Science of Information, Computation, Learning, and Fusion

Program Description

The U.S. Air Force and Space Force collects vast amounts of data through various modes at various times in order to extract and derive needed “information” from these large and heterogeneous (mixed types) data sets. Some data, such as those collected from magnetometers, register limited information content which is more identifiable at the sensor level but beyond human’s sensory reception. Other types of data, such as video cameras or text reports, possess more semantic information that is closer to human cognition and understanding. Nevertheless, these are instances of disparate data which encapsulate different types of “information” pertained to,

In order to understand and interpret information contained in various data sources, it is necessary to extract relevant pieces of information from these datasets and to make inferences based on prior knowledge and probabilities. This bottom-up processing direction needs conceptually driven reasoning to integrate or fuse the previously extracted snippets of information by leveraging domain knowledge. Furthermore, the top-down processes can offer causal explanation or causal inference, generate new hypotheses, verify or test hypotheses in light of observed datasets. Between the data driven and conceptually-driven ends, there may reside different levels of abstraction in which information is partially extracted and aggregated based on the nature of applications.

Basic Research Objectives can be found in this program’s section of the BAA.

You are highly encouraged to contact our Program Officer prior to developing a full proposal to briefly discuss the current state-of-the-art, how your research would advance it, and the approximate cost for a three (3) to five (5) year effort, and if there are any specific submission target dates.

Solicitation
BAA

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Program Officer
Dr. Doug Riecken is a trained concert pianist with a B.A. from the Manhattan School of Music and studies at the Julliard School of Music. He spent many years performing classical, jazz, and rock styles on international concert tours with world-renowned artists before he switched to a career in cognitive and computing science. He received his PhD from Rutgers University under thesis advisor Dr. Marvin Minsky from MIT; a founding father of artificial intelligence. Riecken and Minsky spent 30+ years in friendship researching learning and the mind. Dr. Riecken’s career is grounded from 15+ years of research at ATT Bell Laboratories Research (during the classic days in AREA 11 Research) and later 11 years at IBM Watson Research. During that time his focus was in multimedia systems, intelligent multi-agent systems, and computational commonsense reasoning and learning. In 2011 he combined his passion for teaching and conducting research at Columbia University and later went on to conduct research as a principal knowledge architect at both Dow Jones and the Federal Reserve Bank of New York. Dr. Riecken is a thought leader in the areas of big data analytics and machine learning, human-computer interaction and design, knowledge discovery and data mining, global cloud enterprise architectures, and privacy management. He joined the Air Force Office of Scientific Research as a program officer in 2014 and is a senior member of the AFRL ACT3 team.