Publications – Chandrika Kamath

2020 – present

Chandrika Kamath, Classification of orbits in Poincaré maps using machine learning, International Journal of Data Science and Analytics, November 2022, https://doi.org/10.1007/s41060-022-00368-3
Chandrika Kamath, Intelligent sampling for surrogate modeling, hyperparameter optimization, and data analysis, Machine Learning with Applications, Volume 9, 15 September 2022, 100373, https://doi.org/10.1016/j.mlwa.2022.100373
Chandrika Kamath, “Intelligent Sampling for Surrogate Modeling, Hyperparameter Optimization, and Data Analysis, ” LLNL Technical Report LLNL-TR-829837, December 2021.
Chandrika Kamath, Juliette Franzman, and Ravi Ponmalai, “Data mining for faster, interpretable solutions to inverse problems: A case study using additive manufacturing,” Machine Learning with Applications, Volume 6, 15 December 2021, https://doi.org/10.1016/j.mlwa.2021.100122.
A. Buluc, T. G. Kolda, S. M. Wild, M. Anitescu, A. DeGennaro, J. Jakeman, C. Kamath, R. Kannan, M. E. Lopes, P.-G. Martinsson, K. Myers, J. Nelson, J. M. Restrepo, C. Seshadhri, D. Vrabie, B. Wohlberg, S. J. Wright, C. Yang, P. Zwart, “Randomized Algorithms for Scientific Computing (RASC)”, arXiv:2104.11079, April 2021.
Juliette Franzman, “Understanding the Effects of Tapering on Gaussian Process Regression,” student poster, Student and Post-Doc Poster Session, Conference on Data Analysis, February 25-27, 2020, Santa Fe, New Mexico.
Ravi Brannon Ponmalai, “Self-Organizing Maps and Their Applications to Data Analysis,” student poster, Student and Post-Doc Poster Session, Conference on Data Analysis, February 25-27, 2020, Santa Fe, New Mexico. Honorable Mention.
Chandrika Kamath, “Building High-Density, Additively-Manufactured Metal Parts – A Retrospective Look From a Data Analysis Perspective”, invited presentation, Conference on Data Analysis, February 25-27, 2020, Santa Fe, New Mexico.
C. Kamath, “Compressing unstructured mesh data from simulations using machine learning,” International Journal of Data Science and Analytics, Volume 9, pp 113-130, (2020) https://doi.org/10.1007/s41060-019-00180-6

2019

Chandrika Kamath,”Intelligent Exploration of Large-Scale Data: What Can We Learn in Two Passes?,” IEEE International Conference on Big Data, Los Angeles, CA, December 2019.
Chandrika Kamath, “Selecting parameters for image processing algorithms: A case study using retinal image segmentation,” Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, November 2019.
Ravi Ponmalai and Chandrika Kamath, “Self-Organizing Maps and Their Applications to Data Analysis,” LLNL Technical report LLNL-TR-791165, 20 September 2019.
Z. Li, T. Voisin, J. T. McKeown, J. Ye, T. Braun, C. Kamath, W. E. King, an Y. Morris Wang, “Tensile properties, strain rate sensitivity, and activation volume of additively manufactured 316L stainless steels,” International Journal of Plasticity, Volume 120, September 2019, Pages 395-410
Juliette Franzman and Chandrika Kamath, “Understanding the Effects of Tapering on Gaussian Process Regression,” LLNL-TR-787826. 19 August 2019.

2018

C. Kamath and Y.J. Fan, “Regression with Small Data Sets: A Case Study using Code Surrogates in Additive Manufacturing,” Knowledge and Information Systems Journal, Volume 57, Number 2, November 2018, pp. 475-493.
C. Kamath, Y.-J. Fan, “Compressing Unstructured Mesh Data Using Spline Fits, Compressed Sensing, and Regression Methods,” IEEE GlobalSIP, November 2018, Anaheim, CA, pp. 316-320.
Y. Wang, C. Kamath, T. Voisin, and Z. Li, “A processing diagram for high-density Ti-6Al-4V by selective laser melting,” Rapid Prototyping Journal, Vol. 24 Issue: 9, pp.1469-1478, 2018. https://doi.org/10.1108/RPJ-11-2017-0228

2017

C. Kamath, “Learning to compress unstructured mesh data from simulations,” IEEE/ACM/ASA International Conference on Data Science and Advanced Analytics (DSAA 2017), Tokyo, Japan, October 19-21, 2017.
C. Kamath, “Determination of Process Parameters for High-Density, Ti-6Al-4V Parts Using Additive Manufacturing,” Lawrence Livermore National Laboratory Technical report, LLNL-TR-736642, August 2017. Available as https://e-reports-ext.llnl.gov/pdf/889406.pdf

