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Knowledge Extraction via Comparison of Complex Computational Models to Massive Data Sets

This workshop, is devoted to applying and developing new techniques for the statistical analysis of massively complex models and the application of cutting edge visualization tools to drive data exploration. Currently, MADAI's analysis infrastructure and work-flows are being designed to address scientific challenges in Heavy-Ion Physics, Cosmology and Climate Sciences. Once fully developed these should be broadly extensible to other domains. (http://www.samsi.info/extraction). Co-sponsored by SAMSI and the NSF funded MADAI collaboration (Models and Data Analysis Initiative, http://madai.us).
When 29 July 2013 10:00 PM to
31 July 2013 06:00 PM
Where Research Triangle Park NC USA
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Advances in computation have significantly improved our abilities to model complex processes in science, engineering and the social sciences. In parallel, experimental observations have grown in size and complexity as well. Gaining knowledge and insight from these efforts requires rigorous comparison of models and data. The ever increasing sophistication of the models along with the size and detail of the heterogeneous data sets demands commensurate advances in the processes and practices of data analysis.

This workshop, co-sponsored by SAMSI and the NSF funded MADAI collaboration (Models and Data Analysis Initiative, http://madai.us) is devoted to applying and developing new techniques for the statistical analysis of massively complex models and the application of cutting edge visualization tools to drive data exploration. Currently, MADAI's analysis infrastructure and work- flows are being designed to address scientific challenges in Heavy-Ion Physics, Cosmology and Climate Sciences. Once fully developed these should be broadly extensible to other domains.

The purpose of the workshop is to introduce a broader base of domain scientists in the aforementioned communities to statistical and visualization tools that facilitate knowledge extraction via complex model to data comparisons. The workshop will also provide opportunities for the Statistical Science community to learn about recent developments in complex modeling and computer experiments as well as engage in new collaborative ventures. Two half-day hands-on tutorials will showcase a modular visualization platform (based on Paraview) that allows for advanced visualization of complex model dynamics as well as statistical analysis tools. The statistical tools are based on Gaussian process surrogate models for rapid exploration of a model's parameter space.

 

APPLICATION

To begin the application process login and register, then click on "Apply for Workshop" button at the top of this page. When you have completed the form, be sure to click on the green "Complete Application" button.

This form also includes the application for financial support. You will be notified in a timely manner if your participation will be possible; regrettably, limited seating will preclude acceptance of all applications. New researchers (graduate students, postdocs, and faculty in the early stages of their careers) and members of underrepresented groups are especially encouraged to apply.

The application/registration deadline is July 8, 2013. Note, however, that capacity might be reached before this deadline. Also, any application that requests support for expenses should typically be submitted at least 6 weeks in advance of the workshop.

Please make reservations at the Radisson RTP as soon as possible. The SAMSI room block and rate ($91) is effective until July 8, 2013. After this date, there is no guarantee a room will be available. If you have a change in plans, individual room reservations must be cancelled 72 hours prior to arrival. Check-in is at 3:00 PM; check-out is 12:00 noon.

If you need further information please send an email to md@samsi.info

Tentative Schedule

Monday 7/29/13:
* afternoon session (2pm to 6pm): Domain Sciences

Tuesday 7/30/13:
* morning session (8:30am to 12:30pm): Scientific Visualization
* lunch break (12:30pm to 1:30pm)
* afternoon session (1:30pm to 6:00pm): Visualization Tutorial

Wednesday:
* morning session (8:30am to 12:30pm): Statistical Methodology
* lunch break (12:30pm to 1:30pm)
* afternoon session (1:30pm to 6:00pm): Statistical Tools Tutorial

Attendees who wish to work on their own scientific problems utilizing techniques and tools introduced at the workshop or form new collaborative ventures will have the opportunity to spend the remainder of the week at Duke University and interact with each other, the workshop organizers and the tutorial instructors.

 

Workshop Organizers:
Steffen A. Bass, Duke University
Scott Pratt, Michigan State University
Russell M. Taylor II, University of North Carolina
Robert Wolpert, Duke University

Co-sponsored by: Models and Data Analysis Initiative
Host Website: https://madai-public.cs.unc.edu/

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