# Difference between revisions of "Connections II"

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The ''Connections'' workshop series pulls together researchers mathematics, science and engineering who brought together novel ideas and tools from outside their traditional | |||

training to influence problems in areas as diverse as Internet protocols, fluid | |||

mechanics, biologic signal transduction, ecology, systems biology, | mechanics, biologic signal transduction, ecology, systems biology, | ||

finance, and multiscale physics | finance, and multiscale physics. An | ||

underlying theme of this workshop is to look forward to ways in which | underlying theme of this workshop is to look forward to ways in which | ||

future scientists can be educated in computation and quantitative | future scientists can be educated in computation and quantitative | ||

methods, to prepare them to interact broadly from the time they are | methods, to prepare them to interact broadly from the time they are | ||

students and throughout their academic careers. | students and throughout their academic careers. | ||

The first | |||

The first ''Connections'' workshop, held at Caltech in July 2004, | |||

brought together over 200 researchers in the fields of biology, | brought together over 200 researchers in the fields of biology, | ||

mathematics, physics, engineering and other disciplines to participate | mathematics, physics, engineering and other disciplines to participate | ||

in a 3 day conference exploring the the role of uncertainty and | in a 3 day conference exploring the the role of uncertainty and | ||

robustness in complex systems. | robustness in complex systems. For the second ''Connections'' workshop, we plan to organize the activities around three main themes (roughly one each day): | ||

* ''Simple models'' - one of the key techniques in dealing with complex, network systems is to identify simple models that capture essential phenomena. The CDS community has developed many techniques for doing such modeling, including basic input/output representations for systems and explicit model reduction techniques with undertainty guarantees. Other results include multiscale modeling, learning and ID from data, and model invalidation. | |||

For the second ''Connections'' workshop, we plan to organize the activities around three main themes (roughly one each day): | |||

* Simple models - one of the key techniques in dealing with complex, network systems is to identify simple models that capture essential phenomena. The CDS community has developed many techniques for doing such modeling, including basic input/output representations for systems and explicit model reduction techniques with undertainty guarantees. Other results include multiscale modeling, learning and ID from data, and model invalidation. | |||

* Short proofs - a key element of any successful theory for large scale networked systems is an understanding of how to generate proofs for complex phenomena. Lots continues to happen around proof automation. It connects with the first thread in that simple models help short proofs. The big win will probably be when model simplification and proof search are coupled through systematic relaxations that exploit symmetries. There are some nice starting points here, and lots of mathematicians are working on aspects of this problem. The tie with 1) is something that is not yet exploited as much as it could be. | * ''Short proofs'' - a key element of any successful theory for large scale networked systems is an understanding of how to generate proofs for complex phenomena. Lots continues to happen around proof automation. It connects with the first thread in that simple models help short proofs. The big win will probably be when model simplification and proof search are coupled through systematic relaxations that exploit symmetries. There are some nice starting points here, and lots of mathematicians are working on aspects of this problem. The tie with 1) is something that is not yet exploited as much as it could be. | ||

*Hard limits - a major challenge in network science is to define the fundmantal limits associated with limits. This thread would be about unifying the previously disconnected hard limits that arise due to thermodynamics, control, communications, and computing. There are now some pairwise connections, like the Bode-Shannon theory developed by Martins, Dahleh, Doyle and others. | * ''Hard limits'' - a major challenge in network science is to define the fundmantal limits associated with limits. This thread would be about unifying the previously disconnected hard limits that arise due to thermodynamics, control, communications, and computing. There are now some pairwise connections, like the Bode-Shannon theory developed by Martins, Dahleh, Doyle and others. |

## Revision as of 20:21, 27 March 2006

Connections II: |

Fundamentals of Network Science |

August 2006 Pasadena, CA |

The *Connections* workshop series pulls together researchers mathematics, science and engineering who brought together novel ideas and tools from outside their traditional
training to influence problems in areas as diverse as Internet protocols, fluid
mechanics, biologic signal transduction, ecology, systems biology,
finance, and multiscale physics. An
underlying theme of this workshop is to look forward to ways in which
future scientists can be educated in computation and quantitative
methods, to prepare them to interact broadly from the time they are
students and throughout their academic careers.

The first *Connections* workshop, held at Caltech in July 2004,
brought together over 200 researchers in the fields of biology,
mathematics, physics, engineering and other disciplines to participate
in a 3 day conference exploring the the role of uncertainty and
robustness in complex systems. For the second *Connections* workshop, we plan to organize the activities around three main themes (roughly one each day):

*Simple models*- one of the key techniques in dealing with complex, network systems is to identify simple models that capture essential phenomena. The CDS community has developed many techniques for doing such modeling, including basic input/output representations for systems and explicit model reduction techniques with undertainty guarantees. Other results include multiscale modeling, learning and ID from data, and model invalidation.

*Short proofs*- a key element of any successful theory for large scale networked systems is an understanding of how to generate proofs for complex phenomena. Lots continues to happen around proof automation. It connects with the first thread in that simple models help short proofs. The big win will probably be when model simplification and proof search are coupled through systematic relaxations that exploit symmetries. There are some nice starting points here, and lots of mathematicians are working on aspects of this problem. The tie with 1) is something that is not yet exploited as much as it could be.

*Hard limits*- a major challenge in network science is to define the fundmantal limits associated with limits. This thread would be about unifying the previously disconnected hard limits that arise due to thermodynamics, control, communications, and computing. There are now some pairwise connections, like the Bode-Shannon theory developed by Martins, Dahleh, Doyle and others.