2016

W. A. Dawson, M. D. Schneider, and C. Kamath, “Blind Detection of Ultra-faint Streaks with a Maximum Likelihood Method,” AMOS Conference, September 2016.
Y. J. Fan and C. Kamath, “A comparison of compressed sensing and sparse recovery algorithms applied to simulation data,” Statistics, Optimization, and Information Computing, Vol. 4, Issue 3, September 2016, pp 194-213. DOI: http://dx.doi.org/10.19139/soic.v4i3.207
Ya Ju Fan and Chandrika Kamath, “Detecting ramp events in wind energy generation using affinity evaluation on weather data,”, Statistical Analysis and Data Mining, Volume 9, issue 3, June 2016, pages 155–173. DOI: http://dx.doi.org/10.1002/sam.11308
C.Kamath, “Data Mining and Statistical Inference in Selective Laser Melting”, International Journal of Advanced Manufacturing Technology, Volume 86, Issue 5, pp 1659–1677, September 2016. Appeared online 11 January, 2016. http://dx.doi.org/10.1007/s00170-015-8289-2
W. E. King, A. T. Anderson, R. M. Ferencz, N. E. Hodge, C. Kamath, S. A. Khairallah, A. Rubenchik, “Laser powder bed fusion additive manufacturing of metals; physics, computational, and materials challenges,” Applied Physics Reviews, 2, 041304 (2015); http://dx.doi.org/10.1063/1.4937809.
C. Kamath, “On the use of data mining to build high-density, additively-manufactured parts,” invited book chapter, Information Science for Materials Discovery and Design, T. Lookman, F. Alexander, and K. Rajan (eds.) in Springer Series in Materials Science, 225, pp 141-155, 2016.

2015

C. Kamath, “Data Mining and Analysis”, invited contribution, Princeton Companion to Applied Mathematics, Princeton University Press, pp 350-360, September 2015.
C. Kamath “Identifying process parameters for high-density 316L SS by combining simulations and experiments using data mining,” Solid Freeform Fabrication Symposium, Austin, TX, Aug. 10-12, 2015.
W. King, A. T. Anderson, R. M. Ferencz, N. E. Hodge, C. Kamath, S. A. Khairallah, “Overview of modelling and simulation of metal powder–bed fusion process at Lawrence Livermore National Laboratory,” Materials Science and Technology, Materials Science and Technology, Volume 31, Issue 8, June 2015, pp 957-968. Available at: http://dx.doi.org/10.1179/1743284714Y.0000000728
C. Kamath, “Data mining and statistical inference in selective laser melting,”, Invited presentation, International Symposium on Big Data and Predictive Computational Modeling, TU Munich, May 18-21, 2015.
J. Iverson, C. Kamath, and G. Karypis, Evaluation of connected-component labeling algorithms for distributed-memory systems, Parallel Computing, Vol. 44, May 2015, Pages 53-68. doi:10.1016/j.parco.2015.02.005
Y.J.Fan and C.Kamath, Practical considerations in applying compressed sensing to simulation data,” Data Compression Conference, Utah, April 2015.
Y.J.Fan and C.Kamath, Identifying and Exploiting Diurnal Motifs in Wind Generation Time Series Data, International Journal of Pattern Recognition and Artificial Intelligence , Vol 29, Number 2, 1550012-1 – 1550012-25, March 2015. Available at http://dx.doi.org/10.1142/S0218001415500123
Y. J.Fan and C.Kamath, On the Selection of Dimension Reduction Techniques for Scientific Applications,” in Real World Data Mining Application, Springer Annals of Information Systems,Volume 17, pp 91-122, 2015.

2014

C. Kamath and Y. J. Fan, “Incremental SVD for Insight into Wind Generation,” 13-th International Conference on Machine Learning and Applications (ICMLA), Detroit, Dec 3-6, 2014.
C. Kamath, “Mining Science Data: Challenges and Opportunities,” Computer Science and Engineering Colloquium, University of Nevada, Reno, October 2014.
Wayne E. King, Holly D. Barth, Victor M. Castillo, Gilbert F. Gallegos, John W. Gibbs, Douglas E. Hahn, Chandrika Kamath, and Alexander M. Rubenchik, “Observation of keyhole-mode laser melting in laser powder-bed fusion additive manufacturing,” Journal of Materials Processing Technology, 214 (2014), pp. 2915-2925 DOI: http://dx.doi.org/10.1016/j.jmatprotec.2014.06.005
Chandrika Kamath, Bassem El-dasher, Gilbert F. Gallegos, Wayne E. King, and Aaron Sisto, “Density of additively-manufactured, 316L SS parts using laser powder-bed fusion at powers up to 400 W,”. Int J Adv Manuf Technol. Volume 74, Issue 1 (2014), Page 65-78.
C. Kamath, “Data Mining in Materials Science,” invited presentation, Informatics in Materials Design and Discovery conference, Santa Fe, Feb 5-6, 2014.
C. Kamath, “The evolution of SDM, A premier data mining conference”, SIAM News, January 2014.

