I’m a graduate student at UCLA and a Lawrence Scholar at Lawrence Livermore National Lab. My research centers around unsupervised models of distributional semantics. More narrowly, I focus on Word Sense Induction Models which attempt to automatically learn the diverse meanings of a word without any external semantic knowledge. I’m actively working on publications in the field and most everything I do is open sourced on GitHub as part of the S-Space Project. I also developed some Word Sense Disambiguation tools centering around Princeton WordNet and a set of tools for directly modifying the WordNet hierarchy. All of this code is stored in the C-Cat Project.
I anticipate graduating in the near future or, if that fails, taking a temporary break from my academic life. I’m actively interested in taking a full time job related to Natural Language Processing and Machine Learning, especially if the company aspires to help make written information more accessible and understandable. Feel free to contact me using the information below.
Keith Stevens PhD student. Department of Computer Science, University of California, Los Angeles Lawrence Scholar. Lawrence Livermore National Lab
I was born in Northridge, CA in 1984. I attended the University of California, Los Angeles for both my undergraduate studies and graduate studies. During my undergraduate studies, I participated in the local chapter of IEEE and worked on the Natcar project. I also did research with the NeSL lab. After graduating, I spent a 9 month internship with Google working on a scalable server for a new product. I began my graduate studies in 2008. I have been studying under Professor Michael Dyer and have worked on several projects with David Jurgens. I’ve also spent internships at Google and Lawrence Livermore National Lab. In 2011, I joined LLNL as a Lawrence Scholar, where I do the majority of my research.