School of Medicine
Showing 31-40 of 156 Results
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Ali Etemadi
Postdoctoral Scholar, Nephrology
Current Research and Scholarly InterestsI am a clinician and data scientist focusing on drawing causal inferences from observational data when randomized controlled trials are not feasible. Currently, my work centers on patients with late-stage chronic kidney disease, a rapidly growing population for which evidence is limited due to their frequent exclusion from RCTs. At the moment, I aim to move towards precision medicine approaches to optimize outcomes for these patients.
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Priya Fielding-Singh
Postdoctoral Scholar, SCRDP/ Heart Disease Prevention
BioI am a Sociologist and Postdoctoral Fellow in Cardiovascular Disease Prevention at the Stanford Prevention Research Center. My research examines health, gender, and social inequality.
My primary research agenda investigates health disparities across class, race, and gender in the United States. I draw on both qualitative and quantitative methods to understand how neighborhoods, schools, and families shape our health behaviors and outcomes. My work has been published in journals such as Social Science & Medicine, Obesity, Sociological Science, and the Journal of Adolescent Health.
I hold a Ph.D. in Sociology from Stanford University, a M.A. in Anthropology from the University of Bremen, and a B.S. in Education and Social Policy from Northwestern University. -
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 in bioinformatics 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, high-throughput proteomics) derived from human observational or intervention studies (vaccination and experimental human infection). This work revealed 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 developing deep learning models to investigate aberrant splicing in cardiovascular disease.
