About me

Biography

A native of Grand Rapids, I graduated from Calvin University in 2017 with a BSc in Biology.

I followed my passion for infection prevention to the University of Michigan School of Public Health, where I completed an MPH in Hospital & Molecular Epidemiology in 2020. There, I worked for Dr. Lona Mody, of the Division of Geriatric & Palliative Medicine, studying the infection prevention and epidemiology of antibiotic-resistant bacteria in hospitals and nursing homes. We continue to collaborate on projects, with particular interest in capturing young adult voices on public health and health education.

Currently, I am in my 6th year of a PhD in Microbiology & Immunology. I work with Dr. Evan Snitkin to leverage clinical metadata and whole-genome sequencing to study the evolution and spread of multidrug-resistant organisms in hospital and community settings.

Research interests

My career goal is to develop innovative solutions to combat antibiotic resistance by combining advanced genomic approaches, data analysis, and wet lab experimentation to identify patient and bacterial features that drive the emergence and spread of antibiotic resistance. ​

My interests:

  1. Evolution of antibiotic resistance

  2. Transmission of antibiotic-resistant organisms

  3. Phylogenetics of bacterial genome-influenced traits

  4. Epidemiologic trends of antibiotic-resistant organisms

  5. Translational infection prevention research 

Methods of interest:

  1. Whole-genome sequencing

  2. Epidemiological study designs

  3. Statistical genomics and phylogenetics

  4. Bioinformatic tool development for molecular epidemiology

  5. Experimental validation of genomic observations

Skills

  1. Software: Microsoft Office, Adobe Creative Suite, BioRender, DropBox, and Google Suites
  2. Programming: R, Linux, SAS, Python, GitHub, Docker/Singularity, SLURM (high-performance computing cluster)
  3. Molecular epidemiology: Whole-genome sequencing, variant calling, gene identification, pangenomics, phylogenetics
  4. Statistical methods: Ancestral state reconstruction, convergence-based genome-wide association, burden testing, regression modeling
  5. Wet lab experimentation: Specimen collection, bacterial cultivation, identification, and susceptibility testing