PeopleofSuperintelligence

Researcher

Nima Aghaeepour

Nima Aghaeepour is a Stanford professor who develops machine learning methods for clinical and biological data, with a focus on maternal and child health. He studied computer science at the University of Tehran and completed a bioinformatics PhD at the University of British Columbia in 2013. His work traced the immune clock of pregnancy in 2017 and used wearable data to study premature-birth risk in 2023. In 2025, his laboratory helped develop TPN2.0, a system that uses electronic health records to guide nutrition for premature newborns.

Works
412
Citations
9,991
h-index
53

Publication numbers from OpenAlex, as of 27 October 2026.

Timeline

  1. 2008–2013

    Computer science and bioinformatics

    He earns a bachelor's degree in computer science at the University of Tehran in 2008. In 2013, he completes a PhD through the University of British Columbia's Strategic Training Program in Bioinformatics for Health Research; Ryan Brinkman and Holger Hoos mentor his graduate research on single-cell data.

  2. By 2017

    The immune clock of pregnancy

    After postdoctoral training with Garry Nolan at Stanford, he works as an instructor in anesthesiology, perioperative and pain medicine in 2017. He is lead author of a 2017 study that models the immune clock of pregnancy using blood samples from 18 women with full-term pregnancies.

  3. 2021

    Blood markers of labor

    In 2021, he coauthors a study in Science Translational Medicine that uses blood measurements to predict the onset of labor. The team analyzes 7,142 metabolic, protein and immune features in samples from 63 women and identifies a biological shift two to four weeks before labor.

  4. 2022

    Data science leadership at Stanford

    In 2022, he becomes vice chair for research in data science in Stanford's Department of Anesthesiology, Perioperative and Pain Medicine. He also becomes co-chair of the Computational Systems Immunology PhD Program within Stanford's Immunology Interdepartmental Program in 2022.

  5. 2023

    Wearables and premature birth

    As senior author of a 2023 study, he helps develop a machine learning model of sleep and physical activity during pregnancy. The team uses wearable data from 1,083 pregnant women and finds that departures from typical sleep and activity patterns are linked to premature-birth risk.

  6. 2025

    An AIMBE fellowship

    In 2025, the American Institute for Medical and Biological Engineering inducts him into its College of Fellows. The election recognizes his work connecting AI and biological engineering with preterm-birth research and newborn health.

  7. 2025

    TPN2.0 for premature newborns

    In 2025, his laboratory helps develop TPN2.0, a machine learning approach that uses electronic health records to guide nutrition for premature newborns. The team identifies 15 feeding formulas and validates the approach with a separate hospital cohort at the University of California, San Francisco.

  8. 2026

    A clinical research award

    He receives a 2026 Top Ten Clinical Research Achievement Award from the Clinical Research Forum. The award recognizes his work developing and validating TPN2.0 for nutrition in neonatal intensive care units.

  9. As of October 2026

    Professor across three Stanford departments

    As of October 2026, he is Stanford's Anesthesiology, Perioperative and Pain Medicine II Endowed Professor and a professor of Pediatrics (Neonatology) and Biomedical Data Science. His laboratory develops machine learning methods for clinical and biological data, including maternal and child health and perioperative care. Since 2025, he also chairs the Education Committee of Stanford's Maternal and Child Health Research Institute.

Career

  1. Since 2022Stanford UniversityVice Chair for Research in Data Science
  2. Since 2022Stanford UniversityCo-chair, Computational Systems Immunology PhD Program
  3. NowStanford UniversityProfessor (Research) of Anesthesiology, Perioperative and Pain Medicine, of Pediatrics (Neonatology), and of Biomedical Data Science; Anesthesiology, Perioperative and Pain Medicine II Endowed Professor
  4. Stanford UniversityPostdoctoral researcher
  5. Stanford UniversityInstructor in anesthesiology, perioperative and pain medicine

Education

  1. 2013University of British ColumbiaPhD in bioinformatics
  2. 2008University of TehranBachelor's degree in computer science

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

Checked career sources: med.stanford.edu.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Nima Aghaeepour yet. Send us a free-licensed photo.

  1. Nima Aghaeepour | Stanford Medicine med.stanford.edu. Checked 27 October 2026.
  2. GLIIFCA - 2017 GLIIFCA Speakers gliifca.org. Checked 27 October 2026.
  3. Perfect timing: The key to pregnancy clockwork med.stanford.edu. Checked 27 October 2026.
  4. Stanford researchers identify blood markers that indicate labor is approaching med.stanford.edu. Checked 27 October 2026.
  5. Wearable device data reveals that reduced sleep and activity in pregnancy is linked to premature birth risk med.stanford.edu. Checked 27 October 2026.
  6. Nima Aghaeepour Inducted into the 2025 Class of the AIMBE College of Fellows aimbe.org. Checked 27 October 2026.
  7. CTSA-affiliated researchers’ application of AI leads to successful neonatal feeding interventions med.stanford.edu. Checked 27 October 2026.
  8. Nima Aghaeepour, PhD med.stanford.edu. Checked 27 October 2026.
  9. Nima Aghaeepour - Aghaeepour Laboratory nalab.stanford.edu. Checked 27 October 2026.