“Rachel will be among the top 5% students among all the undergraduate and graduate students that I have trained/interacted with so far. Rachel is an outstanding science student as evident from several honors and awards highlighted in her CV, including a graduate college scholarship for her predoctoral work (offered only to the top students in the program).” -Ashutosh Mangalam, associate professor, pathology

Hometown: I grew up in Waunakee, Wisconsin, and moved to Parker, Colorado, during my senior year of high school. I consider both my hometowns.

Faculty mentor/advisor: Ashutosh Mangalam, PhD, associate professor, pathology, Carver College of Medicine

What is your degree program and expected graduate date? PhD in Bioinformatics and Computational Biology. Expected to graduate in May 2025.

Please describe your research: The microbiome consists of all the bacteria, viruses, and other microorganisms found in and on our bodies. They are critical in maintaining our health and when disrupted can contribute to disease. I study how the microbiome contributes to the neurodegenerative disease, Multiple Sclerosis (MS).

In simple terms, why does this research matter? My work will increase our understanding of the microbiome’s impact on MS, which can lead us closer to personalized therapy options for people with this incurable disease.

How soon after starting at the University of Iowa were you able to participate in research? I began research remotely in Colorado as soon as I accepted the position!

How has being involved in research made you more successful at the University of Iowa? While being in research I have met so many wonderful people. Many of whom have become close friends and have pushed me to learn and become more creative with every project. I believe the most profound research comes from a strong team, and the University of Iowa has provided that team for me!

What are your career goals and/or plans after graduation? My goal after graduation is to teach at the collegiate level. I hope to create a class that models an experiment, starting with an idea and finishing with data analysis and interpretation.

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