Multimodal Objective Sensing to Assess Individuals with Context (MOSAIC)
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The MOSAIC program seeks innovative approaches to unobtrusive, passive, and persistent measurement to predict an individual’s job performance.
The goal of the MOSAIC program is to improve the Intelligence Community’s capabilities to evaluate its workforce throughout their careers. The program aims to advance multimodal sensing to measure personnel and their environment unobtrusively, passively, and persistently both at work and outside of work, reduce the time and manpower required to process and integrate such data, and construct personalized and adaptive assessments of an individual that are accurate throughout the individual’s career.
Performers (Prime Contractors)
Lockheed Martin; The University of Memphis; The University of Notre Dame: The University of Southern California
- Behavioral science
- Cognitive psychology
- Human performance
- Mobile computing
- Context sensing
- Signal processing
- Data fusion
- Machine learning
- Data privacy and security
To access MOSAIC program-related publications, please visit Google Scholar.
- USC ISI Researchers Poised to Crack the Code on Reducing Workforce Stress
- What the Intelligence Community Wants to Get Out of Tracking Its Workforce
- Researchers to develop mobile sensor technology, improve job performance
- IARPA Funds Project to Track Worker Productivity with Sensors
- Peek @ performance: Duluth research part of national study about work productivity
- UMD research part of national study about work productivity