School of Medicine


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  • Dayan J. Li, MD, PhD

    Dayan J. Li, MD, PhD

    Clinical Scholar, Dermatology
    Postdoctoral Scholar, Pediatric Surgery

    Current Research and Scholarly InterestsWound healing, cutaneous fibrosis

  • Islam Mohamed Nour Hassan Mohamed

    Islam Mohamed Nour Hassan Mohamed

    Postdoctoral Scholar, Pediatric Surgery

    BioDr. Islam Nour is a molecular virologist with over fifteen years of research experience spanning viral genomics, reverse genetics, and structural–functional analysis of pathogenic RNA viruses. As a previous postdoctoral fellow in Molecular Virology at USDA-ARS, he designed and deployed reverse-genetics systems for IBDV and avian reovirus, integrated Illumina and Oxford Nanopore sequencing with comparative genomics, and coupled these approaches to IHC/IF-based pathogenesis models. His earlier work on rotavirus and SARS-CoV spike evolution, protein modelling, and molecular viral surveillance further strengthened his ability to connect viral sequence variation to phenotypic outcomes and tissue injury. He is particularly motivated to bring this mechanistic and translational expertise to multidisciplinary clinical teams in pediatric liver disease and transplantation in division of pediatric surgery in Stanford Medicine, contributing rigorous viral pathogenesis, vector design, and protein expression skills to clinically relevant models and biomarker discovery.

  • Humza Thobani

    Humza Thobani

    Postdoctoral Scholar, Pediatric Surgery

    BioHumza is a Postdoctoral Research Fellow in the Division of Pediatric Surgery at Stanford University. He earned his medical degree from the Aga Khan University in Karachi, Pakistan in 2023. Prior to joining Stanford, he had completed a dedicated research fellowship in pediatric surgery, also at the Aga Khan University, where he was named Best Research Fellow in 2024.

    Humza's research interests revolve around congenital surgical anomalies, pediatric solid tumors, and pediatric inflammatory bowel diseases, with a focus on leveraging big data and machine learning methods to study rare pediatric conditions.