As a new high school graduate, I knew upon establishing my career that I would be prosperous, independent, and involved in my community. When I entered college, I lacked distinct goals but quickly developed self-motivation and self-determination through the support of Dr. Linda Hayden and the Elizabeth City State University (ECSU) Center of Excellence for Remote Sensing Education and Research (CERSER) program. In addition, I have been exposed to conferences, distinguished lectures, and research projects, which have encouraged my ambition within the field of computer science. Webster defines ambition as the desire to achieve a particular end. The particular ends that I desire to achieve are to work for and later own my own remote sensing and geographic information system (GIS) corporation. My scholastic preference leans toward developing applications, software, and hardware that advances the exploration and conservation of the environmental systems.
As a freshman researcher on the CERSER Multimedia team for 2010-2011, I conducted research to redesign the database and the code required to process the remotely sensed Advanced Very High Resolution Radiometer (AVHRR) data received from orbiting National Oceanic and Atmospheric Administration (NOAA) satellites. This data is collected by the SeaSpace TeraScan® system that is installed in the CERSER labs on the ECSU campus. Due to a recent change in operating systems the data derived from this system no longer were being analyzed daily. The team’s implementation of cross platform compatible file permits the data to be analyzed and reduces the challenges to be faced in future platform changes.
During the following summer, I had the opportunity of participating in the Summer Scholars Institute STEM initiative at the Indiana University Bloomington campus. While there, I was assigned to the MapReduce Team. MapReduce is a data processing framework that allows developers to write applications that can process large sets of data in a timely manner with the use of distributed computing resources. The focus of this research project was to analyze the attributes of MapReduce frameworks for data intensive computing and to compare two different MapReduce frameworks, Hadoop and Twister. The MapReduce WordCount application was used to analyze the two frameworks because of its superior ability to partition large computation into parallel process computation. The team compared the performance of Hadoop's and Twister's scalability and efficiency for this particular application. This research experience helped teach me how to utilize various applications with increased skill.
Upon completion of my bachelor’s degree, I plan to pursue my master’s degree in Remote Sensing. Furthermore, I would also like to conduct a lecture series which exposes different grade-level students to Science, Technology, Engineering, and Math (STEM) fields. Hopefully, some students will gain interest in STEM which, in turn, will motivate them to continue their education in the sciences. After receiving my Master’s degree, I will continue my education by pursuing a doctorate. I will incorporate the knowledge gained through my experiences to advance the daily lives of the general public. This blueprint that has been laid therefore incorporates the immortal words of Bill Gates: “The computer was born to solve problems that did not exist before”.
