Leslie Myint


PhD in Biostatistics

Johns Hopkins Bloomberg School of Public Health

Dissertation: Evidence-Based Methods in Studies of Biology and Data Analysis

Advisor: Kasper Daniel Hansen

BS in Biomedical Engineering

Johns Hopkins University

Secondary major: Applied Mathematics and Statistics
Minor: Computer Science

Work Experience

Assistant Professor

Department of Mathematics, Statistics, and Computer Science

Macalester College, Saint Paul, MN

Johns Hopkins Biostatistics Center

Student statistical consultant

Johns Hopkins Bloomberg School of Public Health, Baltimore, MD

Advisor: Carol Thompson, MS

Siemens Competition

Stage I, II, and finalist judge

Categories: Computer Science, Mathematics, Bioinformatics, Cell/Cancer Biology, and Genetics



  1. Monroe, Anne K., Leslie Myint, Richard Rutstein, Judith Aberg, Stephen Boswell, Allison Agwu, Kelly Gebo, Richard Moore, and HIV Research Network. 2018. "Factors Associated with Gaps in Medicaid Enrollment among People with HIV and the Effect of Gaps on Viral Suppression." Journal of Acquired Immune Deficiency Syndromes, April. https://doi.org/10.1097/QAI.0000000000001702.
  2. Kang, Joon Y., Amin H. Rabiei, Leslie Myint, and Maromi Nei. 2017. "Equivocal Significance of Post-Ictal Generalized EEG Suppression as a Marker of SUDEP Risk." Seizure: The Journal of the British Epilepsy Association 48 (May): 28–32. https://doi.org/10.1016/j.seizure.2017.03.017.
  3. Myint, Leslie, Andre Kleensang, Liang Zhao, Thomas Hartung, and Kasper D. Hansen. 2017. “Joint Bounding of Peaks Across Samples Improves Differential Analysis in Mass Spectrometry-Based Metabolomics.” Analytical Chemistry 89 (6): 3517–23. https://doi.org/10.1021/acs.analchem.6b04719.


  1. Myint, Leslie, Dimitrios G. Avramopoulos, Loyal A. Goff, and Kasper Hansen. 2017. "Linear Models Enable Powerful Differential Activity Analysis in Massively Parallel Reporter Assays." bioRxiv. doi:10.1101/196394.
  2. Myint, Leslie, Jeffrey T. Leek, and Leah R. Jager. 2017. "Explanation Implies Causation?" bioRxiv. https://doi.org/10.1101/218784.


Magical Web Scraping with rvest
Invited Talk: Baltimore R Ladies Group (slides)
May 2018

Joint Preprocessing of Samples Improves Power in Differential Analysis for Mass Spectrometry-Based Metabolomics
Invited Talk: JHU Biophysics
December 2017

Shiny Applications for Teaching and Dungeons and Dragons
Invited Talk: Baltimore UseR Group (slides)
September 2017

A Method for Joint Processing of Mass Spectrometry-Based Metabolomics Data for Improved Differential Analysis
Poster: ENAR, Washington D.C.
March 2017


yamss: Tools for the analysis of high-throughput metabolomics data. An R package released through the Bioconductor project.

mpra: Tools for the analysis of data from massively parallel reporter assays. An R package released through the Bioconductor project.


Johns Hopkins Bloomberg School of Public Health

  • Statistical Thinking for Informed Decision Making (2 semesters)
    I developed this course as part of the Gordis Teaching Fellowship, a school-wide award that provides funds to design and teach an undergraduate class. A news article-motivated introduction to major biostatistical areas, including causal inference, survey sampling, and survival analysis.

Teaching Assistant
  • Public Health Biostatistics (3 semesters)
  • Introduction to R for Public Health Researchers (1 course)
  • Statistical Methods in Public Health (3 quarters)
  • Data Analysis Workshop (2 courses)
  • Statistics for Genomics (1 quarter)
  • Statistics for Laboratory Scientists (2 quarters)
  • Summer Institute: Statistical Reasoning in Public Health (2 courses)

  • Statistical Methods in Public Health (2 quarters)
  • Mentor for Center for Talented Youth Cogito Research Award Recipient (3 months)

Johns Hopkins University

Teaching Assistant
  • Introduction to Java (1 semester)


Helen Abbey Award

Johns Hopkins Bloomberg School of Public Health

Excellence in teaching (website)


  • 2018: Referee - BiOverlay
  • 2018: Referee - American Journal of Epidemiology
  • 2017: Referee - Observational Studies

Technical Skills

Programming languages
  • R
  • Stata
  • Python
  • Java
  • Matlab
Application development
  • Shiny
  • HTML
  • CSS
  • Javascript
  • d3.js
  • Git
  • RMarkdown
  • Adobe Photoshop