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  • Computational Biology
  • Genetics
Shaila Ahsan Musharoff, assistant professor, Department of Computational Biology.

Shaila Musharoff was hired as part of the CALS Cohort Initiative and the Cornell NIH FIRST Cohort.

Academic focus: Statistical and population genetics

Research summary: My lab studies how human disease is shaped by genetic and environmental factors and whether these factors differ between populations. We do this by first using theory and simulations to assess how population histories, including migrations and mixtures, shape genetic variation. We then develop statistical genetic methods that account for these population histories and apply them to data from individuals with diverse ancestries. Our goal is gain insight into disease function and to reduce health disparities.

What do you like to do when you’re not working?

I enjoy hiking, biking, and visiting the beautiful waterways in Ithaca. As a trained dancer, I enjoy attending dance performances and occasionally dancing myself.

What are three adjectives people might use to describe you?

Passionate, determined, creative.

What (specifically) brought you to Cornell CALS?

I came to CALS for its scientific excellence as well as its commitment to mentorship. I spent the first year of my PhD at CALS, and the faculty’s dedication to student development transformed the way I viewed myself as a scholar. My goal is to make scientific training equitable for all people, and I feel very supported in doing so at CALS.

What do you think is important for people to understand about your field?

Though the findings from human genetic studies have the potential to improve human health, they are being abused in myriad ways, from making race-based claims about biological essentialism to predicting human traits in biased ways. To address this, geneticists must educate ourselves about the ethical implications of our work and engage in potentially challenging conversations about the interpretations of our findings.  

Why did you feel inspired to pursue a career in this field?

Growing up, I watched people in my family and ethnic community having poorer health outcomes than doctors expected, and I wanted to understand why. I noticed that some health conditions occurred more frequently in people with the same geographical origin, which led me to the study of human population genetics. I wondered how their environments and histories, including factors like poor water quality and forced migrations, affected their health outcomes. This led me to the study of statistical genetics with a focus on populations with diverse and mixed ancestries. To tackle these questions with increasingly complex data, I combined these fields of study with computer science to form my research program today.

If you had unlimited grant funding, what major problem in your field would you want to solve?

I would solve the problems of genetic data access as well as the ethical use of genetic data. Most of the data that people contribute to genetic studies is prohibitively expensive or difficult to access. As a result, only a few researchers can work with these data, which limits the pace of scientific discovery and adds to the existing inequity among the global population of researchers. Furthermore, the results of genetic studies are not often returned to the people who contributed their data in a way that benefits them. I would make it a requirement to work in partnership with the communities who contribute their data, from the study design through the conclusion of the study.

Learn more about Shaila on their faculty profile page.

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