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Difference between revisions of "Aaron Clauset"

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Aaron Clauset [[http://www.santafe.edu/~aaronc/ homepage]] is an Omidyar fellow at the Santa Fe Institute (since 2006), and will be an assistant professor in computer science at CU Boulder starting Fall 2010. He is an alumnus of the CSSS 2003 (Santa Fe), and has been a lecturer at the Santa Fe summer school since 2007, and the Beijing summer school since 2008.
 
Aaron Clauset [[http://www.santafe.edu/~aaronc/ homepage]] is an Omidyar fellow at the Santa Fe Institute (since 2006), and will be an assistant professor in computer science at CU Boulder starting Fall 2010. He is an alumnus of the CSSS 2003 (Santa Fe), and has been a lecturer at the Santa Fe summer school since 2007, and the Beijing summer school since 2008.
  
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Aaron's research interests are broad, and currently include statistical patterns in complex systems, complex networks (structure, function, methods; technological, biological and social), statistical inference and machine learning, power-law distribtions (data, mechanisms); laws and contingencies in conflict (terrorism, war), human social dynamics; the Internet (structure, routing, security); adaptive and evolutionary computation; self-organization; robustness; innovation; and algorithmic game theory.
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Much of Aaron's work focuses on understanding how to separate what is contingent from what is constrained or structured in a complex phenomenon. This general idea can be applied to complex social, biological, and technological systems. It has strong emphases on discovery and modeling, using both numeric and analytic tools, and it draws heavily on ideas and tools from computer science, statistics, machine learning, and statistical physics. Most recently, Aaron has been applying these ideas to understand the large-scale structure of complex networks, the mechanisms and constraints that give rise to morphological diversity among species, and the patterns of terrorists.
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* [[Media:CSN_07_PowerlawDistributionsInEmpiricalData_arxiv.pdf|"Power-law distributions in empirical data." A. Clauset, C. R. Shalizi and M. E. J. Newman. arXiv:0706.1062 (2007).]]
 
* [[Media:CSN_07_PowerlawDistributionsInEmpiricalData_arxiv.pdf|"Power-law distributions in empirical data." A. Clauset, C. R. Shalizi and M. E. J. Newman. arXiv:0706.1062 (2007).]]
 
* [http://siamdl.aip.org/getpdf/servlet/GetPDFServlet?filetype=pdf&id=SIREAD000045000002000167000001 "The structure and function of complex networks." M. E. J. Newman, ''SIAM Review'' '''45''', 167-256 (2003)]
 
* [http://siamdl.aip.org/getpdf/servlet/GetPDFServlet?filetype=pdf&id=SIREAD000045000002000167000001 "The structure and function of complex networks." M. E. J. Newman, ''SIAM Review'' '''45''', 167-256 (2003)]
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Revision as of 04:53, 8 July 2009

Aaron Clauset [homepage] is an Omidyar fellow at the Santa Fe Institute (since 2006), and will be an assistant professor in computer science at CU Boulder starting Fall 2010. He is an alumnus of the CSSS 2003 (Santa Fe), and has been a lecturer at the Santa Fe summer school since 2007, and the Beijing summer school since 2008.

Aaron's research interests are broad, and currently include statistical patterns in complex systems, complex networks (structure, function, methods; technological, biological and social), statistical inference and machine learning, power-law distribtions (data, mechanisms); laws and contingencies in conflict (terrorism, war), human social dynamics; the Internet (structure, routing, security); adaptive and evolutionary computation; self-organization; robustness; innovation; and algorithmic game theory.

Much of Aaron's work focuses on understanding how to separate what is contingent from what is constrained or structured in a complex phenomenon. This general idea can be applied to complex social, biological, and technological systems. It has strong emphases on discovery and modeling, using both numeric and analytic tools, and it draws heavily on ideas and tools from computer science, statistics, machine learning, and statistical physics. Most recently, Aaron has been applying these ideas to understand the large-scale structure of complex networks, the mechanisms and constraints that give rise to morphological diversity among species, and the patterns of terrorists.