Conferences & Workshops

Starting in 2000 the research community has organized numerous DDDAS related activities, to include workshops, panels and numerous forms which are listed below.

Program Overview

The 2017 PI meeting was held in Dayton, Ohio, Sept 6-8.

2014 DDDAS Program PI Meeting was held December 1-3, 2014 at the IBM Thomas J Watson Research Center, Yorktown Heights, NY. Agenda for the DDDAS Program PI Meeting 2014 and presentations.

DDDAS Conferences, Forums and Workshops

Principal Investigator Workshops


ASME/ADTEC2014 – DDDAS Keynotes and Panel

Keynote 1: Dynamic Data Driven Application Systems (DDDAS) by Dr. Frederica Darema, AFOSR Manager Keynote2: Top Ten Ways that DDDAS Can Save the World by Prof. Sangtae Kim, Purdue University
Abstract: The DDDAS (Dynamic Data-Drive Application System) paradigm is now firmly established as a powerful framework for the integration of theoretical, experimental and computational approaches to better understand complex natural phenomena and to furnish more robust solutions to urgent societal challenges. This is especially true in the current context where “big data” meets “dynamic data” across disciplinary boundaries. In this vein and as we approach two decades of DDDAS efforts across a broad spectrum of the STEM landscape, we consider a “top ten” list/format as a way to catalog successes from the past and to project unexpected opportunities of the future.

AFOSR Panel: Dynamic Data Driven Application Systems (DDDAS) in the Age of Big Compute and Big Data, Moderators: Young-Jun Son and Abani Patra
Abstract: The DDDAS paradigm and constituent methodologies are creating transformative advances in areas as wide ranging as smart materials and grids to unmanned aerial systems, volcanic ash tracking, and manufacturing. While the early years have produced impressive results, the true power of the DDDAS paradigm is being made more apparent now that ubiquitous big data and big compute enable the infrastructures for computing and analysis implicit in the success of the DDDAS methods. This panel brings together a broad range of experts in the application domains as well as core DDDAS methodologies. The panel will highlight examples of advances enabled through DDDAS and will also address critical challenges in uncertainty quantification, dynamic data assimilation, and dynamical systems that can be effectively exploited through DDDAS methods, to created advanced capabilities in complex engineered systems and processes.


The International Conference for High Performance Computing, Networking, Storage and Analysis (SC’14)

Panel: InfoSymbioticSystems/DDDAS – The Power of Dynamic Data Driven Application Systems and The Next Generation of Big-Computing and Big-Data
Abstract: Dynamic Data-Driven Application Systems (DDDAS) is a paradigm whereby application simulation-models of natural and engineered systems become a symbiotic feedback control system with the application’s instrumentation-measurements. Through this dynamic integration across computing and instrumentation DDDAS creates new capabilities for more accurate analysis, prediction, and control in application systems. The instrumentation-data considered, real-time or archival, and resulting from heterogeneous sensor- and actuation-networks and mobile devices, are the next wave of Big-Data. DDDAS enables intelligent management of such Big Data and extends the traditional notions of Big-Computing to encompass the diverse range of platforms from the exa-scale, to sensors and controllers, and to mobile systems. The panel will discuss new DDDAS-enabled and DDDAS-driven capabilities in important application areas such as civilian and national security infrastructures; environmental systems; medical care systems; privacy and security; systems software and hardware supporting DDDAS environments and in the context of commonalities in underlying exa-scale and sensor-scale technologies.
Moderator/Panelist Details:

Workshop Descriptions

ICCS/DDDAS Workshop Series

This workshop covers several aspects of the Dynamic Data Driven Applications Systems (DDDAS) concept, which is an established approach defining a symbiotic relation between an application and sensor based measurement systems. Applications can accept and respond dynamically to new data injected into the executing application. In addition, applications can dynamically control the measurement processes. The synergistic feedback control-loop between an application simulation and its measurements opens new capabilities in simulations, e.g., the creation of applications with new and enhanced analysis and prediction capabilities, greater accuracy, longer simulations between restarts, and enable a new methodology for more efficient and effective measurements. DDDAS transforms the way science and engineering are done with a major impact in the way many functions in our society are conducted, e.g., manufacturing, commerce, transportation, hazard prediction and management, and medicine. The workshop will present such new opportunities as well as the challenges and approaches in technology needed to enable DDDAS capabilities in applications, relevant algorithms, and software systems. The workshop will showcase ongoing research in these aspects with examples from several important application areas. All related areas in Data-Driven Sciences are included in this workshop.


IPDPS Workshop Series

This workshop provides a forum for an overview, project presentations, and discussion of the research fostered and funded by the NSF Next Generation Software (NGS) Program.  The program announced in October of 1998, has had several calls for proposals (in FY99, FY01, FY02,
FY03, and FY04), and supports research in two broad technical thrusts: One is in developing Technology for Performance Engineered Systems
(TPES) for the Design, Management and Runtime Support of Computing Systems and Applications.  The other thrust (Complex Application Development Support Systems – CADSS) seeks to create new systems’ software technology, including enhanced compiler capabilities, and tools for the development, runtime support and dynamic composition of complex applications executing on complex computing platforms, such as Computational Grids, assemblies of embedded systems and sensor systems, as well as high-end platforms (Grids-in-a-Box) and special purpose processing systems.