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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 a group leader within the Data Centric Engineering Programme of The Alan Turing Institute: see the project page for more details and get in touch if you're interesting in becoming involved.
He will lead the Robust, Scalable Sequential Monte Carlo with Application To Urban Air Quality project from April 2020 — again, get in touch if you're interested in becoming involved.
He is an investigator within The CoSinES Project.
He is co-director of APTS.

There is currently a vacancy for a postdoctoral research associate within my group — feel free to contact me with informal inquiries.


Some generic teaching information - - applicable to my personal tutees, MSc students and those attending my lectures is available from my teaching page.


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.

  • J. Koskela, P. Jenkins, A. M. Johansen, and D. Spanò. Asymptotic genealogies of interacting particle systems with an application to sequential Monte Carlo. To appear in Annals of Statistics [arxiv]
  • P. Guarniero, A. M. Johansen and A. Lee. The Iterated Auxiliary Particle Filter. Journal of the American Statistical Association 112(520):1636–1647, 2017 [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

    MSB 2.18

    024761- 50919

    a dot m dot johansen at