Joonha Park's Research interests & Publications

I am a postdoctoral research associate at the Department of Mathematics and Statistics at Boston University, under the supervision of professor Yves Atchade.  I received a Ph.D. in Statistics at the University of Michigan in June 2018 under the supervision of Professor Edward Ionides.

My recent works include 
1. The development of a spatiotemporal inference methodology for coupled stochastic dynamic models, such as spatiotemporal models addressing the transmission dynamics of infectious diseases 
 The implementation of related methods, including the codes and the data, can be found at the Github repository
 An R package SpatPomp is under development for wider accessibility to researchers in various applied fields.

2. A novel, general framework in Markov chain Monte Carlo with sequential proposals
 The implementation of the algorithms discussed in this paper is available at

My other published papers can be found in my CV and the links below:

3. Ionides, E. L., Breto, C., Park, J., Smith, R. A. and King, A. A. (2017) Monte Carlo profile confidence intervals for dynamic systems. Journal of The Royal Society Interface, 14, 20170126.
4. Koopman, J. S., Henry, C. J., Park, J., Eisenberg, M. C., Ionides, E. L. and Eisenberg, J. N. (2017) Dynamics affecting the risk of silent circulation when oral polio vaccination is stopped. Epidemics.
5. Kim, S.-H., Park, J. H., Yoon, W., Ra, W.-S. and Whang, I.-H. (2017) A note on sensor arrangement for long-distance target localization. Signal Processing, 133, 18–31.

I have research interests in Monte Carlo methods (SMC, MCMC), inference on high-dimensional partially observed Markov process (POMP) models (or hidden Markov models or state-space models), stochastic processes, high-dimensional data, the theory and applications of neural networks, machine learning, and epidemiological, ecological, environmental, and biological applications.

For further information, please email me at