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Olabisi Aishat Bello

Graduate Student

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About Olabisi

Born and raised in Nigeria, Olabisi Aishat moved to the U.S. to pursue a chemical engineering degree at Howard University, Washington, D.C. Although she loved the department and her classes, she eventually discovered that chemistry, and not chemical engineering, made her heart race. This realization led her to undertake several internships in the pharmaceutical industry where she got to apply her computational experience to solving scientific problems with concrete clinical impacts. 

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Motivated by those experiences, Olabisi took a hard left away from her chemical engineering research and applied instead to the University of Chicago’s graduate chemistry program to delve more into her passions. In 2023, she started her Ph.D. at the university and is now co-advised between the Esser-Kahn and Ferguson labs, where she happily works at the intersection of immunology, machine learning, and chemistry– the perfect triangle for her interdisciplinary interests and skills.

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Outside the lab and away from her desk, Olabisi enjoys reading and writing fiction, spending time with her Muslim community, and watching her never-ending list of anime and Korean dramas. She also volunteers with Nigerian non-governmental organizations focused on improving child welfare and child access to education.

Education

B.S., Chemical Engineering, Minor in Chemistry, Howard University (2019-2023)

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Undergraduate research conducted with Dr. Patrick Ymele-Leki on the growth kinetics and viability of Shewanella oneidensis for evaluating their bioremediation capabilities of radioactive iodine at the Hanford Site in Washington State

Favorite Quote

So which of the favors of your Lord would you deny? - The Qur'an 55:31

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Never give up – Naruto Uzumaki

Scientific Hero

Marie Curie & Alex Zhavoronkov

Favorite Paper

Zhavoronkov, A., Ivanenkov, Y.A., Aliper, A. et al. Deep learning enables rapid identification of potent DDR1 kinase inhibitors. Nat Biotechnol 37, 1038–1040 (2019). https://doi.org/10.1038/s41587-019-0224-x

If you could be a piece of lab equipment, what would you be?

Spectrophotometer – always ready to be a ray of light for all kinds of samples 😊🤗

Olabisi's Research

Olabisi is developing data-driven machine learning techniques that can generate small molecule immunomodulator analogs that are optimized for reducing vaccine adverse side effects while also boosting their efficacy. She is co-advised by Dr. Andrew Ferguson.

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