• Financial Mathematics: My early career contributions were focused on applying my knowledge of mathematics to improving the design and analysis of financial models in portfolio management. More specifically, I develop asset pricing models and measure the relationship between risk and expected returns associated with any given investment. My major role in the project was to identify and collect investment data, determine the pricing models suitable for the analysis of the data, analyze the data, and make recommendations as to which investment would have less risk and yield optimum returns.

• Numerical Methods: I proposed various novel numerical techniques for initial value problems that represents motion on a perturbed circular orbit on a complex plane. The result from my research were highly relevant as they provided new symmetric algorithms capable of tracking and tracing the equilibrium points of well-known celestial mechanics problem that represents motion and trajectory of astronomical objects on a perturbed circular orbit on the complex plane with spiral behaviors. I originally developed the novel super-implicit method, performed the stability analysis of the method, and implement the algorithm on the given problem. A subsequent research, in which I characterized a new technique for developing novel methods for solving inverse problems in engineering challenged a key paradigm of treating super-implicit methods in a generalized form rather than in isolation and were featured articles in two major journals in computational and applied mathematics.  

• Computational Biology: My research provides new details into the workings of complex biological systems while employing advanced computational techniques. I got trained in infectious disease modeling by Dr Chick Macal of the Argonne National Laboratory, Illinois and was later mentored by Dr Piers Lawrence on a computational biology research that deals with the development of spectral collocation methods for solving Human African Trypanosomiasis Disease (HAT) model. Essentially, we adopted a polynomial-like interpolation approach into the development of certain computational techniques for solving the HAT disease model while tracking the progression of the disease spread. I jointly developed the state-of-art technique called the spectral collocation methods and implemented it on oscillatory problems, and the HAT model.

• Mathematical Sociology: I developed mathematical models for studying the population dynamics of criminal gangs. During this research, I formulated novel mathematical models for the population dynamics of criminal gangs, in sight from mathematical epidemiology. In particular, the criminal behavior is treated as a socially infectious disease and the spread being modeled into systems of nonlinear differential equations. The models developed in the thesis include differential equations, delay differential equations, optimal control model. Each model was formulated to answer specific research questions. The result suggests various control policies and measures that could reduce crime rate in the most populous country in Africa. I continued in this trajectory by developing a behavioral model to study the juvenile delinquency in New York State by exploring and testing the model against the juvenile crime data obtain from Criminal Justice Services, New York while answering trending open research question.

• Pandemic Decision Science: Having the foundational knowledge in the study of disease epidemic and behavioral sciences, I accepted to take up a postdoctoral training under the supervision of Dr Lauren Ancel Meyers. My work is to develop mathematical and statistical models to assess the effect of COVID-19/influenza interventions for pandemic preparedness. The aim of this research is to determine the individual and joint effects of drugs/vaccines interventions combinations on disease transmission. The research is keen on the formulation of an optimization techniques that will enable us to determine the optimal combination to limit both respiratory virus spread and socioeconomic costs. For instance, measuring the economic cost in drug-resistance during influenza treatments and/or measuring the cost associated with the use of influenza drugs as prophylaxis. 

https://scholar.google.com/citations?user=4wXUpEwAAAAJ