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All Projects

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Brandeis PRIME

Privacy-preserving Information Mediation for Enterprises

The PRIME project seeks to create a flexible platform for research, development, experimentation, demonstration and deployment of techniques that will be important for learning how to build systems that share sensitive information across enterprises while protecting against undesirable uses of that information.


Learning from Experience to Enable Proactive Decision Support

The ELF project seeks to develop an experience-based learning framework that mines information from prior problem-solving activities to enable proactive information gathering in support of current tasks. This framework employs machine learning methods that generalize from past activities to identify preferred sources for specific information needs, to provide mechanisms for retrieving data required to support decision making, and to suggest processes in support of current tasks.


Semantically Enabled Assessment in Virtual Environments (SAVE)

The SAVE framework supports training in virtual environments through automated assessment of learner performance and tools for content authoring.


Probabilistic Reasoning as Symbolic Evaluation

To develop lifted inference algorithms for solving probabilistic models expressed by Turing-complete probabilistic programming languages.


Content-Based Mobile Edge Networking

The CBMEN program seeks to develop the network services and transport architectures to enable efficient, transparent distribution of content in mobile ad hoc network environments.


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.


Multi-Threaded Missions and Means Framework

This project explores the utilization of a multiagent modeling and simulation environment where multiple military domains or threads (e.g. Logistics, Transportation, Combat Operations, Intelligence, Engineering) can be described in terms of tasking and capabilities and their mission interactions simulated over some mission scenario time horizon.


Intelligent Question Answering in the HIV Domain

Natural language technology and deductive inference are applied to allow a researcher to access online HIV databases through English queries.


Behavioral Probes

Activity Recognition in outdoor settings.

This website does not contain information on all of our past or present projects.
For further information please contact us.

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