2013

A. Sisto and C. Kamath, “Ensemble Feature Selection in Scientific Data Analysis,” LLNL Technical Report, LLNL-TR-644160, September 2013.
C. Kamath and Y. J. Fan, “Data Mining in Materials Science and Engineering,” book chapter in Informatics for Materials Science and Engineering: Data-driven Discovery for Accelerated Experimentation and Application, K. Rajan (Ed.), pp 17-36, Elsevier, 2013.
W. E. King, H. Barth, V. Castillo, G. Gallegos, J. Gibbs, D. Hahn, and C.Kamath, “Observation of Keyhole mode laser melting in laser powder-bed fusion additive manufacturing,”International Solid Freeform Fabrication Symposium, Austin, August 2013.
Y. J. Fan and C. Kamath, Detecting changes in weather data streams for wind energy prediction,” SIAM Annual Meeting, San Diego, July 2013
Y. J. Fan and C. Kamath, “Determining number of motifs in wind generation time series data,” SIAM Annual Meeting, San Diego, July 2013.
C. Kamath, “Data analysis meets modeling and simulation,” presentation, Future Directions Panel on “Big Data Meets Big Models”, SIAM Conference on Computational Science and Engineering, Boston, February, 2013.

2012

C. Kamath and Y. J. Fan, “Finding motifs in wind generation time series data,” International Conference on Machine Learning and Applications, Boca Raton, December 12-15, 2012.
M. Ndoye and C. Kamath, “A block-based MC-SURE algorithms for denoising sensor data streams”, LLNL Technical Report LLNL-TR-603554, November 2012.
M. Ndoye and C. Kamath, “Extending MC-SURE to denoise sensor data streams,” Asilomar Conference on Signals, Systems, and Computers, Monterey, CA, November 4-7, 2012 .
J. Iverson, Y. J. Fan, G. Karypis, C. Kamath, “Exa-DM: Enabling Scientific Discovery in Exascale Simulations, ” poster and presentation at the DOE Exascale Research Conference, October 2012.
C. Kamath, “Dimension reduction for streaming data,” book chapter in Data Intensive Computing: Architectures, Algorithms, and Applications, Ian Gorton and Deb Gracio, editors, Cambridge University Press, 2012, pp 124-156.
C. Kamath and Y. J. Fan, “Using Data Mining to Enable Integration of Wind Resources on the Power Grid,” Statistical Analysis and Data Mining, Volume 5, Issue 5, October 2012, pp 410-427.
C. Kamath, “Final report: MINDES – Data Mining for Inverse Design,” Lawrence Livermore National Laboratory Technical report LLNL-TR-583076, September 2012.
C. Kamath, “Analysis of the formation enthalpy dataset,” Lawrence Livermore National Laboratory Technical report LLNL-TR-582974, September 2012.
C. Kamath, “Analysis of the band gap type dataset,” Lawrence Livermore National Laboratory Technical report LLNL-TR-577712, August 2012.
J. Iverson, C. Kamath, G. Karypis, “Fast and effective lossy compression algorithms for scientific datasets,” Euro-Par Conference, Rhodes Island, Greece, August 27-31, 2012.
Y. J. Fan and C. Kamath, “A Heuristic for the Local Region Covering Problem”, 21st International Symposium on Mathematical Programming, Berlin, Germany. August 19-24, 2012.
C. Kamath, “A data deluge in April,” SIAM News, July/August 2012.
C. Kamath, “Sensors, sensors, everywhere …”, 2012 Math Awareness Month article, April 2012
C. Kamath, J. Iverson, R. Kirk, and G. Karypis, “Detection of Coherent Structures in Extreme-Scale Simulations,” DOE Exascale Research Conference, Portland, Oregon, Apr 16- 18, 2012
Y. J. Fan and C. Kamath, “A comparison of dimensionality reduction techniques in scientific applications,” SIAM Conference on Uncertainty Quantification, Raleigh, North Carolina, April 2-4, 2012
C. Kamath, “Scientific data mining techniques for extracting information from simulations,” SIAM Conference on Uncertainty Quantification, Raleigh, North Carolina, April 2-4, 2012
C. Kamath, “On the role of data mining techniques in uncertainty quantification,” International Journal of Uncertainty Quantification, Volume2, Number 1, pp 73-94, 2012.
J. Manobianco, E. J. Natenberg, K. Waight, G. Van Knowe, J. Zack, D. Hanley, C. Kamath, “Limited area model-based data impact studies to improve short-range wind power forecasting,” 16th Symposium on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface (IOAS-AOLS), AMS Annual Meeting, New Orleans, LA, January 2012.

