Noah Smith

photo of Noah Smith نوح سميث
ノア スミス
Νώε Σμιθ
Ной Смит
노아 스미스
Photo by Karen Meyers.
Noah Smith designs algorithms for automated analysis of human language. He often exploits the web to this end, including mining the web for translations (Resnik and Smith, 2003), measuring public opinion from social messages (O'Connor et al., 2010), and inferring geographic linguistic variation (Eisenstein et al., 2010).

Smith has also contributed algorithms tackling the core problems of natural language processing: parsing sentences into syntactic representations (Eisner et al., 2005; Martins et al., 2009) and semantic representations (Das et al., 2010; Flanigan et al., 2014), as well as cross-cutting techniques for unsupervised language learning (Smith and Eisner, 2005; Cohen and Smith, 2009). His 2011 book, Linguistic Structure Prediction, synthesizes many statistical modeling techniques for language.

Such methods advance applications for automatic translation (Al-Onaizan et al., 1999; Gimpel and Smith, 2011), empirical work in the social sciences (Kogan et al., 2009; Yano et al., 2009, Sim et al., 2013) and humanities (Bamman et al., 2014), and education (Heilman and Smith, 2010), and other next-generation language technologies.

Smith is associate professor of Computer Science & Engineering at the University of Washington. Formerly, he was assistant professor (2006–11), Finmeccanica associate professor (2011–14), then tenured associate professor (2014–15) at the Language Technologies and the Machine Learning Department in the School of Computer Science at CMU. Before that, he was a Hertz Foundation Fellow at Johns Hopkins University, where he completed his Ph.D. in 2006. He is a clarinetist, tanguero, and swimmer.


Active courses at CMU:

Recent tutorials: Older teaching:

Research in NLP (Natural Language Processing)

How can computer programs intelligently process text data? My research brings together linguistic abstractions, statistical reasoning, and computational formalisms to develop general NLP methods and models. The results are used in software applications (e.g., machine translation, information extraction, text mining, question answering, and text-driven forecasting) and also serve scientific discovery wherever text serves as data (e.g., sociolinguistics, political science, and economics).

Some research activities and events I have helped organize include:

Curriculum vitae highlights

See also: biographical blurbs and long C.V.