Stanford University
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Jessica Hsueh
Affiliate, Department Funds
Fellow in Pediatrics - Peds/Critical CareBioCurrent combined adult and pediatric critical care fellow physician interested in medical education, curriculum design, and health services for adolescent and young adults with childhood-onset chronic conditions and medical complexity.
Most recently, I pursued my internal medicine and pediatrics (MedPeds) residency, chief residency and a medical education fellowship at the University of Illinois in Chicago. During this time, I helped implement our new X+Y resident schedule, created a multidisciplinary medical education track for residents, revamped curricula on resident mistreatment and self-advocacy, and worked with both the pediatric and adult critical care teams to develop resuscitation simulation bootcamps. My academic and institutional service interests revolved around the evolution of expertise and belonging over the course of training, particularly as it pertains to critical care resuscitation, medical educators in training, and underrepresented groups in medicine. -
Natalie Htet
Clinical Assistant Professor, Emergency Medicine
Current Research and Scholarly InterestsMy research focuses on advancing the care of critically ill patients in the Emergency Department, spanning from health system improvements in boarding critically ill patients to genetic phenotyping in septic shock, optimizing intubation for patients with metabolic acidosis, and critical care ultrasound. I am actively involved in medical education for graduate medical education and exploring the integration of AI to enhance ultrasound diagnostics.
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Jiaqi Hu
Postdoctoral Scholar, Cardiovascular Medicine
BioJiaqi Hu is a Postdoctoral Scholar at Stanford University, supervised by Drs. Tim Assimes and Shoa Clarke. She received her PhD in Chronic Disease Epidemiology from the Yale School of Public Health in 2026 and her Bachelor of Arts degree from Peking University in 2021. Her research focuses on identifying genetic variants underlying complex diseases, applying polygenic scores for disease risk prediction and subtype identification, and integrating genetic, environmental, and clinical data to improve individual-level risk stratification.