2011

Y. J. Fan and C. Kamath.“ Intrinsic Dimensionality Using Non-linear Dimension Reduction Techniques”. Institute for Operations Research and Management Sciences Annual Meeting, Charlotte, NC, November 13-16, 2011.
C. Kamath, “WindSENSE Project Summary: FY2009-2011,” LLNL Technical Report, LLNL-TR-501376, September 2011.
J. Zack, E. J. Natenberg, G. V. Knowe, K. Waight, J. Manobianco, D. Hanley, C. Kamath, Observing System Simulation Experiments (OSSEs) for the mid-Columbia Basin,” LLNL Technical Report LLNL-TR-499162, September 2011.
J. Zack, E. J. Natenberg, G. V. Knowe, J. Manobianco, K. Waight, D. Hanley, C. Kamath, “Use of data denial experiments to evaluate ESA forecast sensitivity patterns,” LLNL technical Report, LLNL-TR-499166, September 2011.
M. Ndoye and C. Kamath, “Pattern analysis in wind power time – early results,” poster, Conference on Intelligent Data Understanding, Mountain View, October 2011.
C. Kamath, “On the role of data mining techniques in uncertainty quantification”, Invited plenary talk at the USA/South America Symposium on Stochastic Modeling and Uncertainty Quantification, Rio de Janeiro, Brazil, August 1-5, 2011.
C. Kamath and O. Hurricane, “Robust extraction of statistics from images of material fragmentation,” International Journal of Image and Graphics, Volume 11, Issue 3, pp 377-401, July 2011.
C. Kamath, “Subspace tracking for dimension reduction in streaming data,” SIAM Conference on Computational Science and Engineering, Reno, February 28-March 4, 2011.
C. Kamath, “Associating Weather Conditions with Ramp Events in Wind Power Generation,” 2011 IEEE PES Power Systems Conference & Exposition, Phoenix, Arizona, March 20 – 23, 2011.
E. J. Natenberg, S. Young, G. Van Knowe, J. Zack, J. Manobianco, C. Kamath, “Observational Targeting Using Ensemble Sensitivity Analysis to Improve Short-Term Wind Power Forecasting in the Mid-Columbia Basin,” Second Conference on Weather, Climate, and the New Energy Economy, AMS Annual Meeting, Seattle, January 23-27, 2011.

2010

J. Zack, E. J. Natenberg, S. Young, G. V. Knowe, K. Waight, J. Manobianco, and C. Kamath, “Application of ensemble sensitivity analysis to observation targeting for short term wind speed forecasting in the Tehachapi region winter season,” LLNL Technical Report LLNL-TR-460956, October 2010.
J. Zack, E. J. Natenberg, S. Young, G. V. Knowe, K. Waight,J. Manobianco, and C. Kamath, “Application of ensemble sensitivity analysis to observation targeting for short term wind speed forecasting in the Washington-Oregon region,”LLNL Technical Report LLNL-TR-458086, October 2010.
E. J. Natenberg, J. Zack,S. Young, J. Manobianco, and C. Kamath, ” A new approach using targeted observations to improve short term wind power forecasts, ” AWEA WindPower 2010 Conference and Exhibition, Dallas, TX, May 2010.
C. Kamath, Y. Xiao, and Z. Lin. “Analysis of structures and event size statistics in plasma turbulence: Preliminary results”, International Sherwood Fusion Theory Conference, Seattle, WA, April 2010.
C. Kamath, “Understanding wind ramp events through analysis of historical data,” IEEE PES Transmission and Distribution Conference, New Orleans, April 2010.
J. Zack, E. J. Natenberg, S. Young, J. Manobianco, and C. Kamath, “”Application of ensemble sensitivity analysis to observational targeting for short term wind speed forecasting,”LLNL Technical Report LLNL-TR-424442, February, 2010.
C. Kamath, “Using simple statistical analysis of historical data to understand wind ramp events,” LLNL Technical report LLNL-TR-423242, February 2010.
E. J. Natenberg, J. Zack, S. Young, R. Torn, J. Manobianco, and C. Kamath, “”Application of ensemble sensitivity analysis to observational targeting for wind power forecasting,” 14th Symposium on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface (IOAS-AOLS), AMS Annual Meeting, Atlanta, January, 2010.
C. Kamath, N. Wale, G. Karypis, G. Pandey, V. Kumar, K. Rajan, N. F. Samatova, P. Breimyer, G. Kora, C. Pan, S.Yoginath, “Scientific Data Analysis”, book chapter in “Scientific Data Management: Challenges, Technology, and Deployment”, A. Shoshani and D. Rotem, editors, Chapman and Hall/CRC Press, pp 281-324, 2010.

2009

C. Kamath, A. Gezahegne, and P. L Miller, “Identification of coherent structures in three-dimensional simulations of a fluid-mix problem, ” International Journal of Image and Graphics, Volume 9, No. 3, pp. 389-410, July 2009.

2008

C. Kamath, “Application-driven data analysis”, Editorial, Statistical Analysis and Data Mining, Vol 1, Issue 5, 2008.
A. Gezahegne and C. Kamath, “Tracking non-rigid structures in computer simulations,” IEEE International Conference on Image Processing, San Diego, October 2008, pp. 1548-1551.
W. P. Kegelmeyer, R. Calderbank, T. Critchlow, L. Jameson, C. Kamath, J. Meza, N. Samatova, and A. Wilson, “Mathematics for Analysis of Petascale Data: Report on a Department of Energy Workshop”, June 2008.
C. Kamath, “Sapphire: Experiences in Scientific Data Mining,”, SciDAC 2008, Journal of Physics Conference Series 125, 012094, July 2008.
A. Goodman, C. Kamath, V. Kumar, “Data analysis in the 21st century,” Editorial, Statistical Analysis and Data Mining, Vol. 1, Issue 1, Feb 2008, pp 1-3.

