School of Medicine


Showing 1-4 of 4 Results

  • Saisindhu Narala, MD, MAS

    Saisindhu Narala, MD, MAS

    Clinical Assistant Professor, Dermatology
    Clinical Assistant Professor, Pathology

    BioDr. Narala completed her dermatology residency at the University of Texas at Houston and MD Anderson Cancer Center. She then completed a fellowship in dermatopathology at Stanford. Her clinical interests include general medical dermatology, dermatology in skin of color, and pigmentary disorders. She also has an interest in medical education.

  • Yasodha Natkunam, M.D., Ph.D

    Yasodha Natkunam, M.D., Ph.D

    Ronald F. Dorfman, MBBch, FRCPath Professor of Hematopathology

    Current Research and Scholarly InterestsMy research interests focus on the identification and characterization of markers of diagnostic and prognostic importance in hematolymphoid neoplasia.

  • Jeff Nirschl

    Jeff Nirschl

    Instructor, Pathology

    BioJeff Nirschl, M.D., Ph.D. is an Instructor in Pathology at Stanford University, Stanford, CA with clinical expertise in Neuropathology. He completed his Ph.D. in Neuroscience at the University of Pennsylvania under the supervision of Dr. Erika Holzbaur. During his thesis research, he investigated axonal transport and genetic forms of parkinsonism. He also developed computational image analysis workflows for fluorescence microscopy and digital pathology. His research interests include molecular motors and the neuronal cytoskeleton, the regulation of axonal transport in neurodegeneration, digital pathology, and quantitative image analysis using machine learning.
    https://orcid.org/0000-0001-6857-341X

  • Roberto Novoa, MD

    Roberto Novoa, MD

    Clinical Professor, Pathology

    Current Research and Scholarly InterestsMy research interests include the medical applications of artificial intelligence, cutaneous lymphoma, and the side effects of targeted therapies. I have served as the lead dermatologist in our ongoing effort to develop AI-augmented classification of skin lesions. We are in the process of establishing one of the first prospective studies examining the performance of a deep learning algorithm in real-world patients.