Earl Christopher Lawrence

Education

• Ph.D., Statistics
• University of Michigan
• 2005

• B.S., Statistics
• University of Michigan
• 2000

Positions

• 2007 - Present | Scientist

Awards

• Los Alamos Distinguished Performance Award as member of the SHIELDS team, 2018
• R&D 100 Award as member of the SHIELDS team, 2017
• Los Alamos Star Award for Door Sleuthing, 2013
• Los Alamos Achievement Award for establishing and hosting the Conference on Data Analysis, 2012
• Los Alamos Achievement Award for CCS-6 Search Committee, 2011, 2012
• Defense Programs Aware of Excellence for Significant Contributions to the Stockpile Stewardship Program, 2007
• Los Alamos Achievement Award for QMU Production Team, 2007

Publications

• S. Myren, E. Herrera, A. Shoats, E. Lawrence, E. Casleton, D. J. Luscher, and S. J. Fensin, “Input estimation and dimension reduction for material models,” Model Validation and Uncertainty Quantifi- cation, Volume 3, IMAC XXXVII, 2019.
• F. Sun, R. B. Gramacy, B. Haaland, E. Lawrence, and A. Walker, “Emulating satellite drag from large simulation experiments,” Journal of Uncertainty Quantification, 2019.
• A. Biswas, C. M. Biwer, D. J. Walters, J. Ahrens, D. C. Francom, E. Lawrence, R. L. Sandberg, D. A. Fredenburg, and C. Bolme, “An interactive exploration tool for high-dimensional datasets: A shock physics case study,” Computing in Science & Engineering, 2018.
• A. Biswas, K. R. Moran, E. Lawrence, and J. Ahrens, “Visualization of uncertainty for computationally intensive simulations using high fidelity emulators,” IEEE Vis (Scivis Short papers), 2018.
• V. Jordanova, G. L. Delzanno, M. Henderson, H. Godinez, C. Jeffrey, E. Lawrence, S. Morley, J. D. Moulton, L. Vernon, J. Woodroofe, T. Brito, C. Meierbachtol, D. Svyatsky, Y. Yu, G. Toth, D. Welling, Y. Chen, J. Haiducek, S. Markidis, J. Albert, J. Birn, M. Denton, and R. Horne, “Specification of the near-earth space environment with SHIELDS,” Journal of Atmospheric and Solar-Terrestrial Physics, 2018.
• D. J. Walters, A. Biswas, E. Lawrence, D. C. Francom, D. J. Luscher, D. A. Fredenburg, K. R. Moran, C. M. Sweeney, R. L. Sandberg, J. Ahrens, and C. D. Bolme, “Bayesian calibration of strength parameters using hydrocode simulations of symmetric impact shock experiments of al-5083,” Journal of Applied Physics, 2018.
• R. Zoh, A. Wilson, S. Vander Wiel, and E. Lawrence, “The negative log-gamma prior distribution for Bayesian assessment of system reliability,” Journal of Risk and Reliability, 2018.
• H. Director, J. R. Gattiker, E. Lawrence, and S. Vander Wiel, “Efficient sampling on the simplex with a self-adjusting logit transform proposal,” Journal of Statistical Computation and Simulation, 2017.
• E. Lawrence, K. Heitmann, J. Kwan, A. Upadhye, D. Bingham, S. Habib, D. Higdon, A. Pope, H. Finkel, and N. Frontiere, “The Mira-Titan Universe II: Power spectrum emulation,” The Astrophysical Journal, 2017.
• E. Lawrence, S. Vander Wiel, C. J. Law, S. Burke-Spolaor, and G. C. Bower, “The non-homogeneous Poisson process for fast radio burst rates,” The Astronomical Journal, 2017.
• M. Garcia, T. Catanach, S. Vander Wiel, R. Bent, and E. Lawrence, “Line outage localization using phasor measurement data in transient state,” IEEE Transactions on Power Systems, 2016.
• H. Godinez, Y. Yu, E. Lawrence, M. Henderson, B. Larsen, and V. Jordanova, “Ring current estimation with RAM-SCB using data assimilation and Van Allen Probe flux data,” Geophysical Research Letters, 2016.
• K. Heitmann, D. Bingham, E. Lawrence, S. Bergner, S. Habib, D. Higdon, A. Pope, R. Biswas, H. Finkel, N. Frontiere, and S. Bhattacharya, “The Mira-Titan Universe: Precision predictions for dark energy surveys,” The Astrophysical Journal, 2016.
• K. Myers, E. Lawrence, M. Fugate, C. M. Bowen, L. Ticknor, J. Woodring, J. Wendelberger, and J. Ahrens, “Partitioning a large simulation as it runs,” Technometrics, 2016.
• H. Godinez, E. Lawrence, D. Higdon, A. Ridley, J. Koller, and A. Klimenko, “Specification of the ionosphere-thermospere using the ensemble Kalman filter,” Dynamic Data-Driven Environmental Sys- tems Sciences, 2015.
• J. Kwan, K. Heitmann, S. Habib, N. Padmanabhan, E. Lawrence, H. Finkel, N. Frontiere, and A. Pope, “Cosmic emulation: Fast predictions for the galaxy power spectrum,” The Astrophysical Journal, 2015.
• C. J. Law, G. C. Bower, S. Burke-Spolaor, B. Butler, E. Lawrence, T. J. Lazio, C. Mattmann, M. Rupen, A. Siemion, and S. Vander Wiel, “A millisecond interferometric search for fast radio bursts with the Very Large Array,” The Astrophysical Journal, 2015.
• K. Heitmann, E. Lawrence, J. Kwan, S. Habib, and D. Higdon, “The Coyote Universe extended: Precision emulation of the matter power spectrum,” The Astrophysical Journal, 2014.
