Information Fusion over Sources of Unknown Reliabi
at ORAU Workforce Solutions

Date Posted: 12/23/2018

Opportunity Description

Information Fusion over Sources of Unknown Reliability Information fusion requires the processing of disparate hard and soft data sources over various operational contexts. The reliability of the data sources is generally unknown a priori. These sources might report noisy data, or worse yet, intentionally report misleading data. Much work has been done in the sensor network community to detect and repair sensor faults. Recently, many efforts in trust/reputation systems and truth-finding have led to methods to jointly estimate the credibility of reports and the reliability of the sources. Most all of these methods are focused on a single information domain, and they do not exploit the semantic relations between the hard/soft reports or the social relations between the data sources themselves. This research opportunity considers both the theory and applications for detecting and resolving conflicting data from disparate sources and extracting/estimating the resulting information. It is anticipated that this research will draw upon uncertain representations such as basic belief mass assignment in belief theory, reasoning using uncertain probabilistic logics, trust estimation in reputation and/or truth-finding systems, and finally social network theory for modeling the sources. References: Wang D, Kaplan L, Le H, Abdelzaher T: ACM Intl. Conf. on Information Processing in Sensor Networks, pp. 233-244, 2012 Kaplan L, Sensoy M, de Mel G: IEEE/ISIF Intl. Conf. on Information Fusion, 2014 Click here for more information

Opportunity Snapshot

  • Employee Type: Full-Time
  • Location: Adelphi, MD
  • Opportunity Type: Other
  • Experience: Not Specified
  • Date Posted: 12/23/2018

About Us

Oak Ridge Associated Universities (ORAU) administers Science, Technology, Engineering and Mathematics (STEM) research participation programs for civilians such as:

The U.S. Army Research Laboratory (ARL) Research Associateship Program (RAP) allow Postdoctoral Fellows, Journeyman Fellows (undergraduate and graduates students and recent graduates), Senior Researchers, and Summer Faculty engage in research initiatives of their own choice, that are compatible with the interests of the government and will potentially contribute to the general effort of the ARL. Scientists and engineers at ARL help shape and execute the Army's program for meeting the challenge of developing technologies that will support Army forces in meeting future operational needs.

Research opportunities include, but are not limited to the following disciplines: Aerospace Engineering, Anthropology, Archeology, Biology, Biochemistry, Biological Engineering, Biomechanical Engineering, Biomedical Engineering, Chemical Engineering, Chemistry, Computer Science, Computer Engineering, Electrical Engineering, Environmental Health Risk Assessment, Environmental Science, Entomology, Epidemiology, Ergonomics, Geology, Health Education Mechanical Engineering, Materials Science, Mathematics, Nanotechnology, Photonics, Physics, Public Health Economics, Public Health Policy, and more.

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