Over the summer of 2024, I interned at NASA Goddard Space Flight Center (GSFC) in the Heliophysics Science Division under the mentorship of Dr. Jeffrey Klenzing. My practicum focused on both software development and scientific research, with my primary responsibility being contributions to the Pysat project—an open-source Python library used internationally by astrophysicists to analyze satellite data. In addition, I worked on some of the Heliophysics Science Division’s ongoing ionospheric research efforts, particularly in the detection and analysis of Traveling Ionospheric Disturbances (TIDs) using machine learning and satellite observations. The goals of the software development aspect of the project were to repair and enhance pysat to provide astrophysicists around the world with greater tools and support with which to conduct their research and development. The research aspect aimed to better understand the causes, signs, effects, and trends relating to TIDs, in order to determine and optimize their impact on human life.
Most days during the internship would be focused on a mix of software development and meetings to reevaluate the priorities in terms of features to build, bugs to fix, etc. for pysat. I would also occasionally have research meetings to discuss the current status of the project and publications, and what work needed to be done on that end. We would also brainstorm different analyses to conduct and hypotheses to investigate during these meetings. Due to this team-centric approach, I learned a lot from watching the scientists around me. I was able to get a lot more exposure not only to the development philosophy of scientific/research software engineering (which is quite different from that of a startup or corporate software engineering role), but also how astrophysicists think in terms of drawing research conclusions and proposing experiments or investigations based on large-scale historical data.
This experience has definitely taught me about myself and my interests when it comes to future career paths and projects I like to become involved in. Both of my initiatives during this internship were heavily involved in both computer science and physics, and the intersection of the two is an area that I really enjoy working in. I have historically struggled to choose projects because I could not decide whether I wanted to focus on physics or computer science projects. This allowed me to deeply involve myself in both and also make a large impact, which is exactly what I want to do in my future projects as well. Additionally, I’ve developed a lot of skills required for these tasks, learning how to conflate the physics behind satellite instruments with computational handling and the resulting tools that can be used worldwide. I also learned many of the research approaches and became accustomed to the process. As a result of this experience, I intend to focus on roles that allow me to solve problems relating to both physics and computer science, particularly focusing on machine learning of physical phenomena or relating to physical reasoning.
For future SGC students who may be interesting in pursuing a similar role, I would highly recommend this and reaching out to the scientists at NASA GSFC, as I learned a lot from the role and I was able to make a much larger impact on real scientists on a global scale than I have been able to in any of my previous roles.