Amber Stubbs '05UG returned to her undergraduate alma mater to join the Simmons GSLIS faculty in Fall 2014. Stubbs received her doctorate in computer science from Brandeis University, after which she held a position as a Postdoctoral Associate in the Information Studies department of the State University of New York at Albany. She is co-author of Natural Language Annotation for Machine Learning with Professor James Pustejovsky of Brandeis University. Her primary research involves natural language processing with an emphasis on annotation methodology, temporal analysis of natural language, and data mining, particularly as they apply to bioclinical texts.
Her doctoral dissertation, "A Methodology for Using Professional Knowledge in Corpus Annotation," involved creating an annotation methodology to extract high-level information — such a hospital patient's medical diagnosis — from narrative texts. As part of that research, she also developed the Multi-Purpose Annotation Environment (MAE) and Multi-document Adjudication Interface (MAI) software, which is used at institutions around the world for natural language processing research.
Stubbs teaches computer science and library and information science courses about data structures and algorithms, programming and theory of programming languages, and information retrieval.
Additional information about Stubbs can be found at www.amberstubbs.net or by following her on Twitter @amber_stubbs.