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Junming Guan

PhD student in Statistics at the University of Chicago

I am a PhD student in Statistics at the University of Chicago, advised by Prof. Matthew Stephens. My research focuses on empirical Bayes, matrix factorization, and high-dimensional statistics.

I also work with Prof. Nikos Ignatiadis on empirical Bayes theory and methods. Before coming to Chicago, I developed methods for estimating direct genetic effects in family-based GWAS, supervised by Prof. Alexander Young and Prof. Dan Benjamin. I obtained my MS in statistics from the University of Washington, and BS in applied math from the University of California, Los Angeles.

Research interests

• Empirical Bayes
• High-dimensional statistics
• Matrix factorization
• Statistical genetics

Internship

Merck & Co., Inc.

June-September 2025

PhD Research Intern, Biostatistics

Developed ensemble learning methods that integrate randomized-trial and observational genetic data to improve treatment-response prediction and identify responsive patient subgroups.

Publications

Presentations and talks

• 2022 A unified method for estimating direct genetic effects and performing genome-wide association studies
  Presenter
  American Society of Human Genetics Annual Meeting, Los Angeles · Platform talk · October 2022
  Integrating Genetics and the Social Sciences Conference, Boulder · Oral presentation · September 2022
• 2022 The nature of nurture is not in the parents’ genes: estimating indirect genetic effects from parents using imputed grandparental genotypes
  Co-author
  American Society of Human Genetics Annual Meeting, Los Angeles · Poster · October 2022
• 2022 Mendelian imputation of parental genotypes improves estimates of direct genetic effects
  Presenter
  52nd Behavior Genetics Association Annual Meeting, Los Angeles · Oral presentation · June 2022

Services

Peer reviewer

IEEE Transactions on Information Theory

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Nature Scientific Reports