Defense Advanced Research Projects AgencyTagged Content List

Analytics for Data at Massive Scales

Extracting information from large data sets

Showing 70 results for Analytics RSS
Program Manager
Dr. Matt Turek joined DARPA’s Information Innovation Office (I2O) as a program manager in July 2018. His research interests include computer vision, machine learning, artificial intelligence, and their application to problems with significant societal impact.
Program Manager
Mr. Ian Crone joined DARPA in June 2017 to develop, execute, and transition programs in cybersecurity and cyberspace operations.
Program Manager
Mr. Steve Jameson joined DARPA in August 2014. His current research focuses on technologies to enable situation understanding, improve effectiveness and timeliness of decision-making, and build trust between humans and autonomous reasoning systems. Specific interests include knowledge representation, techniques for causal modeling, reasoning, and inference, as well as technologies to support mixed initiative reasoning, with a focus on enabling non-expert users to effectively interact with automated reasoning systems.
11/13/2018
The Defense Advanced Research Projects Agency (DARPA) Young Faculty Award (YFA) program aims to identify and engage rising stars in junior faculty positions in academia and equivalent positions at non-profit research institutions and expose them to Department of Defense (DoD) and National Security challenges and needs. In particular, this YFA will provide high-impact funding to elite researchers early in their careers to develop innovative new research directions in the context of enabling transformative DoD capabilities.
12/12/2018
The Defense Sciences Office (DSO) at the Defense Advanced Research Projects Agency (DARPA) is soliciting innovative research proposals for the development and deployment of automated tools to assign Confidence Scores (CSs) to different kinds of Social and Behavioral Science (SBS) research results and claims. CSs are quantitative measures that should enable someone to understand the degree to which a particular claim or result is likely to be reproducible and/or replicable.