CSpotlight: Takeaways as an intern
Why did you choose to study computer science specifically at the University of Minnesota? What made you decide to pursue the integrated program?
After touring quite a few different schools, I chose the U because it felt like the right place for me. It has been nice to be close to home, especially with COVID. I chose to pursue the integrated program because I finished my undergraduate degree in three years, and wanted another year of college, especially a somewhat “normal” college experience. This year, I have had a ton of fun playing the saxophone in the pep band and jazz band, something that I missed a lot during COVID.
How did you become interested in computer science?
I participated in the First Lego League robotics competition, and that was my first introduction to programming. I also learned a lot and grew my interest in computer science from CoderDojo Twin Cities, a non-profit organization that teaches computer science principles to kids.
How did you become a software engineer at Optum? What kind of project did you work on at Optum?
Through CoderDojo, I have had the opportunity to meet a great mentor that works at Optum, and I was very interested in the work that he was doing. I was able to intern at Optum after my freshman year, through meeting with a recruiter at the CSE Career Fair and talking with my mentor. At Optum, I worked on various projects using both machine learning and graph, such as determining similar members, integrating call center data into a knowledge graph using NLP, and fraud detection. It was great to be at a company that could provide a breadth of experiences! Through my experiences at Optum, I got to know some TigerGraph employees, where I am currently interning. At TigerGraph, I am working on graph machine learning tools, demos, and tutorials for their In-Database Graph Data Science Library and Machine Learning Workbench.
How did you develop pyTigerGraph? Tell us more about the software!
When I interned at Optum, I was introduced to the graph database software TigerGraph, and my team used it in our project for performing machine learning on graph data. TigerGraph provides a REST API to run queries and other functions, which is what my team used over the summer. I wanted to create something that cleaned up some of the code overhead that we had, which is what pyTigerGraph does. Now Python developers can set up the connection one time in their code and then call different functions and queries as they wish without re-authenticating or other steps. The project gained enough traction that TigerGraph is now developing and maintaining the package.
What advice do you have for incoming computer science students?
Go to the career fair your freshman year. It is a great opportunity to get an internship, but even if you don’t, you’ll be more prepared in the future. Get involved with different organizations both on and off campus, both for fun and possible networking opportunities. I have learned a lot from other volunteers that I met at CoderDojo, and the experience of meeting and working with a ton of industry professionals is something that you don’t gain with an on-campus organization.
What are your plans after graduation?
I would like to continue working on projects that combine machine learning and graphs, as well as dig deeper into natural language processing.
Are there any additional experiences you had that you would like to highlight in the article?
I really enjoy mentoring at CoderDojo - it is a great way to share your knowledge with the next generation of computer scientists, and the volunteers form a great community. We are always looking for more mentors, check it out at coderdojotc.org!