Stanford University


Showing 41-50 of 60 Results

  • Charles William Ryan

    Charles William Ryan

    Postdoctoral Scholar, Ophthalmology
    Resident in Surgery

    BioI was born and raised in Syracuse, New York. I first attended Onondaga Community College, where I developed a fascination with the development of complex biological systems, and then transferred to Syracuse University where I completed my B.S. in biochemistry. I next attended the University of Michigan MD/PhD program, where I used in-vitro models of human neurodevelopment to study to role of epigenetic marks in guiding neurogenesis. While at Michigan, I became interested in the prospect of harnessing in-vitro differentiation to cultivate functional tissues that can be transplanted to replace what is lost in degenerative conditions. Ophthalmology, with its microsurgical access to functionally critical cell layers, is well-positioned to capitalize on this emerging field of science to treat degenerative conditions. I am humbled and incredibly thankful to have the opportunity to pursue this aim as a SOAR resident at Stanford.

  • Shruti Singh Kakan

    Shruti Singh Kakan

    Postdoctoral Scholar, Ophthalmology

    Current Research and Scholarly InterestsStudying the three-dimensional regulation of the genome in neuronal cell types in the healthy retina, and investigating dysfunctional genome regulation in a) inherited genetic diseases, b) aging, c) metabolic disease and d) cancer

  • Shih-Po Su

    Shih-Po Su

    Postdoctoral Scholar, Ophthalmology

    BioDr. Shih-Po Su is a Postdoctoral Research Fellow in the Department of Ophthalmology at Stanford University. He earned his Ph.D. in Biomedical Engineering from National Yang Ming Chiao Tung University (NYCU), Taiwan, in 2024. His doctoral research focused on the development of advanced optical imaging systems, including a three-dimensional near-infrared fluorescence and photoacoustic vascular imaging platform for preclinical applications.

    Dr. Su has over a decade of experience in biomedical imaging, integrating optical system design, image analysis, and in vivo disease modeling. His research interests center on the interface of optical engineering and translational medicine, particularly in retinal ganglion cell (RGC) imaging and neuroprotective strategies for glaucoma. At Stanford, he is extending his expertise to short-wave infrared (SWIR/NIR-II) imaging and in vivo retinal functional imaging to establish sensitive biomarkers for neurodegeneration.

    His recent work has advanced optical imaging and NIR-II contrast agents, including the co-development of polymer-dot probes for three-dimensional tumor and bone imaging (Chemical Science, 2022; Advanced Healthcare Materials, 2021) and an ultrabright polymer-dot platform for rotational stereo imaging (Advanced Healthcare Materials, 2024). He also designed integrated small-animal imaging systems combining bioluminescence tomography and ultrasound, as well as rotational stereo NIR-II fluorescence imaging (Optics Express, 2024; Journal of Biomedical Optics, 2023; Biosensors, 2022).

    Dr. Su has received multiple international recognitions, including the Taiwan Science and Technology Hub@Stanford Postdoctoral Fellowship (2024), First Prize in the NYCU Annual Thesis Competition (2023), the Future Tech Award (MOST, 2022), and the MOST Pilot Scholarship Program (2019). His long-term goal is to develop regenerative medicine–based imaging and therapeutic platforms to address unmet clinical needs in neurodegenerative diseases and vision restoration.

  • Imran Thobani

    Imran Thobani

    Postdoctoral Scholar, Ophthalmology

    BioDr. Imran Thobani is a postdoctoral scholar in Ophthalmology co-advised by Dan Yamins and Andreas Tolias as part of the Enigma project. He is interested in building large-scale predictive models of the brain that he thinks will be useful for both scientific insights and downstream biomedical applications. He did his PhD at Stanford, where he was trained in both philosophy of neuroscience and computational neuroscience, applying this training to develop better methods for comparing artificial neural network models to the brain.