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David H. Collins Jr.

Dave Collins

Phone (505) 667-9186


  • Computational Physics and Applied Mathematics
  • Monte Carlo methods
  • Discrete event simulation
  • Statistics
  • Uncertainty quantification
  • Weapons Science and Engineering
  • Quantification of margins and uncertainty (QMU)


Reliability analysis

Stochastic processes, flowgraphs

Accelerated aging models


Ph.D., Statistics, University of New Mexico, 2009

M.S., Statistics, University of New Mexico, 2005

B.A., Computational Mathematics (summa cum laude), Fordham University, 1983


LANL Positions

Scientist, Statistical Sciences Group (CCS-6), 2012-present

Postdoctoral Research Associate, Statistical Sciences Group (CCS-6), 2009-2012


Professional Societies

Senior life member of the Association for Computing Machinery (ACM); senior member of the American Society for Quality (ASQ); member of the Institute of Electrical and Electronics Engineers (IEEE), American Statistical Association (ASA), Institute of Mathematical Statistics (IMS), American Association for the Advancement of Science (AAAS), Military Operations Research Society (MORS); Secretary, ASA Section on Quality and Productivity (2014 – 2018); Chapter Representative, Albuquerque Chapter of the ASA (2010-2014); Past President (1993) of the Hudson Valley Chapter of the Human Factors and Ergonomics Society. 



Journal of Quality Technology Lloyd S. Nelson Award (2014, with coauthors J. K. Freels, A. V. Huzurbazar, R. L. Warr, and B. P. Weaver) for the article in 2013 (“Accelerated test methods for reliability prediction”) having "The greatest immediate impact to practitioners." 

2014 Defense Programs Award of Excellence "For significant contributions to the Stockpile Stewardship program".



Collins, D. H., Weaver, B. P., and Hamada, M. S. (2017), “Panning for gold: Enhancing the precision of sensitivity test data,” Statistical Analysis and Data Mining: The ASA Data Science Journal 10 (3), 166-181.

Warr, R. L., and Collins, D. H. (2015), “A comprehensive method for solving finite-state semi-Markov processes,” International Journal of Simulation and Process Modelling 10 (1), 89-99.

Collins, D. H., and Huzurbazar, A. V. (2014), “Revisiting Drenick’s failure law of complex equipment,” JSM Proceedings, Section on Physical and Engineering Sciences, Alexandria, VA: American Statistical Association.

Warr, R. L., and Collins, D. H. (2014), “Bayesian nonparametric models for combining heterogeneous reliability data,” Proceedings of the Institution of Mechanical Engineers, Part O, Journal of Risk and Reliability 228 (2) 166-175.

Collins, D. H., Freels, J. K., Huzurbazar, A. V., Warr, R. L., and Weaver, B. P. (2013), “Accelerated test methods for reliability prediction,” Journal of Quality Technology 45 (3) 244-259.

Collins, D. H., Warr, R. L., and Huzurbazar, A. V. (2013), “An introduction to statistical flowgraph models for engineering systems,” Proceedings of the Institution of Mechanical Engineers, Part O, Journal of Risk and Reliability 227 (5) 461-470.

Collins, D. H., and Huzurbazar, A. V. (2013), “Multistate stochastic processes: A statistical flowgraph perspective,” International Statistical Review 81 (1) 78-106.

Collins, D. H. and Huzurbazar, A. V. (2013), “Graph-theoretic analysis of complex stochastic networks,” JSM Proceedings, Section on Statistical Graphics, Alexandria, VA: American Statistical Association, 47-60.

Collins, D. H.,  and Huzurbazar, A. V. (2012), “Prognostic models based on statistical flowgraphs,” Applied Stochastic Models in Business and Industry 28, 141-151.

Collins, D. H., Anderson-Cook, C. M., and Huzurbazar, A. V. (2011), “System health assessment,” Quality Engineering, 23 (2), 141-152.

Collins, D. H., Huzurbazar, A. V., and Anderson-Cook, C. M. (2010), “Statistical tools for prognostics and health management of complex systems,” Proceedings of the 57th JANNAF Propulsion Meeting, Colorado Springs, CO.

Collins, D. H., and Huzurbazar, A. V. (2008), “System reliability and safety assessment using nonparametric flowgraph models,” Proceedings of the Institution of Mechanical Engineers, Part O, Journal of Risk and Reliability 222, 667-674.