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VANESSA: Virtual Analysis Networks and Explanations for Social Sensing Analysis

Award Information
Agency: Department of Defense
Branch: Army
Contract: W911NF-19-P-0017
Agency Tracking Number: A18B-008-0195
Amount: $148,111.02
Phase: Phase I
Program: STTR
Solicitation Topic Code: A18B-T008
Solicitation Number: 18.B
Timeline
Solicitation Year: 2018
Award Year: 2019
Award Start Date (Proposal Award Date): 2018-12-12
Award End Date (Contract End Date): 2019-06-13
Small Business Information
319 1st Ave North Suite 400
Minneapolis, MN 55401
United States
DUNS: 103477993
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Sonja Schmer-Galunder
 Senior Research Scientist
 (415) 604-6293
 sgalunder@sift.net
Business Contact
 Harry B. Funk
Phone: (612) 578-7438
Email: hfunk@SIFT.net
Research Institution
 Smart Information Flow Technologies, d/b/a SIFT
 Michael Rosen Michael Rosen
 
319 1st Ave North, Suite 400
Minneapolis, MN 55401
United States

 (410) 637-6269
 Nonprofit college or university
Abstract

SIFT, JHU medicine and University of Central Florida are proposing to develop VANESSA (Virtual Analysis Networks and Explanations for Social Sensing Analysis) - a social sensing platform providing team diagnostics of interacting teams and recommendations for enhanced team functioning of human and human-cyber teams. The overall goal of VANESSA is to develop an adaptive technology platform with a focus on socially relevant data streams synergizing cognitive, physiological and behavioral processes within inidividuals and teams. This will provide a multi-level tool to generate team diagnostics for the assessment of 1) individuals within teams, 2) interactions between team members and 3) patterns between teams, resulting in scalable recommendations for team composition and interventions. Our primary objectives in Phase I will be to address the first two challenges – 1) development of intelligent social sensing platform for data collection and management and 2) design algorithms for team-level diagnostics. Our Phase 1 effort will also produce an initial design and execution plan to develop Phase 2 challenges that calls for a recommendation engine and visualizations of the network representations.

* Information listed above is at the time of submission. *

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