School of Medicine
Showing 1-10 of 13 Results
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Xiyu Ge
Postdoctoral Scholar, Endocrinology, Gerontology, and Metabolism
Current Research and Scholarly InterestsI’m interested in understanding parathyroid hormone (PTH) signaling and its role in bone remodeling and the bone marrow microenvironment during critical growth periods. My research investigates how PTH influences osteoblast function and interacts with other signaling pathways. Using advanced single-cell sequencing and multi-omics approaches, I aim to uncover cellular and molecular pathways influenced by PTH, elucidate pediatric bone disorders, and identify potential therapeutic targets.
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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) 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 applying deep learning models to investigate aberrant splicing in cardiovascular disease.
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Ethan Goh, MD, MS
Postdoctoral Scholar, General Internal Medicine
BioDr. Ethan Goh is an experienced healthcare executive with a background in informatics, digital health transformation, and strategic innovation. His research at Stanford focuses on leading multi-site, grant-funded evaluation of Large Language Model applications within healthcare. As a cited healthcare AI expert, Dr. Goh's work has been featured in The New York Times, The Washington Post, and other leading publications.
Prior to academic research, he was an Internal Medicine clinician, startup founder, and technology consultant, working with partners like Google, OpenAI, Roche, Samsung, and the NHS in the development, validation and commercialization of digital health products and AI technology. He holds a medical degree from Imperial College London, and a Masters in Clinical Informatics and Management from Stanford University. -
Bruna Gomes
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.
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François Grolleau
Postdoctoral Scholar, Biomedical Informatics
BioFrançois Grolleau MD, MPH, PhD is a Postdoctoral Scholar at the Stanford Center for Biomedical Informatics Research. His research work centers on developing and evaluating computational systems that use large language models and other advanced methods from statistics and machine learning to assist medical decision-making.
François is a certified Anesthesiologist and Critical Care Medicine specialist from France. He holds an MPH degree and a PhD in Biostatistics from Paris Cité University. In 2016/2017, he worked as a research fellow in the Department of Health Research Methods, Evidence, and Impact at McMaster University, Canada (Profs Yannick Le Manach and Gordon Guyatt). During his doctorate with Prof. Raphaël Porcher, he utilized causal inference, personalized medicine methods, and statistical reinforcement learning for medical applications in the ICU.
