Bio

Dave Campbell is an internationally recognized expert in data science whose methodological research customizes methods with domain knowledge to improve algorithm performance and insights. His publications include co-authored discussion papers in the Journal of the Royal Statistical Society and Bayesian Analysis. He has been heavily involved in the data science practicing and academic communities. Before joining the Bank, Dr. Campbell was a full professor with cross joint appointment in Statistics and Computer Science at Carleton University. He was the inaugural President of the Data Science and Analytics Section of the Statistical Society of Canada and a co-organizer of the Vancouver Learn Data Science Meetup. He led the development of a BSc in Data Science while he was a faculty member at Simon Fraser University.


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Journal publications

Selected Peer Reviewed Publications

  • Carleton, W. C., Campbell, D., and Collard, M. “Rainfall, temperature, and Classic Maya conflict: A comparison of hypotheses using Bayesian time-series analysis”, PLOS ONE 16, no. 7, (July 2021). doi : 10.1371/journal.pone.0253043.
  • McDonald, S., Campbell, D. “A Review of Uncertainty Quantification for Density Estimation”, Statistics Surveys 15, (2021):1–71. doi.org/10.1214/21-SS130
  • Baitz, H. A., Jones, P.W., Campbell, D., Jones, A.A., Gicas, K.M., Giesbrecht, C.J. , Thornton, W.L., Barone, C.C., Wang, N. Y., Panenka, W.J., Lang, D.J., Vila-Rodriguez, F., Leonova, O., Barr, A.M. , Procyshyn, R.M., Buchanan, T., Rauscher, A., Macewan, G.W. , Honer , W.G. and Thornton, A.E. “Component processes of decision making in a community sample of precariously housed persons: associations with learning and memory, and health-risk behaviours”, Frontiers in Psychology 12, no. 2, (July 2021). doi: 10.3389/fpsyg.2021.571423
  • Carleton, W. C., Campbell, D., and Collard, M. “A reassessment of the impact of temperature change on European conflict during the second millennium CE using a bespoke Bayesian time-series model”, Climatic Change 265, no. 4 (March 2021). doi : 10.1007/s10584-021-03022-2
  • Chkrebtii, O., and Campbell, D. “Adaptive step-size selection for state-space based probabilistic differential equation solvers” Statistics and Computing 29, no. 3 (September 2019): 1285-1295. doi : 10.1007/s11222-019-09899-5.
  • Stojkova, B. J. and Campbell, D., “Incremental Mixture Importance Sampling with Shotgun Optimization" Journal of Computational and Graphical Statistics 28, no. 4 (2019):806-820. doi: 10.1080/10618600.2019.1592756
  • Carleton, W. C., Campbell, D. and M. Collard , “Radiocarbon dating uncertainty and the reliability of the PEWMA method of time-series analysis for research on long-term human-environment interaction” PLOS ONE 13, no. 1, January (2018).  doi:10.1371/journal.pone.0191055
  • Carleton, W. C., Campbell, D., and Collard, M.  “Increasing temperature exacerbated Classic Maya conflict over the long term" Quaternary Science Reviews 163, (May 2017):209-218. doi : 10.1016/j.quascirev.2017.02.022.
  • Chkrebtii, O., Campbell, D., Calderhead, B., Girolami, M. “Bayesian Solution Uncertainty Quantification for Differential Equations”, Bayesian Analysis (Discussion paper with rejoinder) 11, no. 4 (2016):1239-1299. doi: 1214/16-BA1036
  • Golchi, S. and Campbell, D. “Sequentially Constrained Monte Carlo”, Computational Statistics and Data Analysis 97, (2016):98-113. doi : 10.1016/j.csda.2015.11.013
  • Golchi, S. Bingham, D., Chipman, H., Campbell, D. “Monotone Function Estimation for Computer Experiments” Journal of Uncertainty Quantification 3, no. 1, 14 (June 2015):370-392. doi : 1137/140976741
  • Cameron, E., Chkrebtii, O., Campbell, D., Bayne, E. “Trans-Dimensional Approximate Bayesian Computation for inference on models of invasive species” Computational Statistics and Data Analysis 86 (December 2015):97-110. doi : 10.1016/j.csda.2015.01.002
  • Campbell, D., and Subhash L. "An ANOVA Test for Parameter Estimability Using Data Cloning with Application to Statistical Inference for Dynamic Systems." Computational Statistics and Data Analysis 70 (February 2013):257-267. doi:10.1016/j.csda.2013.09.013.
  • Campbell, D., Chkrebtii, O. “Maximum Profile Likelihood Estimation of Differential Equation Parameters through Model Based Smoothing State Estimates”, Mathematical Biosciences 246, no. 2, (April 2013): 283-292. doi:10.1016/j.mbs.2013.03.011
  • Campbell, D., Hooker, G., McAuley, K. "Parameter Estimation in Differential Equation Models With Constrained Variables", Journal of Chemometrics 26, no. 6, (June 2012):322-332. doi: 10.1002/cem.2416
  • Campbell, D. and Steele, R., “Smooth Functional Tempering for Nonlinear Differential Equation Models”, Statistics and Computing 22, (March 2011):429-443. doi:10.1007/s11222-011-9234-3
  • Ramsay, J. O., Hooker, G., Campbell, D., and Cao, J., "Parameter Estimation for Differential Equations: A Generalized Smoothing Approach (with Discussion)," Journal of the Royal Statistical Society Series B 69, no. 5, (November 2007):741-796. doi : 10.1111/j.1467-9868.2007.00610.x