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Vasundara Varadan
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Photo  GE MedicalThe CNCI Program supports creative research underlying the analysis and design of intelligent engineering systems for control, communications, and computation. The program invites proposals for research that can lead to improved methods for analysis, design, and evaluation of complex systems that incorporate characteristics of non-linearity, uncertainty, scaleability, and non-stationarity.

Airtraf  Distributed systems and networks occur in telecommunications, power and energy, and transportation systems.

Hybrid systems require representation of both continuous and discrete-events and are of increasing interest in the study of networks, manufacturing, and transportation systems.

Neural diagramPhoto  Gary Conner 

Adaptive, learning and self-organizing systems offer potential for improved performance for systems with unknown models and changing characteristics, especially in biomedical and environmental applications.

High performance and domain-specific computation is applied to the development of simulation, design, and decision tools for engineering applications.

Photo  GE Medical Biologically-inspired methods and algorithms including neural networks, evolutionary computation, behavioral architectures, and intelligent agents for engineering applications are also of interest.

Click on Workshops for descriptions of recent workshops.

IS Current Awards

 PROGRAM DIRECTORS:

 AREAS OF INTEREST:

(Click on names for more detail)

Dr. Kishan Baheti

rbaheti@nsf.gov

Control Theory and Applications, Nonlinear and Robust Control, Hybrid Systems, Sensors-based Control

Dr. Vittal Rao
vrao@nsf.gov

Integrated Sensor Systems, Ad hoc Sensor and Actuator Networks; Sensor Data Fusion; Smart Systems; Wireless Communication Systems; Distributed Signal Processing; Computation Video; Cyberinfrastructure.

Dr. James A. Momoh
 jmomoh@nsf.gov

Power and Energy Systems, Reliability, Distributed and Intelligent Systems

Dr. Paul J. Werbos
 pwerbos@nsf.gov
Neural Network Computation and Control, Learning and Self-organizing Systems, Biologically-inspired Computation

 

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