Statistical Methods for Very Large Datasets Conference 2011

Baltimore, Maryland
Wednesday, June 01, 2011

Statistical Methods for Very Large Datasets Conference 2011
Wednesday, June 01, 2011 8:00 AM -
Friday, June 03, 2011 5:30 PM (Eastern Time)

InterContinental Harbor Court Hotel
800-824-0076
550 Light Street
Baltimore, Maryland 21202

Map and Directions

Registrant check-in will take place at 7:00 - 11:00am on June 1 and 8:00 - 10:00am on June 2 and 3.  This will be directly outside the Whitehall Ballroom at the Hotel.

Welcome!

The Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health invites you to a 3-day conference on Very Large Data Sets. The conference is scheduled from June 1-3, 2011 and will be hosted in beautiful, downtown Baltimore, Maryland, USA at the InterContinental Harbor Court Hotel.

The conference has a one-track session for invited presentations and a high profile session for contributed poster presentations.  A panel discussion will attempt to define what large data sets are, anticipate new challenges, and identify possible solutions.  

Conference Overview

There is an acute and increasing need to adapt standard statistical methods and to develop new approaches for the analysis of very large data sets.  A data set is very large if it raises difficult or insurmountable computational problems for standard data analysis using available computing systems. The continuous increase in size and complexity of data sets is due in part to increased computational and storage capabilities, new measurement technologies and study designs, and an increasing number of study “units”. 

Very large data sets are becoming increasingly available in:

  • Epidemiology (Medicare/Medicaid, air pollution studies)
  • Genome Sciences (microarrays, sequencing)
  • Medicine (imaging, sleep studies)
  • Computer Science (search engines)
  • Astronomy (universe maps). 

The goals of this conference are:

  • to bring together researchers who work on very large and complex data sets
  • to explore and define common statistical and  computational methods across a wide spectrum of applications
  • to build awareness of this important area of research.

 

Contact Information

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