Kimberly Kristine Keeton is an American computer scientist specializing in databases and computer data storage. She worked at HP Labs as a Distinguished Technologist and is currently employed by Google as Principal Engineer, and was one of the designers of the Express Query metadata database used by Hewlett-Packard as part of their StoreAll large-scale data storage systems.[1]

Education

Keeton did her undergraduate studies at Carnegie Mellon University, with a double major in computer engineering and in engineering and public policy.[1] She completed her Ph.D. in 1999 at the University of California, Berkeley. Her dissertation, Computer Architecture Support for Database Applications, was supervised by David Patterson.[2]

Recognition

A paper written by Keeton in 2004 with four other researchers on the automated design of disaster-resistant enterprise storage systems won the Usenix FAST Test of Time Award in 2018.[3] She also won the 2018 SIGMOD best paper award for her work with other collaborators on "range filtering" data structures that combine the memory-efficient filtering abilities of bloom filters with the ability of range query data structures to find data with a range of key values rather than with a single exactly matching key.[4]

Keeton was elected as an ACM Fellow in 2018 for "contributions to improving the dependability, manageability, and usability of storage and novel memory".[5] She became an IEEE Fellow in 2021.[6]

References

  1. 1 2 "Kimberly Keeton", FAST17 Speaker Biography, Usenix, retrieved 2018-12-06
  2. ↑ Kimberly Keeton at the Mathematics Genealogy Project
  3. ↑ Hopkins, Curt (March 14, 2018), The work of two more Labs researchers stands the test of time, Hewlett Packard Enterprise
  4. ↑ Hopkins, Curt (June 13, 2018), Labs researcher honoured with SIGMOD 2018 Best Paper award, Hewlett Packard Enterprise
  5. ↑ 2018 ACM Fellows Honored for Pivotal Achievements that Underpin the Digital Age, Association for Computing Machinery, December 5, 2018
  6. ↑ IEEE Fellows directory, IEEE, retrieved 2021-05-30
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