2007

C. Kamath, A. Gezahegne, and P.L. Miller, “Analysis of Rayleigh-Taylor Instability: Statistics on Rising Bubbles and Falling Spikes”, LLNL Technical Report UCRL-TR-236111-REV-1, December 2007.
C. Kamath and O. A. Hurricane, “Analysis of Images from Experiments Investigating Fragmentation of Materials”, LLNL Technical Report, UCRL-TR-234578, September 13, 2007.
C. Kamath and P. L. Miller, “Image Analysis for Validation of Simulations of a Fluid Mix Problem,” IEEE International Conference on Image Processing, Volume III, pages 525-528, San Antonio, September 2007.
A. Bagherjeiran, N. S. Love, C. Kamath, “Estimating Missing Features to Improve Multimedia Retrieval,” IEEE International Conference on Image Processing, Volume II, pages 233-236, San Antonio, September 2007.
C. Kamath, A. Gezahegne, and P. L. Miller, “Sapphire Analysis of DNS of Rayleigh-Taylor Instability”, Presentation, Fall Creek Falls Meeting on Challenges in Modeling and Simulation, Nashville, September 24-26, 2007.
N. S. Love and C. Kamath, “Image Analysis for the Identification of Coherent Structures in Plasma,” Applications of Digital Image Processing, XXX, SPIE Conference 6696, San Diego, August 2007.
C. Kamath, “Understanding the Science in Data: Challenges at the Petascale,” Presentation, DOE ASCR Applied Mathematics Research PI meeting, Livermore, May 2007.
C. Kamath, “Scientific Data Mining- Challenges at the Petascale,” Presentation, SFBay ACM Data Mining SIG Meeting, March 14, 2007.
C. Kamath, “Mining Science Data,” Presentation, 4-th Annual FMS/IMT Colloquium and Workshop on Large Data Issues in HPC, Marina del Rey, March 7, 2007.
C. Kamath, “Mining science data,” Presentation, SIAM Conference on Computational Science and Engineering, Costa Mesa, February 2007.

2006

P. L. Miller, A. G. Gezahegne, A. W. Cook, W. H. Cabot, C. Kamath, “Bubble counts for Rayleigh-Taylor Instability Using Image Analysis, International workshop on the Physics of Compressible Turbulent Mixing, July 17-21, 2006, Paris, France.
C. Kamath, “Mining science data,” SciDAC 2006, Scientific Discovery through Advanced Computing, in Journal of Physics Conference Series, Volume 46, 2006, pp. 500-504.
C. Kamath, A. Gezahegne, and P.L. Miller, “Analysis of Rayleigh-Taylor Instability, Part I: Bubble and Spike Count”, LLNL Technical report, UCRL-TR_223676, August 2006.
A. Bagherjeiran and C. Kamath, “Graph-based Methods for Orbit Classification,” Sixth SIAM International Conference on Data Mining, Bethesda, April 2006. UCRL-CONF-215802
N.S. Love and C. Kamath, “An Empirical Study of Block Matching Techniques for Detection of Moving Objects,” LLNL Technical Report UCRL-TR-218038, April 2006.

2005

A. Bagherjeiran and C. Kamath, “Graph-based Techniques for Orbit Classification: Early Results,” LLNL Technical Report UCRL-TR-215690, September 2005.
Samson S.-C. Cheung and C. Kamath, “Robust background subtraction with foreground validation for urban traffic video,” Eurasip Journal on applied signal processing. Volume 14, pp 2330-2340, 2005.
Cantú-Paz, E. and C. Kamath, An empirical comparison of combinations of evolutionary algorithms and neural networks for classification problems. IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics, pages 915-927, 2005.
A. Bagherjeiran, C. Cantu-Paz, C. Kamath, “Design and Implementation of an Anomaly Detector”, Technical Report, Lawrence Livermore National Laboratory, UCRL-TR-213599, July 2005.
C. Kamath and T. Nguyen, “Feature Extraction from Simulations and Experiments: Preliminary Results Using a Fluid Mix Problem,” Technical report, Lawrence Livermore National Laboratory, UCRL-TR-208853, January 2005.
S. Newsam and C. Kamath, “Comparing shape and texture features for pattern recognition in simulation data,” Image Processing: Algorithms and Systems IV, SPIE Electronic Imaging, January 2005.
C. Kamath, A. Gezahegne, S. Newsam, G.M. Roberts, “Salient Points for Tracking Moving Objects in Video,” Proceedings, Image and Video Communications and Processing, pp 442-453, SPIE Volume 5685, Electronic Imaging, San Jose, January 2005.

