PhD Student in Applied Mathematics · University of Maryland, Baltimore County
Exploring numerical analysis, data assimilation, and quantum computing — with a background in mathematical modeling, fluid dynamics, time series methods, and data-driven research.
I am a PhD student in Applied Mathematics at the University of Maryland, Baltimore County (UMBC). My interests lie at the intersection of mathematical theory, computational methods, and applications, particularly in developing and understanding numerical approaches to complex problems.
My academic journey began with a B.Tech in Pure and Applied Mathematics from the Federal University of Technology, Minna, Nigeria. My undergraduate research investigated liquefied petroleum gas flow in cylindrical pipes using mathematical modeling and MATLAB simulations. I am currently revisiting this work with a colleague with the goal of preparing a scholarly publication.
I later earned an MS in Mathematics from Illinois State University, where my master's thesis examined polynomial-preserving linear filters for time series smoothing. The work studied Savitzky–Golay and Spencer filters through mathematical derivations, moment conditions, and numerical experiments.
My experience also includes healthcare predictive modeling and graph-theoretic approaches to stable matching. As I develop my doctoral research direction, I am especially interested in numerical analysis, data assimilation, and quantum computing. I also value teaching, mentorship, and interdisciplinary collaboration.
Completed and ongoing work across applied mathematics, computation, and data analysis.
Mathematical treatment of Savitzky–Golay and Spencer smoothing filters, including coefficient derivations, polynomial reproduction conditions, and numerical comparisons.
Read Thesis ↗ · Project Repository ↗Studied liquefied petroleum gas flow through cylindrical pipes using differential-equation-based modeling and MATLAB simulations. Revisiting the work collaboratively for potential publication.
Worked with more than 89,000 Medicare records, using feature engineering and Random Forest models to explore how social determinants of health relate to healthcare outcomes and claims.
Featured in Illinois State University News →Studied stable matching problems and their applications using the Gale–Shapley algorithm, Hall's Marriage Theorem, and concepts of fairness and efficiency.
Python · MATLAB · SQL/MySQL · Power BI · Excel · LaTeX
Numerical methods · Mathematical modeling · Differential equations · Statistical modeling · Data visualization · Linear algebra
Azeez, K. B. (2026). Theoretical Analysis of Filtering and Smoothing Techniques in Stochastic Time Series. Master's thesis, Illinois State University.
I welcome conversations about applied mathematics, computational research, teaching, and interdisciplinary collaboration.