Hi, I'm Ethan.

I study medicine and build machine learning models.

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Ethan Wu

Ethan Wu

MD/PhD Candidate · Pitt/CMU MSTP

I'm an MD/PhD student at the University of Pittsburgh and Carnegie Mellon, where I split my time between medical school and building machine learning models for healthcare. Before this, I spent two years at McKinsey & Company advising health organizations, and studied mathematics at Duke.

My research sits at the intersection of machine learning, mathematics, and medicine — I've worked across virology, cancer genomics, mathematical biology, ophthalmology, and infectious disease. The common thread is using quantitative methods to understand complex diseases.

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Experience

MD/PhD Candidate

2024 – Present

Pitt/CMU Medical Scientist Training Program · Pittsburgh, PA

Pursuing an MD at the University of Pittsburgh School of Medicine and a PhD in Computer Science at Carnegie Mellon University. My research focuses on developing interpretable machine learning models for large-scale health data — spanning cancer genomics, ophthalmology, mathematical biology, and infectious disease. I also created and lead-instruct an Applied ML in Medicine course for medical students and co-founded the Pitt AI in Medicine Student Society.

Senior Business Analyst

2022 – 2024

McKinsey & Company · Washington, DC

Advised healthcare and technology organizations on digital, data, and AI transformations. Built and managed a $100M+ data organization for a U.S. government health agency focused on emerging infectious diseases. Led quantitative modeling and stakeholder execution for a $900M+ hospital-provider merger.

B.S. Mathematics

2018 – 2022

Duke University · Durham, NC

Phi Beta Kappa. Conducted research across machine learning (Computer Science), mathematical biology (Mathematics), cardiovascular medicine (School of Medicine), and virology (National Cancer Institute). Summer Business Analyst at McKinsey & Company.

Selected Publications

First-author work across machine learning, ophthalmology, and infectious disease.

View all publications

Novel Systemic Associations of Idiopathic Epiretinal Membrane Identified via Machine Learning

Ophthalmology Science·2026

Predicting Early Onset of Age-Related Macular Degeneration: A Machine Learning Approach

American Journal of Ophthalmology·2025·1 citation

Patient-Specific Models of Treatment Effects Explain Heterogeneity in Tuberculosis

ML4H·2024·2 citations

Off the Clock

A few things I care about when I'm not reading papers or writing code.

Survivor

Would not last on the island. Will gladly debate your strategy for hours.

Fantasy Football

Perennial league optimist. The data says my team is good, actually.

Get in Touch

Always open to interesting conversations — whether about research, medicine, machine learning, or fantasy football trades.

etw46@pitt.eduLinkedIn(opens in new tab)Google Scholar(opens in new tab)
Pittsburgh, PA

© 2026 Ethan Wu