Why Texas Tech
Boluwatife was drawn to medicine and engineering from a young age, but mathematics became the field she enjoyed most. She chose mathematics because of its strong foundation and its ability to connect with many other disciplines.
She learned about Texas Tech University through an alumnus who is also her sibling. After exploring the university’s culture and research environment, she became confident that TTU would be a strong place to grow as a researcher while also enjoying a balanced and supportive student life in Lubbock.
Research in Plain Language
Boluwatife’s research focuses on developing large-scale simulation and modeling frameworks to better understand how complex biological systems respond to changes in inputs.
In particular, she studies how sensitive system-level outcomes are to variations in parameters. Her work has applications in cancer dynamics and ecological systems, where computational models can help researchers explore behavior across many possible scenarios.
Her research involves building computational models that allow for systematic exploration across high-dimensional parameter spaces.
A Defining Graduate School Milestone
One of Boluwatife’s most defining experiences was working through her pure mathematics preliminary examination. She chose Complex Analysis and used all three attempts before passing.
The experience was humbling and transformative. Failing the third attempt would have meant leaving the Ph.D. program, so the process pushed her to reflect deeply on her approach to learning and preparation.
That journey taught her resilience, discipline, and the importance of not taking any stage of the process for granted.
“Trust that you are growing, even when it is not immediately visible.”— Boluwatife Elizabeth Awoyemi
Skills and Career Goals
Boluwatife’s goal is to work as an independent researcher at the intersection of computational modeling and biomedical data science. She is especially interested in contributing to drug development and quantitative systems pharmacology within a research-intensive environment.
Through her Ph.D. work, she has developed experience building adaptive simulation pipelines that run tens of thousands of simulations on high-performance computing systems. These tools allow her to explore high-dimensional parameter spaces and translate biological questions into mathematical and computational frameworks.
She has also gained experience with MATLAB, Python, and R to build reproducible analytical workflows and has worked in interdisciplinary settings where modeling supports real-world decision-making.
Life at TTU and in Lubbock
One of the things Boluwatife appreciates most about Texas Tech is the campus itself. She describes the layout as structured and visually appealing and considers it one of the most beautiful campuses she has experienced.
Lubbock has also been a welcoming place to live, offering a calm and steady environment. Within the Department of Mathematics & Statistics, she has been especially grateful for the faculty, the SIAM TTU chapter, and the multicultural community.
Favorite Department Memory
One of Boluwatife’s favorite memories is the monthly group meetings with her advisor, Dr. Amanda Laubmeier, and the students in her research group.
These meetings served as regular moments to reset and recharge. The group shared research progress, discussed challenges, exchanged ideas, and supported one another beyond academics.
Advice for Future Graduate Students
Boluwatife encourages prospective graduate students to take advantage of time whenever they can. If something can be completed today, she advises students to do it, because tomorrow may bring new challenges.
She also encourages students to trust that they are growing, even when progress is not immediately visible. Over time, students may find themselves able to handle problems that once felt impossible.
Next Step After Graduation
After graduation, Boluwatife is pursuing opportunities in computational pharmacology and data science. This includes a potential fellowship opportunity with the U.S. Food and Drug Administration.
More broadly, she is interested in roles within the pharmaceutical industry as a mechanistic modeler contributing to drug development.