2004

C. Kamath, “Statistics and Practical Applications of Data Mining: Highlights from SDM04,” SIAM News, Volume 37, Number 6, July/August 2004.
A. Lazarevic, Kanapady, R. and Kamath, C., “Effective Localized Regression for Damage Detection in Large Complex Mechanical Structures,” Proceedings, ACM International Conference on Knowledge Discovery and Data Mining, pp 450-459, August 22-25, 2004, Seattle, WA.
Cantu-Paz, E., Newsam, S., Kamath, C., “Feature Selection in Scientific Applications,” Proceedings, ACM International Conference on Knowledge Discovery and Data Mining, pp 788-793, August 22-25, 2004, Seattle, WA.
Newsam, S. and C. Kamath, “Retrieval using texture features in high resolution multi-spectral satellite imagery,” Data Mining and Knowledge Discovery: Theory, Tools, and Technology, VI, SPIE Volume 5433, pp. 21-32, SPIE Defense and Security, Orlando, April 2004.
Cantu-Paz, E., Cheung, S-C., and Kamath, C., “Retrieval of Similar Objects in Simulation Data Using Machine Learning Techniques,” Image Processing: Algorithms and Systems III, SPIE Volume 5298, pp 251-258. SPIE Electronic Imaging, San Jose, January 2004.
Cheung, S.-C., and C. Kamath, “Robust techniques for background subtraction in urban traffic video,” Video Communications and Image Processing, Volume 5308, pp 881-892, SPIE Electronic Imaging, San Jose, January 2004.
Weeratunga S. and C. Kamath, “An investigation of implicit active contours for scientific image segmentation,” Video Communications and Image Processing, SPIE Volume 5308, pp. 210-221, SPIE Electronic Imaging, San Jose, January 2004.

2003

Lazarevic, A., R. Kanapady, C. Kamath, V. Kumar, and K. Tamma, “Localized Prediction of Continuous Target Variables Using Hierarchical Clustering,” Proceedings, IEEE International Conference on Data Mining, pp. 139-146, Melbourne, Florida, Nov. 2003.
Moelich, M., “Autonomous Motion Segmentation of Multiple Objects in Low Resolution Video Using Variational Level Sets,” LLNL Technical report, UCRL-TR-201054., November 19, 2003.
Gyaourova, A., C. Kamath, and S.-C. Cheung, “Block matching for object tracking,” LLNL Technical report, October 2003. UCRL-TR-200271.
Lazarevic, A., Kanapady, R., Kamath, C., Tamma K., Kumar, V., “Damage Detection Employing Novel Data Mining Techniques,” book chapter, New Generation of Data Mining Applications, IEEE Press, August 2003.
Kamath, C., E. Cantu-Paz, S.-C. Cheung, I. K. Fodor, and N. Tang, “Experiences in mining data from computer simulations,” book chapter, New Generation of Data Mining Applications, IEEE Press, August 2003.
Cheung S.-C. and C. Kamath, “Initial experiences with retrieving similar objects in simulation data,” Proceedings, Sixth Workshop on Mining Scientific and Engineering Datasets, in conjunction with the Third SIAM conference on Data Mining, May 3, 2003, pp 11-18.
Fodor, I.K. and C. Kamath, “Using independent component analysis to separate signals in climate data,” Proceedings, Independent component analysis, Wavelets, and Neural Networks, SPIE Aerosense, Orlando, April 2003.
I. K. Fodor and Kamath, C., “Efficient segmentation of spatio-temporal data from simulations,” Proceedings, Image and Video Communications and Processing, SPIE Electronic Imaging, San Jose, January 2003.
Sengupta, S. K., C. Kamath, D. Poland, J. Futterman, “Detecting human settlements in Satellite Images,” Proceedings, Optical Engineering at the Lawrence Livermore National Laboratory, SPIE Photonics West, Lasers and Applications in Science and Engineering, San Jose, January 2003.
Kamath, C., S. Sengupta, D. Poland, and J. Futterman, “On the use of machine vision techniques to detect human settlements in satellite images, Proceedings, Image Processing: Algorithms and Systems II, SPIE Electronic Imaging, San Jose, January 2003.
Weeratunga S.K., and C. Kamath, “A comparison of PDE-based non-linear anisotropic diffusion techniques for image denoising,” Proceedings, Image Processing: Algorithms and Systems II, SPIE Electronic Imaging, San Jose, January 2003.

