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.
Students and Collaborators
Current interests include Monte Carlo methodology, particularly sequential methods together with Bayesian statistics and decision theory more generally.
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:
- Thomas Honnor (co-supervisor Julia Brettschneider) -- Submitted and awaiting viva.
- Tom Jin (co-supervisor Frank Wood)
- Lewis Rendell (co-supervisor Anthony Lee)
- Måns Unosson (co-supervisor Bärbel Finkenstädt )
(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].
Adam M. Johansen
C0.20 Zeeman Building
a dot m dot johansen at warwick.ac.uk