Simon Jackman is a political scientist and statistician, formerly at Stanford University and subsequently at the University of Sydney. He has contributed to the adoption of Bayesian and MCMC methods in quantitative political science, with well-known pedagogical treatments of Gibbs sampling and Metropolis-Hastings and applications to ideal-point estimation in legislative bodies.
Jackman (2000): Pedagogical tour MLE → EM → Gibbs → MH for political scientists; probit via Albert-Chib truncated-Normal data augmentation; AR(1) 3-block Gibbs; MNP via McCulloch-Polson-Rossi; Geweke and Gelman-Rubin convergence diagnostics; BUGS/WinBUGS advocacy. American Journal of Political Science 44(2): 375–404.
Count-data models in R — Zeileis-Kleiber-Jackman (2008): With Achim Zeileis and Christian Kleiber, the pscl implementation of hurdle and zero-inflated count regression. See Count-Data Regression and Zeileis-Kleiber-Jackman (2008). (Jackman is also the author of the pscl package.)