2002

Gyaourova, A., C. Kamath, and I. K. Fodor, “Undecimated Wavelet Transforms for Image De-Noising,” LLNL Technical report, UCRL-ID-150931.
Kirshner, S., I. V. Cadez, P. Smyth, C. Kamath, and E. Cantu-Paz, “Probabilistic Model-based Detection of Bent-double radio galaxies,” poster presentation at International Conference on Pattern Recognition, August 2002.
Kamath, C., E. Cantu-Paz, I.K. Fodor, N. Tang, “Classification of bent-double galaxies in the FIRST survey,” IEEE Computing in Science and Engineering, July/August 2002, pp 52-60,.
Kamath, C., “Mining the Sky: Data Analysis Meets Astronomy,” SIAM News, April 2002.
Cantu-Paz, E., and C. Kamath, “Evolving neural networks for the classification of galaxies,” Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2002, pp. 1019-1026, Morgan Kaufmann Publishers, San Francisco, 2002, UCRL-JC-147020. Tied for the best paper award in the Real World Applications Category.
Fodor, I. K., and C. Kamath, “On the use of independent component analysis to separate meaningful sources in global temperature series,” Joint Statistical Meetings, August 2002.
Kamath, C., “Mining Science and Engineering Data: An Overview,” book chapter, Handbook of Data Mining, Nong Ye (ed.), pp 549-572, Lawrence Erlbaum Associates. New Jersey, 2003.
Kamath, C., and E. Cantu-Paz, “Classification of bent-double galaxies: Experiences with ensembles of decision trees,” Proceedings, Fifth Workshop on Mining Scientific Datasets, pp. 43-50, Held in conjunction with the Second SIAM International Conference on Data Mining, April 13, 2002.
Cantu-Paz E., and C. Kamath, “Evolving neural networks to identify Bent-Double Galaxies in the FIRST Survey,” Neural Networks, Volume 16, No. 3-4, pp. 507-517, 2003.
Kamath, C., “Workshop report: The Fourth Workshop on Mining Scientific Datasets,” SigKDD Newsletter, Volume 3, Issue 2, pp. 68-69, January 2002.
Weeratunga S.K. and C. Kamath, “PDE-based non-linear diffusion techniques for denoising scientific/industrial images: An empirical study,” Proceedings, Image Processing: Algorithms and Systems, SPIE Electronic Imaging, pp. 279-290, San Jose, January 2002.
Kamath, C., E., Cantú-Paz, and D. Littau, “Approximate Splitting for Ensembles of Trees using Histograms,” Proceedings, Second SIAM International Conference on Data Mining, pp. 370-383, April 2002.

2001

Kanapady, R., S. K. Bathina, K.K. Tamma, C. Kamath, and V. Kumar, “Determination of an initial mesh density for finite element computations via data mining,” Proceedings of the Fourth Workshop on Mining Scientific Datasets, pp. 64-70, KDD 2001, August 2001. Also available as Lawrence Livermore National Laboratory technical report, UCRL-JC-144765.
Sandhu, S.S., R. Kanapady, K.K. Tamma, C. Kamath, and V. Kumar, “Damage Prediction and estimation in structural mechanics based on data mining,” Proceedings of the Fourth Workshop on Mining Scientific Datasets, KDD 2001, pp 56-63, August 2001. Also available as Lawrence Livermore National Laboratory technical report, UCRL-JC-144764.
C. Kamath, Proceedings of the Fourth Workshop on Mining Scientific Datasets (ed.), August 2001, KDD2001. Also available as Lawrence Livermore National Laboratory technical report, UCRL-ID-144763.
Fodor, I. K., and C. Kamath, “Dimension reduction techniques and the Classification of Bent Double Galaxies,” Computational Statistics and Data Analysis journal, Volume 41, pp. 91-122, 2002.
Fodor, I. K., and C. Kamath, “Denoising through Wavelet Shrinkage: An Empirical Study,” SPIE Journal on Electronic Imaging, Vol. 12, No. 1, pp. 151-160, January 2003.
R. Grossman, C. Kamath, W. Kegelmeyer, V. Kumar, and R. Namburu eds., Data Mining for Scientific and Engineering Applications, Kluwer, September 2001.
E. Cantú-Paz, and C. Kamath, “Inducing Oblique Decision Trees with Evolutionary Algorithms,” IEEE Transactions on Evolutionary Computing, Volume 7, No. 1, pp. 54-68, February 2003.
Kamath, C., E. Cantu-Paz, I. K. Fodor, N. Tang, “Using data mining to find bent-double galaxies in the FIRST survey,” Proceedings, Astronomical Data Analysis, at the SPIE Annual Meeting, San Diego, July-August 2001.
Kamath, C., and E. Cantu-Paz, Creating ensembles of decision trees through sampling, Proceedings, 33rd Symposium on the Interface of Computing Science and Statistics, Costa Mesa, CA, June 2001.
Fodor, I. K., and C. Kamath, “A comparison of de-noising techniques for FIRST images,” Proceedings, Third workshop on Mining Scientific Datasets, held in conjunction with the First SIAM Int. Conf. on Data Mining, Chicago, April 2001, pp. 13-20.
Fodor, I. K., and C. Kamath, “On Denoising Images Using Wavelet-based Statistical Techniques,” Lawrence Livermore National Laboratory technical report, UCRL JC-142357.
Kamath, C., “The Role of Parallel and Distributed Processing in Data Mining,” Spring 2001 newsletter of the IEEE Technical Committee on Distributed Processing, pp. 10-15. Also available as Lawrence Livermore National Laboratory technical report, UCRL-JC-142468.
Cantu-Paz, E., and C. Kamath, “On the Use of Evolutionary Algorithms in Data Mining,” book chapter in Data Mining: A Heuristic Approach, Eds. H. Abbass, R. Sarker, and C. Newton, pp. 48-71, 2001.
C. Kamath, “On Mining Scientific Datasets,” book chapter in Data Mining for Scientific and Engineering Applications, eds. R. Grossman, C. Kamath, P. Kegelmeyer, V. Kumar, and R. Namburu, Kluwer, pp. 1-22, 2001.
Kamath, C, E., Cantu-Paz, I. K. Fodor, N. Tang, “Searching for Bent-Double Galaxies in the FIRST Survey,” book chapter in Data Mining for Scientific and Engineering Applications, eds. R. Grossman, C. Kamath, W. Kegelmeyer, V. Kumar, and R. Namburu, Kluwer, pp. 95-114, 2001.
Fodor, Imola, and Chandrika Kamath, “The Role of Multiresolution in Mining Massive Image Datasets,” in Multiscale and Multiresolution Methods, Lecture Notes in Computational Science and Engineering, T. J. Barth, T. Chan, and R. Haimes, (Eds.), Volume 20, Springer-Verlag, pp. 307-318, 2001.

