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Dr Dayne Freitag

Program Director
Artificial Intelligence Center

SRI International
9988 Hibert St., Suite 203
San Diego CA 92131

Phone:  858-527-1412
Fax: (650) 859-3735

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Biography and Interests


Dayne Freitag, Ph.D., is director of the Advanced Analytics group in SRI’s Artificial Intelligence Center. His research seeks to apply artificial intelligence to information assimilation, management and exploitation. Specific areas of interest include natural language processing and computational linguistics; machine learning; data mining; information extraction; information retrieval; information diffusion; and information integration.

Freitag has served as principal investigator for a number of research projects including several large, multi-institutional efforts. His research goals have focused on the automation of data science; the automatic extension of mechanistic models through machine reading; knowledge federation over diverse information sources through data analytics and natural language processing; explaining the spread of ideas through online communities; and novel approaches to institutional knowledge management using controlled English.

Before joining SRI in 2009, Freitag led and participated in fundamental research at Fair Isaac Corporation with a special focus on the rapid deployment of textual information extraction, and the unsupervised induction of linguistic structure and function through corpus analysis. He also was a research scientist and vice president for technology at Burning Glass Technologies, LLC, which develops solutions for human resource management using machine learning and natural language processing. Between 1998 and 2000, Freitag conducted information extraction and information retrieval research at Just Research.

Freitag holds a B.A. in English literature from Reed College, and a Ph.D. in computer science from Carnegie Mellon University.


Past Projects


Copernicus: Automating Emergence Detection

IARPA’s Foresight and Understanding from Scientific Exposition (FUSE) Program seeks to develop automated methods that aid in the systematic, continuous, and comprehensive assessment of technical emergence using publicly available information found in published scientific, technical and patent literature. SRI’s team uses a theory-directed extension of best-of-breed language and network modeling techniques to produce the Copernicus system. SRI’s CSTED leads the theory of emergence task.


DoVETAIL: Domain Vocabulary Extraction and Transduction, and Auto-Induction of Layout

The ability to quickly produce actionable intelligence from unanticipated, multiple, varied data sets require research advances in two key areas: (1) alignment of data models; and (2) advanced analytic algorithms. Making advances in these two research areas, and fully characterizing the performance of the research results, is the focus of this project, which is part of the IARPA Knowledge Discovery and Dissemination (KDD) Program.


Extensible Controlled Language for Advanced Information Retrieval

The ECLAIR project sought to facilitate the collaborative management of knowledge assets by providing an extensible controlled English for the annotation of source material. Using ECLAIR, analysts could describe the contents of source documents in simple sentences, the semantic interpretation of which was used for sophisticated meaning-based retrieval.


Meme Epidemiology

Meme Epidemiology sought to explain the propagation of ideas in online communities using techniques from epidemiology. We adopted a strict interpretation of "meme": an idea subject to linguistic expression and useful as a marker of cultural group membership.


The following are in reverse chronological order of publication.
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