Information Sciences

Army Research Office
P.O. Box 12211
Research Triangle Park, NC 27709-2211

Commercial: 919-549-4321
Fax: (919) 549-4303

DSN: 832-4321

Dr. Randy Zachery, Director

Research in the Information Sciences is focused on discovering, understanding, and exploiting the mathematical, computational, and algorithmic foundations that are expected to create revolutionary capabilities for the future Army. Discoveries in this area are expected to lead to capabilities in materials, the information domain, and Soldier performance augmentation, well beyond the limits facing today's Army.

Computing Science

Is focused on understanding the fundamental principles and techniques governing computational models and architectures for intelligent, trusted, and resilient computing. It provides the foundation for revolutionary capabilities for future warfighters in signal and data processing, data fusion, and social informatics.

  • Information Processing and Fusion
  • Computational Architectures and Visualization
  • Information and Software Assurance
  • Intelligent Systems
  • Advanced Computing (International Program)

Network Science

Pursues discovery and understanding of robust mathematical principles and laws that govern a broad variety of networks including organic, social, and electronic. These principles and laws serve as the foundation for the creation of algorithms which may be leveraged for autonomous system reasoning.

  • Multi-Agent Network Control
  • Wireless and Hybrid Communication Networks
  • Social and Cognitive Networks
  • Communications and Human Networks
  • Intelligent Information Networks
  • Network Science and Intelligent Systems (International Program)

Mathematical Sciences

Underlies and enables understanding of complex nonlinear systems, stochastic networks and systems, mechanistic models of adaptive biological systems and networks, and the vast variety of partial differential equation based phenomena. Nonlinear structures and metrics for modeling and studying complex systems are sought, as is creating theory for the control of stochastic systems, spatial-temporal statistical inference, data classification and regression analysis, predicting and controlling biology through hierarchical and adaptive models, enabling new capabilities through bio-inspired techniques, creating high-fidelity computational principles for sharp-interface flows, solving inverse problems, deriving reduced-order methods, and developing computational linguistics.

  • Modeling of Complex Systems
  • Probability and Statistics
  • Biomathematics
  • Computational Mathematics

Last Update / Reviewed: December 12, 2017