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Dr Adam Johansen

Dr Adam Johansen is a Reader in Statistics; his research focuses upon methodological and theoretical aspects of simulation-based algorithms.
He is co-director of APTS.


Some generic teaching information - - applicable to my personal tutees, MSc students and those attending my lectures is available from my teaching page. This year I will be lecturing ST407 Monte Carlo Methods.

I will be lecturing the APTS Computer Intensive Statistics module again in 2017.


Students and Collaborators

Current interests include Monte Carlo methodology, particularly sequential methods together with Bayesian statistics and decision theory more generally.

Information about former students.

Prospective Ph.D. students should feel free to email me to discuss possible research directions and might find the theses of some of my former students (available by following the above link) useful indicators of the types of project in which I am typically involved.

Current Ph.D. Students:


(Pre)Publications to date are listed here. Selected recent additions are listed below.

  • P. Guarniero, A. M. Johansen and A. Lee. The Iterated Auxiliary Particle Filter. To appear in Journal of the American Statistical Association [journal|arxiv]
  • F. Lindsten, A. M. Johansen, C. Naesseth, B. Kirkpatrick, T. Schön, J. A. D. Aston, and A. Bouchard-Côté. Divide and conquer with sequential Monte Carlo. Journal of Computational and Graphical Statistics 26(2):445–458, 2017. [journal website|arxiv]
  • Y. Zhou, A. M. Johansen and J. A. D. Aston, Towards Automatic Model Comparison: An Adaptive Sequential Monte Carlo Approach. Journal of Computational and Graphical Statistics, 25(3):701--726, 2016. [journal|arxiv]
  • M. Pollock, A. M. Johansen and G. O. Roberts, On Exact and -strong Simulation of (Jump) Diffusions. Bernoulli, 22(2):794--856, 2016. [pdf|journal website|arxiv].


     Dr Johansen

    Adam M. Johansen

    C0.20 Zeeman Building

    024761- 50919

    a dot m dot johansen at