcoma using Ferumoxytol-enhanced-MRI.
I served as a physician in Nepal for two years (2019-2021), which deepened my understanding of complex diseases like cancers and infectious and inflammatory disorders. Later, I worked as a research scholar at the Hospital of the University of Pennsylvania (2021-2023) where I worked with PET/CT imaging across various studies using novel radiotracers such as FDG, NaF, PSMA, and DOTATATE. My research at UPenn primarily focused on PET/CT imaging of hematological malignancies. I assessed the potential of PET/CT in CAR-T cell therapy for lymphoma and multiple myeloma and analyzed the efficacy of hematopoietic stem cell transplantation in multiple myeloma. I also studied dual time point imaging for Hodgkin's and non-Hodgkin's lymphoma using total-body FDG PET/CT. Beyond oncology, my research broadened to include PET/CT applications in aging, musculoskeletal, neurological, psychiatric, and cardiovascular diseases.
Each phase of my career has deepened my resolve to harness the power of imaging and artificial intelligence to revolutionize clinical management, honoring my commitment to patient care and groundbreaking scientific research. The significant potential of the application of artificial intelligence with both - structural (CT and MRI) and molecular (PET) imaging modalities has spurred my interest in utilizing AI to refine disease diagnosis and monitoring processes. I envision being a physician-scientist at the intersection of advanced clinical imaging and AI-based innovation, developing cutting-edge tools for early and accurate disease diagnosis and management. I believe that my contributions signify my commitment to this vision.