• E. Lawrence, D. Higdon, A. Walker, and M. Shoemaker, “Estimation for satellite collision probabilities using importance sampling,” Proceedings of the 24th AAS/AIAA Space Flight Mechanics Meeting, 2014.
• S. Vander Wiel, R. Bent, E. Casleton, and E. Lawrence, “Identification of topology changes in power grids using phasor measurements,” Applied Stochastic Models in Business and Industry, 2014.
• D. Higdon, J. R. Gattiker, E. Lawrence, C. Jackson, M. Tobis, M. Pratola, S. Habib, K. Heitmann, and S. Price, “Computer model calibration using the ensemble Kalman filter,” Technometrics, 2013.
• E. Lawrence, S. Vander Wiel, and R. Bent, “Model bank state estimation for power grids using im- portance sampling,” Technometrics, 2013.
• . Mehta, A. Walker, E. Lawrence, R. Linares, D. Higdon, and J. Koller, “Modeling satellite drag co- efficients with response surfaces,” Proceedings of the 2013 AAS/AIAA Astrodynamics Specifical Conference, 2013.
• D. Higdon, E. Lawrence, K. Heitmann, and S. Habib, “Simulation-aided inference in cosmology,” Statistical Challenges in Modern Astronomy V, 2012.
• D. Higdon, K. Heitmann, E. Lawrence, and S. Habib, “Using the Bayesian framework to combine sim- ulations and physical observations for statistical inference,” Large-Scale Inverse Problems and Quan- tification of Uncertainty, 2011.
• E. Lawrence, K. Heitmann, M. White, D. Higdon, C. Wagner, S. Habib, and B. Williams, “The Coyote Universe III: Simulation suite and precision emulator for the nonlinear matter power spectrum,” The Astrophysical Journal, 2010.
• E. Lawrence and D. Higdon, “Comment on article by Vernon et al.,” Bayesian Analysis, 2010.
• K. Heitmann, D. Higdon, M. White, S. Habib, B. Williams, E. Lawrence, and C. Wagner, “The Coyote Universe II: Cosmological models and precision emulation of the nonlinear matter power spectrum,” The Astrophysical Journal, 2009.
• E. Lawrence, D. Bingham, C. Liu, and V. N. Nair, “Bayesian inference for multivariate ordinal data using parameter expansion,” Technometrics, 2008.
• E. Lawrence, G. Michailidis, and V. N. Nair, “Statistical inverse problems in active network tomog- raphy,” IMS Lecture Notes–Monograph Series: Complex Datasets and Inverse Problems: Tomography, Networks and Beyond, 2007.
• J. R. Gattiker, E. Lawrence, and D. Higdon, “Analysis of multi-domain complex simulation studies,” Computational Science and Its Application - ICCSA 2006, 2006.
• E. Lawrence, G. Michailidis, and V. N. Nair, “Comment on monitoring networked applications with incremental quantile estimation,” Statistical Science, 2006.
• E. Lawrence, G. Michailidis, and V. N. Nair, “Flexicast delay tomography,” Journal of the Royal Statistical Society, Series B, 2006.
• E. Lawrence, G. Michailidis, V. N. Nair, and B. Xi, “Network tomography: A review and recent developments,” Frontiers in Statistics, 2006.
• E. Lawrence, G. Michailidis, and V. N. Nair, “Local area network analysis using end-to-end delay tomography,” Performance Evaluation Review and Sigmetrics ’05 Workshop on Large Scale Network Inference, 2005.
• E. Lawrence, G. Michailidis, and V. N. Nair, “Maximum likelihood estimation of internal network link delay distributions using multicast measurements,” Proceedings of the 37th Conference on Information Sciences and Systems, 2003.
• T. Catanach, M. Garcia, S. Vander Wiel, R. Bent, and E. Lawrence, “Power system dynamic state estimation using a layered local-global method,” IEEE Transactions on Signal Processing, In Progress.
• J. Ang, D. Bingham, and E. Lawrence, “A Bayesian approach to spatial correlation in the multivariate probit model,” Technometrics, In Progress.
• T. L. Graves, M. Hamada, N. Hengartner, D. Higdon, A. Huzurbazar, E. Lawrence, C. D. Linkletter, C. S. Reese, D. Scott, R. Sitter, R. Warr, and B. Williams, “Using simulated likelihood with discretized continuous data in Bayesian analysis,” Technometrics, In Progress.
• T. L. Graves, E. Lawrence, K. Myers, and C. S. Reese, “Ratings using score histories,” Journal of Quantitative Analysis in Sports, In Progress.
• M. Grosskopf, K. Myers, and E. Lawrence, “Time series alignment for cyberphysical network intrusion detection,” Annals of Applied Statistics, In Progress.
• E. Hou, E. Lawrence, and A. O. Hero, “Penalized ensemble Kalman filter for high-dimensional non- linear systems,” Monthly Weather Review, In Progress.
• N. Klein, E. Lawrence, D. J. Walters, D. J. Luscher, and K. Ramos, “Autoencoders for emulation and calibration of multivariate output,” Technometrics, In Progress.
• R. Payne, E. Lawrence, D. Higdon, K. Heitmann, and S. Habib, “Deep process convolutions,” Journal of the American Statistical Association, In Progress.
• S. Vander Wiel, S. Burke-Spolaor, E. Lawrence, C. J. Law, and G. C. Bower, “Rare event statistics applied to transient science,” The Astrophysical Journal, In Revision.