Stanford University
Showing 41-60 of 121 Results
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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
Postdoctoral Scholar, Anesthesiology, Perioperative and Pain Medicine
Current Research and Scholarly InterestsData-driven healthcare and AI research in a translational setting.
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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.
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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.
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Ciara Giles Doran
Graduate Visiting Researcher Student, Chemical Engineering
BioVisiting Student Researcher from ETH Zürich with the Bao Group. February - July 2024.
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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.
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Sneha Goenka
Postdoctoral Scholar, Cardiovascular Medicine
Stanford Student Employee, Hoover InstitutionBioSneha Goenka is a Ph.D. candidate in the Electrical Engineering Department at Stanford University where she is advised by Prof. Mark Horowitz. Her research centers on designing efficient computer systems for advancing genomic pipelines for clinical and research applications, with a focus on improving speed and cost. She is a 2023 Forbes 30 Under 30 Honoree in the Science category, 2022 NVIDIA Graduate Fellow, and 2021 Cadence Women in Technology Scholar. She has a B.Tech. and M.Tech. (Microelectronics) in Electrical Engineering from the Indian Institute of Technology, Bombay where she received the Akshay Dhoke Memorial Award for the most outstanding student in the program.
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Ethan Goh, MD, MS
Postdoctoral Scholar, General Internal Medicine
BioDr. Goh's research focuses on AI in healthcare, digital health, and informatics. He has successfully led multi-site, grant-funded evaluation studies on Large Language Models applications within healthcare. Prior to Stanford, he was an Internal Medicine clinician, startup founder and technology consultant, working with partners like Google, OpenAI, Roche, Samsung, IDEO, and the NHS in the development, validation and commercialization of digital health products and AI technology. He holds an MD from Imperial College, London, and a Masters in Clinical Informatics and Management from Stanford University.
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Bruna Filipa Gomes Botelho Quintas
Postdoctoral Scholar, Cardiovascular Medicine
Current Research and Scholarly InterestsThe increasing availability of very large datasets, along with recent advances in deep learning based tools for automatic extraction of cardiac traits, has led to the discovery of further common variants associated with cardiac disease. However, the genetic underpinnings of valvular heart disease remains understudied. I am interested in developing deep learning techniques to automatically extract cardiac flow information to facilitate genome-wide association studies of cardiac flow traits.