Stanford University


Showing 41-50 of 121 Results

  • Farnaz "Naz" Ghaedipour

    Farnaz "Naz" Ghaedipour

    Postdoctoral Scholar, Management Science and Engineering

    BioI am a postdoctoral scholar in the Department of Management Science and Engineering at Stanford University at the Centre for Work, Technology, and Organization (WTO), advised by Arvind Karunakaran. I earned my PhD in Management of Organizational Behavior and Human Resources from McMaster University, under Erin Reid’s supervision.

    I study how technological changes in the organization of work (e.g., the advent of AI and digital platforms) and the rise of the gig economy combine with norms and ideal images of work (e.g., authenticity, passion, entrepreneurialism) to shape the structure, organization, and experience of work. I primarily use qualitative research methods, including interviews, participant observation, and ethnography. To approach the individual phenomena as embedded in the contextual structure, I often complement the data derived from interviews and observations with contextual information derived from secondary data sources (e.g., archival and walk-through data). Occupations studied include Instagram content creators, journalists, Upwork freelancers, software engineers, and graphic designers.

    I was a finalist in the 2021 INFORMS/Organization Science Dissertation Proposal Competition and the recipient of the SSHRC post-doctoral fellowship (2022), Ontario Graduate Fellowship (2021), and the Ontario Graduate Scholarship (2020).

  • Marc Ghanem

    Marc Ghanem

    Postdoctoral Scholar, Anesthesiology, Perioperative and Pain Medicine

    Current Research and Scholarly InterestsData-driven healthcare and AI research in a translational setting.

  • Maitrayee Ghosh

    Maitrayee Ghosh

    Postdoctoral Scholar, Photon Science, SLAC

    BioI am a postdoctoral scholar at the High Energy Density Sciences Division in the SLAC National Accelerator Laboratory in the Stanford University. I have received my PhD from the University of Rochester in 2023 in high-pressure chemistry. My research interests include theoretical and computational investigations of materials in both ambient and high-pressure regimes, that can be relevant for planetary sciences and inertial confinement fusion. I hail from Kolkata, India, and enjoy reading fictions and traveling in my leisure.

  • Ruth Margaret Gibson

    Ruth Margaret Gibson

    Postdoctoral Scholar, Medicine

    BioDr. Ruth M. Gibson is a Banting Postdoctoral Fellow at the Center for Innovation in Global Health, at Stanford University School of Medicine. Her research focuses on geopolitical coercion and global maternal child health. Prior to her return to academia, she spent a decade working in global health in countries such as Madagascar, Yemen, Saudi Arabia, and Ecuador.

  • Ciara Giles Doran

    Ciara Giles Doran

    Graduate Visiting Researcher Student, Chemical Engineering

    BioVisiting Student Researcher from ETH Zürich with the Bao Group. February - July 2024.

  • Joshua Gillard

    Joshua Gillard

    Postdoctoral Scholar, Cardiovascular Medicine

    BioDr. Josh Gillard is a Canadian biomedical data scientist with experience in bioinformatics, machine learning, and immunology. After completing a BSc and a MSc in Experimental Medicine at McGill university, he relocated to the Netherlands for his PhD at Radboud University in Nijmegen. During his PhD, he gained experience analyzing and interpreting complex immunological data (bulk and single-cell transcriptomics, high-dimensional cytometry, proteomics data) derived from human observational or intervention studies (vaccination and experimental human infection) in order to discover molecular and cellular correlates of clinically important endpoints such as disease severity, symptom progression, and antibody responses. In 2022, Josh relocated to Stanford to join the Gaudilliere lab to develop and apply multi-omic data integration and machine learning techniques, establishing that early gestational immune dysregulation can predict preterm birth. Since 2024, in the Ashley lab, Josh is focused on the use of deep learning and transformer models to identify novel splice isoforms of hypertrophic cardiomyopathy using whole genome sequencing data.