Los Alamos National Laboratory

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Kary Lynn Myers

Kary Myers

Email
Phone (505) 606-1455

Expertise

Statistics
Machine Learning
Analysis of spectra

Education

  • Ph.D., Statistics, Carnegie Mellon, 2006
    • Thesis: Developing Models to Reveal Brain Activation in Massive Neuroimaging Datasets
  • M.S., Machine Learning, Carnegie Mellon, 2002
    • Master's project: A Boosting Approach to Topic Spotting on Subdialogues
  • B.S. with University Honors, Statistics (Computer Science Minor), Carnegie Mellon, 1999
    • Honors thesis: Finding Galactic Clusters in Massive Astrophysical Datasets
 

LANL Positions

Scientist, CCS-6 Statistical Sciences Group, Los Alamos National Laboratory

 

Professional Societies

  • American Statistical Association
  • Sigma Xi Scientific Research Society
  • Phi Beta Kappa
  • Phi Kappa Phi
  • Association for Women in Mathematics
 

Awards

  • New Mexico Small Business Association Success Story, 2015
  • American Statistical Association Chapter Service Recognition Award, 2014
  • Los Alamos Achievement Award, 2007, 2011-2013, 2015
  • Early Career Scholarship, Isaac Newton Institute for Mathematical Sciences, 2011
  • Certificate of Appreciation, ASA Section on Physical and Engineering Sciences, 2011
  • AT&T Labs Fellowship, 1999-2005
  • Student Paper Competition Winner, Statistical Computing and Graphics Sections of the American Statistical Association, 2004
  • Student Scholarship, Spring Research Conference on Statistics in Industry and Technology, 2004 and 2005
  • Outstanding Reviewer Award, American College of Gastroenterology, 2004
  • Carnegie Scholars Program Fellowship, 1999-2003
  • Election to Phi Beta Kappa, Phi Kappa Phi, and Sigma Xi, 1999
  • Richard Schoenwald Phi Beta Kappa Undergraduate Research Prize, 1999
  • Lucent Technologies First Prize, Sigma Xi Undergraduate Research Competition, 1999
 

Publications

K. Myers, E. Lawrence, M. Fugate, C. McKay Bowen, L. Ticknor, J. Woodring, J. Wendelberger, and J. Ahrens. Partitioning a Large Simulation as It Runs. Technometrics, DOI 10.1080/00401706.2016.1158740 (2016)

B. Nouanesengsy, J. Woodring, J. Patchett, K. Myers, and J. Ahrens. ADR Visualization: A Generalized Framework for Ranking Large-Scale Scientific Data Using Analysis-Driven Refinement. In 4th IEEE Symposium on Large Data Analysis and Visualization (LDAV) (2014)

Y. Su, G. Agrawal, J. Woodring, K. Myers, J. Wendelberger, J. Ahrens. Effective and Efficient Data Sampling Using Bitmap Indices. Cluster Computing, 17(4), 1081-1100 (2014)

Y. Su, G. Agrawal, J. Woodring, K. Myers, J. Wendelberger, J. Ahrens. Taming Massive Distributed Datasets:  Data Sampling Using Bitmap Indices. 22nd International ACM Symposium on High Performance Parallel and Distributed Computing, 13-24 (2013)

T. Burr, M.S. Hamada, K. Myers, M. Skurikhin. Point-Source Detection Using Gamma-Ray Spectra in Radiation-Portal Monitoring. Journal of Quality Technology, 45(3), 285-296 (2013)

C. Longo, T. Burr, K. Myers. Change Detection Using Wavelets in Solution Monitoring Data for Nuclear Safeguards. Axioms (2), 271-285 (2013)

T. Burr, A. Bakel, S. Bryan, K. Budlong-Sylvester, J. Damico, S. Demuth, M. Ehinger, H. Garcia, J. Howell, S. Johnson, J. Krebs, K. Myers, C. Orton, M. Thomas.  Roles for Process Monitoring in Nuclear Safeguards at  Aqueous Reprocessing Plants. Journal of Nuclear Materials Management, 40(2), 42-53 (2012)

D. Hush, N. Pawley, K. Myers, R. Nemzek. A comparison of methods for estimating broadband noise in the frequency domain. In Asilomar Conference on Signals, Systems and Computers, IEEE Computer Society, 316-320 (2011)

D.I. Moody, S.P. Brumby, K.L. Myers, N.H. Pawley. Radio frequency (RF) transient classification using sparse representations over learned dictionaries. In SPIE Optical Engineering Applications, International Society for Optics and Photonics, doi:10.1117/12.898894 (2011)

D.I. Moody, S.P. Brumby, K.L. Myers, N.H. Pawley.  Classification of transient signals using sparse representations over adaptive dictionaries. In SPIE Defense, Security, and Sensing, International Society for Optics and Photonics, doi:10.1117/12.883341 (2011)

D.I. Moody, S.P. Brumby, K.L. Myers, N.H. Pawley.  Sparse classification of RF transients using chirplets and learned dictionaries. In Asilomar Conference on Signals, Systems and Computers, IEEE Computer Society, 1888-1892 (2011)

S. Brumby, K. Myers, and N. Pawley.  Capturing dynamics on multiple time scales: A multilevel fusion approach for cluttered electromagnetic data.  SPIE Defense, Security, and Sensing (2010)

N. Pawley, K. Myers, J. Galbraith, and S. Brumby.   Capturing dynamics on multiple time scales: A hybrid approach for cluttered electromagnetic data.  43rd Asilomar Conference on Signals, Systems, and Computers (2009)

T. Burr and K. Myers.   Effects of background suppression of gamma counts on signal estimation.  Applied Radiation and Isotopes67, 1729-1737 (2009)

T. Burr and K. Myers.   Signatures for several types of naturally occurring radioactive material.  Applied Radiation and Isotopes66, 1250-1261 (2008)

K.L. Myers, A.E. Brockwell, and W.F. Eddy.    State-space models for optical imaging. Statistics in Medicine, 26, 3862-3874 (2007)

T. Burr, J.R. Gattiker, K. Myers, and G. Tompkins.  Alarm criteria in radiation portal monitoring.  Applied Radiation and Isotopes,  65, 569-580 (2007)

K. Myers. The billion byte brain: Combining physiological data and gigabytes of images to improve maps of brain activity. 2004 Proceedings of the American Statistical Association.
—Winner, Statistical Computing and Graphics Sections Student Paper Competition

K. Myers, M. Kearns, S. Singh, and M.A. Walker.   A boosting approach to topic spotting on subdialogues. Proceedings of the Seventeenth International Conference on Machine Learning, 655-662 (2000)

 

Documents and Files