Kevin was born and raised in Honolulu, where he graduated from Kaimuki HS in 2009. He is currently a senior at the University of Hawai‘i at M?noa, working toward concurrent degrees in Computer Engineering and in Studio Art with a focus in Graphic Design. Kevin’s future goal is to apply creativity to computer software and technology to better enrich society. In his spare time, Kevin enjoys freelance graphic designing, playing piano and French horn, photography, video gaming, karaoke, and eating his heart out!
Home Island: Oahu
High School: Kaimuki High School
Institute when accepted: University of Hawaii at Manoa
Star Formation Processes Visualized Using
Project Site: UH Hilo
Mentor: Marianne Takamiya
Understanding star formation processes throughout distant galaxies requires analyzing and identifying correlations among the properties of star-forming regions (HII regions). A large database of observations of HII regions, including star formation rate and dust extinction, has been compiled. This database, however, is solely text-based, so my task was to identify correlations among the data science products. Creating and implementing an object-oriented database to plot and visualize all the data will allow the astronomical community to comprehend what is happening among more than 30,000 different spectra. Completing such a task required understanding the scientific background of the data, proficiency with data-mining software, and a Web-based interactive user-interface for data visualization. To accomplish this, I selected and implemented a data-mining program called Orange, which allows visualization of data through a multitude of methods, including generating on-demand scatter plots. After extensive familiarization with this program, I developed a tutorial document to aid new members of the astronomy research group with using Orange. I also learned Python and incorporated routines that allow for the generation of 3-D plots, a function that Orange does not easily provide. Members of the astronomical research team are already incorporating recently generated plots into a Web interface. These newly discovered trends will help us understand more about star formation rates in galaxies, and therefore more about our cosmic environment and galactic evolution.