Projects

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neatmaps

The neatmaps R package simplifies the exploratory data analysis of multiple network datasets through a combination of heatmaps and consensus clustering.

scPCA

The scPCA R package implements sparse constrastive PCA, a variant of PCA that extracts sparse, stable, interpretable, and relevant signal, given access to control data

Teaching

University of California, Berkeley

  • The Foundations of Data Science, Data 8 (Summer ‘20) – Instructor
  • Statistical Analysis of Categorical Data, PBHLTH 241 (Spring ‘20) – Graduate Student Instructor
  • Principles and Techniques of Data Science, DATA 100 (Spring ‘19, Fall ‘19) – Graduate Student Instructor
  • Introduction to Probability and Statistics in Biology and Public Health, PBHLTH 142 (Fall ‘18) – Graduate Student Instructor

Experience

 
 
 
 
 

Graduate Student Intern

Sutter Health - Research, Development and Dissemination

Jun 2019 – Aug 2019 Walnut Creek, CA, United States
Developed a statistical modeling pipeline that uses electronic health record data to evaluate patients’ risks of developing sepsis during hospital visits. The pipeline relies on data-adaptive ensemble techniques, and is demonstrably more accurate than competing methods.
 
 
 
 
 

Undergraduate Summer Researcher

Concordia University

May 2017 – Sep 2017 Montreal, QC, Canada
Developed an exploratory data analysis method for high-dimensional network data under the supervision of Dr. Lea Popovic and Dr. Lisa Kakinami. The method was applied to the the Quebec Adipose and Lifestyle Investigation in Youth cohort data to explore potential associations between social networks and lifestyle behaviours related to youth obesity.
 
 
 
 
 

Research Assistant

Canadian Longitudinal Study on Aging, Statistical Analysis Center

Jun 2015 – Jul 2018 Montreal, QC, Canada
Worked with biostatisticians, data curators and data access managers on various projects, including the preparation of statistical reports for the Public Health Agency of Canada, the development of an R package to facilitate analysis of proprietary data, the creation of software to verify accuracy of survey responses and the curation of a public use dataset.