Growing up in Africa, I saw little of computers. My high school got its first computer in 2006 only two years before my graduation, and prestigious institutions, like hospitals, limited its use to data storage. Despite their dearth, their flaws, like mismanagement, insecurity and corruption, were conspicuous around me. This birthed and kindled my passion for technology and encouraged me to seek out resources that exposed me to computers as a problem-solving science. I became acquainted with cyber cafés that were remote and costly, but the investment was worthwhile. I started to notice the correlation between computer science and data management and security, and their correlation with other disciplines. As a result, I developed the dream of applying various data management skills and establishing rigid security systems across the various structures in society to enhance the completion of operations. My educational and career goals have, therefore, been shaped by an engagement in interdisciplinary studies that explores how Computer Science can meet the needs of developing countries.
My interest in these areas was solidified two summers ago when I participated in the Distributed Research Experience for Undergraduates (DREU) at the Ohio State University (OSU). For 10 weeks, I worked under Dr. Christopher Stewart, a graduate professor at OSU, and Jing Li, a graduate student, to evaluate the feasibility of renewable energy powering datacenters. I examined the flow of energy at different levels by collecting power usage information in some local datacenters and organizing this information to capture the coordination of power delivery in each datacenter. Following this, I systematically read the power usage metrics from various LCD displays in the datacenters to draw generalized conclusions regarding datacenters’ energy consumption.
Last summer, I again completed research with Dr. Yu-Han Chang at the University of Southern California. I developed data mining algorithms for basketball game data to unveil and analyze patterns in the data. Accordingly, I created an optimized SQL database for over 300 NBA games using various data modeling and mining techniques. I further examined this information by programming graphic tools that present, analyze, and interpret the data from different perspectives to generate complex relationships in multidimensional data. We thus developed some learning experience from the raw data for machine learning and subsequently artificial intelligence.
Participating in these programs introduced me to new problem-solving procedures and accompanying skills, most notably organizational and analytical reasoning skills, patience, and determination. For example, working with Jing to collect information about power usage often resulted in discrepancies. With patience and determination, we addressed them and found answers to questions we never anticipated. I certainly appreciated the high accountability standards set for our...