InfoSym DDDAS Conf.v3

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Organizing Committee Co-Chairs Sai Ravela [email protected] Erik Blasch [email protected] Communications Chair Alex Aved [email protected] Program Agenda • Keynotes • Talks • Posters • Panels • Workshops

About InfoSymbiotics/DDDAS DDDAS is a paradigm whereby instrumentation data are dynamically integrated into an executing application model while in reverse the executing model controls the instrumentation. The scope of application areas where this paradigm can engender transformative capabilities ranges from the nano-scale to the extra-terra-scale. For example, it includes applications in (but not limited to) aerospace, critical infrastructures, biological sciences and geosciences, cyber security, and resilient architectures. Through the DDDAS paradigm, data inputs integrated into dynamically determined parts of the model phase-space increase modeling speed and accuracy for enhanced analysis and prediction of system evolution and behavior and create decision support systems with the accuracy of full-scale models. Dynamic control of instrumentation enables efficient operation of large instruments and adaptive management of distributed and heterogeneous collections of sensor and controller resources. The DDDAS paradigm also implies dynamic integration across the range of computational platforms – from the high-end to the real-time. It synergistically exploits computing at the high-end as well as the tremendous computational power of collections of sensors and controllers (Large-Scale-Big-Computing) and the second wave of “Big Data” that they entail (LargeScale-Big-Data). Participants from academia, industry, government and international counterparts will report original work where DDDAS research is advancing scientific frontiers, engendering new engineering capabilities, and designing operational processes. The InfoSymbiotics / DDDAS Conference spans a broad set of topics and interests.

Call for Contributions

Important Dates Intent to Submit: May 1

1. Application Systems that exploit the symbiotic feed-back control nature between dynamic data-driven and model-based, knowledge driven processes. 2. Systems methodology that optimizes the entire numeric and non-numeric Modeling, Estimation, Sampling, Planning and Control cycle for Efficiency, Robustness, Resilience, Agility or Trust. 3. Stochastic Systems theory for multifidelity modeling, uncertainty quantification, with the integration of data. 4. New instrumentation methods that support DDDAS environments. 5. Data fusion, inference and learning, and decision support.

Abstracts Due:

June 1

Application Areas

Abstract Reviewed:

July 1

Full Papers:

August 15

Full Papers Reviewed:

October 15

The scope of application areas covered include: aerospace (e.g., structural health monitoring, air vehicle controls and decision support, aero & thermos-dynamics, combustion, surveillance), critical infrastructures (e.g., power-grids, transportation systems, smart cities), bio-, geo-, and spacesciences (e.g., environment analysis, health monitoring, disaster response, space weather), and cyber security, systems software and resilient architectures (for high-end computing integrated with the real-time).

Camera-Ready Submissions:

November 15 The dates for abstract submissions and other details will be posted to the conference website.

Important Dates Please check for news and updates at: http://www.1dddas.org/conf/2016/

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