Purpose: As an undergraduate at the University of Utah, from 1993-1997, I received significant financial support from the university and from private individuals who provided scholarships for students. I am delighted to now be in a position to help out current students in a similar way.
Details: This scholarship provides $1000 each year to one undergraduate student at the University of Utah. This student is selected by the Artificial Intelligence faculty in the Computer Science department on the basis of GPA, a focus on AI or Machine Learning, and financial need. To apply, contact the CS department.
Past Recipients:
Even though I knew I wanted to work with computers from a young age, I only became interested in Artificial Intelligence during my Jr. High years. Going through Jr. High and High School, I was eager to start a Computer Science degree so I would be able to learn more about AI. As I finish my degree, I plan on continuing to study AI. I am currently taking a Natural Language processing class, and will take a Machine Learning class in the Spring. My other interests involve Linguistics, and I would be thrilled to find a job involving NLP so I could work in both field. I have studied some Latin and Japanese, and would like to study Russian in the future. While I'm only fluent in English, I enjoy learning about different languages. I plan on graduating in 2007, and if I don't remain in Utah, I'd like to move back to Texas to be near my family.
I am finishing my BS in CS this semester. In the last year I have been working on my biggest interest: applying the principals of NLP to the field of law. The language of the law and its practitioners is fairly homogenous with limited and specific word usage - making it a good candidate for machine understanding. Initially I considered the possibilities of "patent understanding" to aid inventors in their search for prior art before filing a patent. I soon moved on to a more tractable problem: "license understanding." I recently presented a proposal to Professor Lee Hollaar on the subject. The proposed system would improve the usefulness of now-ubiquitous "click-wrap" licenses. I will soon present my work to David Bean, a former PhD student of Ellen Riloff and co-founder of Attensity, who has offered to make his commercial tools available in developing my system. There are a myriad of possibilities where these two fields intersect: using NLP to understand legal documents and using the law (i.e. patents) to protect inventions in NLP and AI related fields. I hope to apply my efforts in both directions. This fall I start law school at George Washington - the top intellectual property law school on the East Coast. David Bean's company maintains an office in DC, where I would hope to keep contact with the industry while I complete law school.
My name is Jacob Quist, born and raised in Salt Lake City, Utah. I have two parents and one older sister who haunted my childhood with relentless teasing and taunting. Growing up, I was the obscure but overly witty computer geek who was always called by friend's parents to fix their computers. My interests are not limited to computers alone. My aspirations also include driving a Harley on every continent. I'm also very interested in the Japanese Language & Culture. I'm doing the BS/MS program and plan to graduate 2006 (maybe?). I hope to work with AI and break the current AI barriers.