Medicine
Showing 41-50 of 162 Results
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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 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.
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Shreya Gupta
Postdoctoral Scholar, Cardiovascular Medicine
Current Research and Scholarly InterestsI am a biomedical researcher focused on understanding the molecular mechanisms governing vascular smooth muscle cell (SMC) behavior in cardiovascular and metabolic diseases. My work investigates how signaling pathways, including Notch3 and Thrombospondin-1, regulate SMC phenotypic switching, fibrous cap stability, and plaque vulnerability in atherosclerosis, with the goal of identifying novel therapeutic targets to prevent heart attacks and strokes.
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Richard Haarburger
Postdoctoral Scholar, General Internal Medicine
BioRichard Haarburger is a postdoctoral scholar in the Department of Medicine (Primary Care and Population Health) at Stanford University, working in the lab of Pascal Geldsetzer. He studies questions at the intersection of epidemiology, health policy, and applied econometrics, with a focus on causal inference in large real-world health datasets.
His current work uses quasi-experimental and survival analysis methods to evaluate how preventive interventions (e.g. herpes zoster vaccinations) affect neurological outcomes such as dementia incidence at the population level. He also develops empirical strategies for dealing with challenges common in observational health data, including treatment effect heterogeneity, incomplete outcome follow-up, and competing risks.
Richard’s broader research interests include impact evaluation methods, causal machine learning, and the health and economic consequences of new technologies. During his PhD in quantitative economics, he worked on measurement bias in health surveys, high-dimensional forecasting, and heterogeneity in technology adoption. -
Florian Hoffmann, Ph.D.
Postdoctoral Scholar, Hematology
BioFlorian is a postdoctoral researcher in Dr. Ami Bhatt's laboratory at Stanford University. He earned his Ph.D. in Biochemistry working in Dr. Sam Sternberg's group at Columbia University where he studied atypical CRISPR systems in prokaryotes, in search of molecular tools for programmable gene editing and gene regulation. His studies elucidate the mechanisms of a novel RNA-guided transposition system, the evolutionary ancestors of the gene editing enzymes Cas9 and Cas12, and an unprecedented Cas12f enzyme that creates custom de novo transcription start sites without requiring promoter elements. Florian is fascinated by the vast untapped resources of novel gene functions encoded in bacteria and their viruses (bacteriophages). He is an inventor on multiple patents related to his doctoral work. During his postdoctoral work at Stanford, he aims to discover novel paradigms of bacteria-virus interactions and how these shape the human gut microbiome, and human health. To investigate these systems, he harnesses interdisciplinary approaches, combining computational gene discovery with experimental techniques in Molecular Biology, Genetics and Biochemistry.
