Center for Computing Research (CCR)

Center for Computing Research

Eric T. Phipps

Eric T. Phipps
Scalable Algorithms
Phone: 505/284-9268
Fax: 505/845-7442

Mailing address:
Sandia National Laboratories
P.O. Box 5800, MS 1318
Albuquerque, NM

Eric joined Sandia National Laboratories in September 2002 and is currently a principal member of the technical staff in the Scalable Algorithms Department.  Eric's research focuses on developing new capabilities for predictive simulation and analysis in Sandia’s large-scale parallel application codes using techniques based on automatic differentiation and template-based generic programming.  His work has recently emphasized developing tools and techniques relevant to emerging extreme-scale computer architectures.  He is the lead developer for several related software packages in Trilinos including the Sacado automatic differentiation, Stokhos embedded uncertainty quantification, and LOCA continuation/bifurcation analysis packages.



Eric earned a B.S. in Applied Mathematics from the University of Colorado in 1997 and a M.S. in Applied Mathematics from Cornell University in 2000.  In 2000 Eric was awared a NSF IGERT graduate fellowship and received his Ph.D. in Applied Mathematics from Cornell University in 2003.  Advised by Dr. John Guckenheimer, his dissertation work focused on developing methods for computing periodic orbits in hybrid dynamical system models of rigid-body mechanical systems using automatic differentiation and high-order Taylor series integration.



Selected Publications & Presentations

  • Kieweg, Sarah, Jaideep Ray, V. Gregory Weirs, Brian Carnes, Derek John Dinzl, Brian Andrew Freno, Micah Howard, Eric T. Phipps, William J. Rider, Thomas M. Smith, "Validation Assessment of Hypersonic Double-Cone Flow Simulations using Uncertainty Quantification, Sensitivity Analysis, and Validation Metrics ," Conference Paper, AIAA SciTechin, January 2019.
  • Phipps, Eric T., Tamara G. Kolda, "Software for Sparse Tensor Decomposition on Emerging Computing Architectures," Journal Article, SIAM Journal on Scientific Computing, Vol. 41, No. 3, pp. C269–C290, Accepted/Published June 2019.
  • Heroux, Michael A., Roscoe A. Bartlett, Victoria E. Howle, Robert J. Hoekstra, Jonathan J. Hu, Tamara G. Kolda, Richard B. Lehoucq, Kevin R. Long, Roger P. Pawlowski, Eric T. Phipps, Andrew G. Salinger, Heidi K. Thornquist, Ray S. Tuminaro, James M. Willenbring, Alan B. Williams, Kendall S. Stanley, "An overview of the Trilinos project," Journal Article, ACM Transactions on Mathematical Software, Vol. 31, No. 3, pp. 397–423, Accepted/Published September 2005.

Awards & Recognition

  • Phipps, Eric T., Invited Talk, Uncertainty Quantification Challenges in High-Performance Scientific Computing , SIAM Conference on Uncertainty Quantification, Mini-tutorial, April 3, 2014.
  • Forth, Shaun, Paul Hovland, Eric Phipps, Jean Utke, Andrea Walther, Journal/Book Editor, Editor for Recent Advances in Algorithmic Differentiation, 6th International Conference on Automatic Differentiation, July 1, 2012.
  • Phipps, Eric Todd, Invited Talk, Mathematical and Computational Tools for Predictive Simulation of Complex Coupled Systems Under Uncertainty, Workshop on Uncertainty Quantification for Multiscale Systems , July 20, 2010.