I am a Virginia Tech graduate with an MEng in Computer Science and Applications. During my master’s, I primarily focused on machine learning and artificial intelligence, occasionally delving into high-performance computing.
For my undergraduate degree, I double-majored in Computer Science and Computer Modeling and Data Analytics.
Throughout my studies, I have gained proficiency in Java, Python, C, R (I don’t like this one), SQL, and CUDA.
In my free time, I also learned Kotlin, Rust, C++, and Go.
During one of my summers, I had the privilege of interning at Clari as a Data Platform Engineer. I was responsible for creating a pipeline to move customer data from production servers and company APIs to the data analytics team’s Snowflake database, along with some summary statistics. It was a fulfilling experience where I learned a lot about Terraform and various AWS tools such as SQS, S3, and Lambda.
The summer before that, I interned with Synthesized. I was responsible for refactoring and adding functionality to insight, a Python package used to assess the quality of synthetic data against the data it was generated from. During that project, I learned much about writing production-ready code, Docker, and Grafana.