Neonatal-Perinatal Medicine Fellows

Our Neonatal-Perinatal Medicine Fellowship lasts three years. Meet our fellows who are at different stages of their career development, and learn about their research projects. All of our current fellows are members of the Stanford Society of Physician Scholars (SSPS) in the Department of Pediatrics.

Eman Haidari, MD | Class of 2021

MD: Albert Einstein College of Medicine in Bronx, NY

Residency: UCSF Benioff Children’s Hospital Oakland in Oakland, CA

Mentors: Henry Lee, MD, MS Epi and Ciaran Phibbs, PhD

Research: I am interested in health services research and working on a project investigating reasons for the increase in NICU admission rates. My goal is to better understand inter-hospital variation and potentially identify overuse of NICUs.

Stanford Maternal & Child Health Research Institute recently awarded me with a Clinical Trainee Award to help fund my research.

Kevin McKim, MD | Class of 2021

MD: Temple University School of Medicine in Philadelphia, PA

Residency: Cohen Children's Medical Center in Queens, NY

Mentor: David Stevenson, MD

Research: My research is focused on the neonatal immune system and its evolution over time. Currently, I am planning to use CytoF to monitor changes in a neonate's immune development as a result of common treatments in our NICU, like the Premieloc hydrocortisone protocol.

Caroline Yeon-Kyeong Noh, MD | Class of 2021

MD: Ajou University School of Medicine in South Korea

Residency: University of Florida in Gainesville, FL

Mentors: Valerie Chock, MD, MS Epi, Krisa Van Meurs, MD, Shazia Bhombal, MD

Research: My research interest is in understanding the physiology of neonatal hemodynamics and its monitoring and management. I am conducting studies related to extracorporeal membrane oxygenation (ECMO), near-infrared spectroscopy (NIRS), and point-of-care ultrasound (POCUS), especially functional echocardiograpy.

Additional Education: I received full tuition support from Stanford Maternal & Child Health Research Institute to pursue a Master's degree in Epidemiology and Clinical Research starting Fall 2019.

Xuxin Chen, MD | Class of 2022

MD: Stony Brook University School of Medicine in Stony Brook, NY

Residency: New York University School of Medicine in New York, NY

Mentor: Henry C. Lee, MD, MS Epi

Pearl Houghteling, MD | Class of 2022

MD: University of Massachusetts Medical School in Worcester, MA

Residency: Yale New Haven Hospital in New Haven, CT

Research Interests: I am interested in the neonatal microbiome and nutrition. 

Jonathan Reiss, MD | Class of 2022

MD: Weill Cornell Medical College in New York, NY

Residency: University of California, San Diego / Rady Children's Hospital in San Diego, CA

Aviva Aiden, MD, PhD | Class of 2023

MD: Harvard Medical School in Boston, MA

Residency: Texas Children's Hospital in Houston, TX

PhD: Harvard University in Boston, MA

Research Interests: My PhD is in applied math and genomics, and my research has focused on the genomics of disease vectors and molecular diagnostics. Most recently, I led a team to develop a whole genome assembly based diagnostic approach to COVID-19.

John Feister, MD | Class of 2023

MD: Ohio State University College of Medicine in Columbus, OH

Residency: Ann & Robert H. Lurie Children's Hospital of Chicago in Chicago, IL

Research Interests: During residency, I pursued a certificate in global health studies and have researched how socioeconomic factors influence Latinx birth outcomes. I am interested in studying how public policy affects neonatal outcomes. 

 

Nicholas Gianaris, MD, MS | Class of 2023

MD: Indiana University School of Medicine in Indianapolis, IN

Residency: UC Davis Medical Center in Sacramento, CA

Research Interests: Prior to starting medical school, I obtained a Master's degree in cellular and integrative physiology and investigated the electrophysiologic properties of transient receptor protein channels. I am interested in investigating neonatal microbial ecology and the applications of machine learning methods for microbiome host-trait predictions.