School of Medicine


Showing 81-90 of 101 Results

  • Muhammad Nasir Ullah

    Muhammad Nasir Ullah

    Postdoctoral Scholar, Molecular Imaging Program at Stanford

    BioMuhammad Nasir Ullah has received a BS degree in Electronic Engineering from International Islamic University, Islamabad (IIUI) Pakistan in Jun 2012 and an integrated MS + Ph.D. degree in Bio-Convergence Engineering from Korea University, Seoul, South Korea under the supervision of Professor Jung-Yeol Yeom in Feb 2020. His Ph.D. thesis was focused on detector design for Nuclear Medicine (NM) system and NM-Ultrasound hybrid systems.
    His area of research interest is radiation detection and measurement for medical applications. He has been working on detector design for Positron Emission Tomography (PET) system, intraoperative gamma probe detector, beta/gamma discrimination, and hybrid Ultrasound-gamma probe. He has also been working on frontend discrete circuit designs for various types of radiation and Ultrasound (US) detectors. He has published 6 peer-reviewed articles as the first author while 2 as co-author. He also has 4-patents under his name in S. Korea.

  • Jeya Maria Jose Valanarasu

    Jeya Maria Jose Valanarasu

    Postdoctoral Scholar, Radiology

    BioDr. Jeya Maria Jose Valanarasu is a postdoctoral scholar working with the Stanford Machine Learning Group and the Center for Artificial Intelligence in Medicine and Imaging (AIMI Center). He leads the AI for Healthcare bootcamp with Dr. Andrew Ng, Dr. Curt Langlotz, and Dr. Nigam Shah which provides Stanford students an opportunity to engage in advanced research at the intersection of AI and healthcare.

    He obtained his Ph.D. and M.S from Johns Hopkins University where he worked on various problems in Computer Vision, Machine Learning, and Healthcare. His research aims to overcome the challenges that arise when translating machine learning models to practical applications for healthcare and engineering sectors. His works have spanned over topics like designing effective deep architectures, model adaptability to changing environments, role of data and annotations, multi-modal learning and taming large models for computer vision and healthcare tasks. He has published over 25 peer-reviewed journal/conference articles at top venues and filed 3 U.S. patents. He has been awarded Amazon Research Fellowship 2022, Best Student Paper Awards at ICRA 2022, CVIP 2019, MICCAI Young Scientist Impact Award Finalist 2022, and the NIH MICCAI Award 2022. He has also served as a reviewer for multiple journals and conferences.

  • Henk van Voorst

    Henk van Voorst

    Postdoctoral Scholar, Radiology

    BioDr. van Voorst is a postdoctoral scholar in Radiology studying the interfaces of artificial intelligence and neuroradiological imaging in stroke. Originally educated as an MD, Dr. van Voorst gained additional degrees in Finance and Data Science. As a PhD student, Dr. van Voorst focused on cost-effectiveness modeling and developed machine learning and deep learning algorithms with applications in acute ischemic stroke imaging. In his current research, Dr. van Voorst develops artificial intelligence algorithms to automatically extract information from arteries and veins in radiological stroke imaging.

  • Jie Wang

    Jie Wang

    Postdoctoral Scholar, Radiology

    BioDr. Jie Wang is deeply passionate about magnetic nanotechnology, including magnetic resonance imaging (MRI), magnetic particle imaging (MPI), magnetic nanoparticles (MNPs), magnetic nanofluid hyperthermia (MNFH), magnetic biosensors, etc., for biomedical applications. His dissertation focuses on MRI-guided magnetic hyperthermia for cancer theranostics. Currently, his research interests include developing enzyme-activable nanoparticles for brain cancer theranostics and employing multi-modal imaging modalities to investigate the interaction between nanoparticles and biosystems (nano-bio interaction) within tumor microenvironment.