I am interested in volunteering for Solve for Good because I want to utilize my analytical knowledge as well as my inquisitive nature to provide solutions to contemporary health issues, such as the COVID-19 pandemic, pregnancy, and pollution. I also hope to further practice my data analytic skills and improve my professional network for my future career trajectory. In order to reinforce my skillset, I have acquired professional data science certification from IBM. In the required courses, I learned relevant skills such as Python, API interactions, web scraping, SQL, and machine learning algorithms. I utilized these skills to complete projects such as the analysis of SpaceX rocket recovery. In the project, I used the SpaceX API as well as public webpages through web scraping to obtain launch data from Falcon 9 rockets. Through exploratory data analysis by Python and SQL, I compiled my results and explained the relevant parameters that are most influential in recovering rockets, such as launch site proximity, orbit type, and payload mass. The ultimate goal was to develop a model for predicting rocket recovery success, which would greatly decrease the cost of future space launches. In my current role as a Ph.D. student at University of California-Irvine, I have efficiently conducted literature reviews and developed efficient methodology to further both my own research on analyzing factors pertinent to cardiac regeneration as well as my collaborative work on bioelectrical signal acquisition (i.e., ECG, EEG) in the zebrafish animal model. Aside from refining my critical thinking skills through my research experience, I also used data analysis strategies to determine the relevant characteristics most pertinent to abnormal cardiac rhythm, as the technology of acquiring bioelectrical signals in zebrafish is still in its nascent stage. This work has currently produced one manuscript, with at least two additional manuscripts in progress.