2000

Kamath, C., and Ann Parker, “Mining Data for Gems of Information,” Research Highlight, Science and Technology Review, September 2000, pages 20-22. UCRL-52000-00-9.
Kamath, Chandrika, and Erick Cantú-Paz, “On the design of a parallel object-oriented data mining toolkit, “Workshop on Distributed and Parallel Knowledge Discovery, at the Knowledge Discovery and Data Mining Conf., Boston, August 20-23, 2000.
Cantú-Paz, E., and Kamath, C. “Combining evolutionary algorithms with oblique decision trees to detect bent double galaxies,” in Conf. Proc. Int. Symposium on Optical Science and Technology, SPIE Annual Meeting, Vol. 4120, pp. 63-71, San Diego, July 30-August 4, 2000.
Kamath, Chandrika, Chuck Baldwin, Imola Fodor, and Nu Ai Tang, “On the design and implementation of a parallel, object-oriented, image processing toolkit,” Proc. Int. Symp. on Optical Science & Technology, SPIE Annual Meeting, San Diego, July 30-August 4, 2000.
Kargupta, Hillol, Chandrika Kamath, and Philip Chan, Distributed and Parallel Data Mining: Emergence, Growth, and Future Directions, epilogue in Advances in Distributed and Parallel Knowledge Discovery, AAAI Press/MIT Press, pages 409-417, 2000.
Cantú-Paz, Erick, and Chandrika Kamath, “Using Evolutionary Algorithms to Induce Oblique Decision Trees,” Genetic and Evolutionary Computation Conf. (GECCO) 2000, Las Vegas, NV, July 8-12, 2000.
Fodor, Imola, Erick Cantú-Paz, Chandrika Kamath, and Nu Ai Tang, “Finding Bent-Double Radio Galaxies: A Case Study in Data Mining, “Interface: Computer Science and Statistics, Volume 33, New Orleans, LA, April 2000.

1999

Kamath, Chandrika, and Ron Musick, “Scalable Data Mining through Fine-Grained parallelism: The Present and the Future,” in Advances in Distributed and Parallel Knowledge Discovery H. Kargupta and P. Chan, Eds., (AAAI Press/MIT Press), pages 29-77, 2000.
Kamath, Chandrika, and Ron Musick, “Data Mining for Large, Complex Data Sets,” a position paper in Mining and Managing Massive Data Sets ‘98, La Jolla, CA, February 5-6, 1998. Also available as Lawrence Livermore National Laboratory technical report. UCRL-JC-129727.
Kamath, Chandrika, SAPPHIRE: Large-Scale Data Mining and Pattern Recognition, Lawrence Livermore National Laboratory technical brochure UCRL-TB-132076, January 1999.

Pre-1999

Chandrika Kamath Roy Ho, Dwight P. Manley, “DXML: a high-performance scientific subroutine library,” Digital Technical Journal Volume 6, Issue 3, Summer 1994, pp. 44–56.
Chandrika Kamath and Ahmed Sameh, “AProjection Method for Solving Nonsymmetric Linear Systems on Multiprocessors,” Parallel Computing , Vol. 9, pp. 291-312, 1989.
C. Kamath, A. H. Sameh, G. C. Yang and D. J. Kuck, “Structural Computations on the Cedar System,” Computers and Structures, Vol. 20, No. 1-3, pp. 47-54, 1985.
C. Kamath and A. Sameh, “The Preconditioned Conjugate Gradient Algorithm on a Multiprocessor,” Fifth IMACS International Symp. on Computer Methods for Partial Differential Equations, pp. 210-217, June, 1984.
Chandrika, Kamath and V.C. Bhavsar, ‘Implementation and Performance Prediction of Some Parallel Algorithms on PLEXUS Microcomputer Network’ Microprocessing and Microprogramming, Vol. 10, pp. 25-31, 1982.