I am a first year doctoral student at UC Berkeley in computer science (specialization: artificial intelligence). My research focuses on natural language processing and cognitive modeling. I am a recent Stanford graduate (M.S., Symbolic Systems) and worked for the past year in Stanford's Natural Language Processing Group as a research programmer for Professor Chris Manning. My master's thesis involved creating computational models of students' learning in intelligent tutoring systems, and I was advised by Professor Dan Schwartz. My other interests include feminist and queer activism and public health. I am originally from northern Minnesota and miss having a lake in my backyard - but the lack of snow in the Bay Area is a plus! Other interests include jigsaw puzzles, rollerblading and hiking, sci-fi books, and SET.

Education:

Ph.D. in progress in Computer Science at UC Berkeley, August 2008-present

M.S., Symbolic Systems, Stanford University, June 2007.

B.S., Symbolic Systems, Focus in Artificial Intelligence, Stanford University, June 2007, with Distinction.

B.A., Feminist Studies, Focus in Women's Sexuality, Stanford University, June 2007, with Distinction.

Relevant Work Experience:

Research Programmer. Natural Language Processing Group, Computer Science, Stanford University, July 2007-August 2008.

Publications:

Rafferty, Anna N. and Christopher D. Manning. "Parsing Three German Treebanks: Lexicalized and Unlexicalized Baselines." Proceedings of Workshop on Parsing German, ACL-HLT 2008. [PDF]

de Marneffe, Marie-Catherine, Anna N. Rafferty, and Christopher D. Manning. "Finding Contradictions in Text." Proceedings of ACL-HLT 2008. [PDF]

Rafferty, Anna N. and Michael Yudelson. "Applying Learning Factors Analysis to Build Stereotypic Student Models." Proceedings of Artificial Intelligence in Education, 2007. Winner of Best Paper Award for the Young Researcher Track. [PDF]

Marie-Catherine de Marneffe, Bill MacCartney, Trond Grenager, Daniel Cer, Anna Rafferty and Christopher D. Manning. "Learning to distinguish valid textual entailments." Proceedings of The Second PASCAL Challenges Workshop. 2006. [PDF]

Slides:

From presentation of above AIED 2007 paper. [PDF]

From Symbolic Systems forum presentation of my master's research. [PDF]

Master's Thesis:

"Using FACT to Challenge Assumptions: Frequency, Accuracy, Choice, and Timing in Machine Learning." Symbolic Systems Department, Stanford University, June 2007. Advised by Professor Dan Schwartz, with second reader Professor Ken Koedinger. [RaffertyMSThesis.pdf]

Resume [Resume]

Contact: rafferty AT eecs DOT berkeley DOT edu