About Me

My first experience in analyzing datasets and applying mathematical statistical methods was in an introductory engineering statistics course in my second year. The power of statistical modeling and analyses techniques to clarify the causal links to variations, uncertainties and incompleteness in datasets was exciting as it opened my eyes to endless possibilities of optimization. During my undergraduate studies I have acquired knowledge in a broad scope of analog and digital electronic system design. This knowledge was utilized in designing and creating multi-subsystems projects requiring cross-platform software solutions. These aforementioned projects ranged from signal processing and telecommunications to more tangible systems such as the development and implementation of an access control system. This developmental life cycle of the projects I have undertaken has not only given me experience in the technical knowledge required to realize the projects but has taught me to construct augments defending my design choices based on statistical analyses of empirical statistical data, justifying its economic and technical feasibility.

The application of mathematics and statistics in engineering has always intrigued me through its potential to yield a better understanding of a complex system’s behaviour and the ability to predict their dynamics. I therefore took the initiative in my specialization module to choose to develop a project that combined these two fields. This aforementioned project encompassed the Field Programmable Gate Array realization of a continuous random variate data generator for generating various statistical distributions from a random seed input. The onus of the generated dataset was to be employed in the modelling of the elimination half-life parameter of different administered drugs. This project was challenging as it not only required designing a quite resource intensive look-up table based solution on FPGA hardware; but also required in depth knowledge in parametric and nonparametric statistical tests as well as regression analyses and pseudo random number generation. These statistical tests were employed to verify and judge the performance of the distribution generator realized on hardware and to validate the mathematical models where upon the hardware architecture was developed. It is after completing this project that I quickly realized that my true passion lay in the nexus of engineering and statistics.