Understanding how to parse natural language in a systematic manner is essential for the future of technology and especially for true AI.
With Big Data in its heyday, now more than ever are strong analytical skills in data important for modern understanding of the world around us.
Syntax is ever-present in natural language, and a theoretical and methodological understanding of such lets us explore the very nature of the human mind.
Languages are fun, but wouldn't it be great to make your own? While this doesn't inherently sound like a useful skill, it translates to having a stronger understanding of linguistics in general and in languages worldwide.
Analysis of natural language is the new frontier for data analysis in general. Computer-understanding of natural human speech and text will allow us to finally bridge the gap present gap before true AI, and I am eager to assist in this evolutionary transition. We can not only expect this technology to advance with English alone either, but with all of the world's major languages as well.
With the massive amounts of data that can be found through the Internet of Things, having a solid understanding of how to process it is essential for future technologies. Knowing how to find trends and correlations, and knowing how to avoid false ones, will be the most important skills to have in the coming years. I am currently working to improve my own ability to work with data, and I hope to be at the forefront of such within a couple years.
The inner workings of human speech lies in its grammar, and understanding not only the most mainstream grammatical formalisms but also alternatives is the only way to ensure that we can determine such. With this knowledge also comes the ability to automatically parse natural language syntactically, and only after this step can we semantically parse the data as well for true computer-understanding of text. I aim to keep up to date with not only syntactic research but also its parsing equivalent as well.
Turning the simple into the beautiful
Understanding the most important and most numerous animals on our planet
Seeing the world in a new light
Building and exploring a new linguistic future
At KS I learned to work with massive datasets and improved my own knowledge of both programming and linguistic analysis. Taking concepts that I'd learned in class, like project management and algorithmic time-analysis, allowed me to apply my skills in a very real and tangible manner.
Continuing my five year masters program at Indiana University, I finally started classes that took all prior general linguistic and computer science knowledge and applied them directly to the modern field of natural language processing. Classes like these allowed me to discover my more specific interests in the field, and I finshed up the program at the end of 2017.
When starting at Indiana University, I focused solely on linguistics. During this time I discovered my interest in the Korean language, both grammatically and culturally. When my department released a new five year MS/BS program in CL, I jumped at the chance.
I had little idea what I'd study in primary school, and I left expecting medicine to be my work of choice. At this time, I still had a strong passion for languages, but didn't expect it to be my future.
I'm currently in Washington D.C. until March, when I will return to Bloomington for the rest of this school year; however, I'd love to answer any questions you might have. You can contact me using any of these mediums below.
2001 E Lingelbach Ln
Bloomington, IN 47408
+1 219 883 9717