• 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.


  • 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.


  • 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