Summaries - Research
Back CMIS1 FY20 Research Support
|Division||Graduate School of Engineering & Applied Science|
|Department||Electrical & Computer Engineering|
|Investigator(s)||Scrofani, James W.|
|Sponsor||Department of Defense Space (DoD)|
Multi-INT is an interdisciplinary field seeking to understand how various data analytic related models and methodologies can vastly improve anomaly detection, situation awareness, and decision making.
In an era where collection of data has outpaced the ability of technology and humans to make sense of all available information, the orthodox notion of working in, or specializing in, independent, single data domains such as electronic communications, multiple types of imagery, and social media data feeds is undergoing significant reconsideration. In fact, Multi-INT approaches employed across the business processes of all types must be examined, and integrated notions of requirements generation, tasking, collection and processing must be considered.
This work seeks to produce research outcomes that significantly increase the ability of the U.S. Navy, U.S. Department of Defense, and other U.S. government agencies to better integrate multiple data streams.
|Keywords||Adversarial Machine Intelligence Anomaly Detection Automated Sensemaking Black Swan Theory multi-int|
|Publications||Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal|
|Data||Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal|