Introduction

I have been interested in language since my first French class in high school. It was amazing to me how different cultures convey meaning in different ways. I grew up in a bilingual home, where I was exposed to both Tamil and English, but because I mostly communicated in English outside the home, to this day I can understand Tamil perfectly but have a hard time constructing grammatical sentences and speaking Tamil. This disjunction was so fascinating to me and I knew I wanted to eventually learn more about linguistics. However, I wasn't sure of the best way to marry this interest with my computational and mathematics skills. Once I took the Computational Linguistics course offered to undergrads at the University of Arizona, though, I knew that this sounded like the perfect way to combine my two interests.

I graduated from the University of Arizona in 2021 with a B.S. in Statistics & Data Science with a minor in Computer Science. After graduation, I worked as a software engineer at Raytheon Intelligence and Space. This strengthened my programming and workplace professionalism skills. When I heard about the M.S. in Human Language Technology program at my alma mater, I wanted to jump on the opportunity to hone my computational linguistics skills, and to learn more about linguistics in general. I joined the in-person program in Fall 2023 and expect to graduate in May 2025.

I have explored topics such as speech synthesis, statistical natural language processing, information retrieval, and parsing in the HLT program on the computational side so far. I have also learned about syntax and psycholinguistics on the linguistics side. It was important to me to be able to take more programming-heavy classes along with more linguistics-oriented classes as I think this makes us more well-rounded computational linguists. I worked on projects in document classification, part-of-speech and token tagging, and word vector models, to name a few. I built on my statistics background by learning more about Markov models, Bayesian models, and logistic regression, as well as more advanced predictive models. All of these classes and projects have strengthened my abilities in Python, HTML, and shell scripting. For the internship requirement of the degree, I worked with Tech Launch Arizona to streamline the commercialization assessment process for potential University of Arizona-affiliated inventions. This allowed me to apply some of the theoretical skills I gained through my classes to a real-world application. I have documented some of my projects on my Portfolio page.