I am a 2020 high school graduate with a background in scientific research and computing. Due to the ongoing pandemic, I have chosen to take a gap year to focus on programming and data science work as a volunteer. I am most familiar with projects utilizing the Python language. My motivation however is to learn and contribute my best, so I would be excited to learn new libraries, languages, and other tools to accomplish any task.

For the past two summers, I have interned in the Bowen Lab, Chemistry Department, Johns Hopkins University. In order to automate data file naming and display real-time data, I taught myself LabView and wrote user-friendly programs to do so. This past summer I also attended the weeklong 2019 PARADIM Summer School at JHU, studying materials discovery in the era of big data. This seminar focused on the application of big data and metadata to predict new useful materials. These materials included new computer memory and energy storage devices as well as stronger ceramic body armors. Using machine learning techniques, patterns in the materials data and metadata can be used to predict new useful materials. At the end of the weeklong program, I had used various Python programming libraries and computational tools to discover and plan a synthesis for a new material. I look forward to continuing to use data to make new discoveries that benefit society.

In my schoolwork, I have challenged myself with the most rigorous science and math classes possible including the AP Physics C, Calculus BC, Chemistry, and Biology courses, with a perfect score on each exam. As a dual enrollment student at Towson University, I have taken advanced classes including Linear Algebra. I completed the MIT OCW Python classes 6.0001 and 6.0002 as well as the Google Developers Machine Learning Crash Course. I am currently reading Michael Neilson’s Deep Learning book and Python for Data Analysis by Wes McKinney.