Degrees, Positions & Editorial Work
Since 12/2011-: Associate Professor (Tenure Track), DSAP, National University of Singapore, SG.
03/2008-09/2008: Lecturer, Institute of Statistical Mathematics, JP.
10/2006-03/2008: Chapman Fellow of Mathematics, Mathematics, Imperial College London.
10/2002-10/2005: Ph.D., Imperial College London. Supervisors: Chris Holmes and Dave Stephens.
I am also an affiliated member of the risk management institute at NUS.
Short-term academic visitor at:
University of Bristol (Statistics) and
University College London (Statistics) (May-July, 2012).
Institute of Statistical Mathematics (Jul-Sept, 2007).
I am currently associate editor at:
Statistics and Computing (2011-)
Markov chain theory.
For more information on my research, please see my Google Scholar profile.
(2013) Beskos, A., Crisan D., Jasra, A. & Whiteley, N. Error bounds and normalizing constants for SMC. Adv. Appl. Probab. (to appear). Arxiv version.
(2013) Jasra, A., Kantas N. & Persing, A. Bayesian parameter inference for partially observed stopped processes Stat. Comp. (to appear). Arxiv version.
(2013) Martin, J., Jasra, A. & McCoy, E. Inference for a class of partially observed point process. Ann. Inst. Statist. Math. Arxiv version.
(2012) Tsagaris, T, Jasra, A & Adams, N. Robust and Adaptive algorithms for online portfolio selection. Quant. Finance. Arxiv version.
(2012) Del Moral, P., Doucet, A. & Jasra, A. An Adaptive Sequential Monte Carlo Method for Approximate Bayesian Computation. Stat. Comp.
(2012) Whiteley, N., Kantas, N. & Jasra, A. Linear variance bounds for particle approximations of time homogeneous Feynman-Kac formulae. Stoch. Proc. Appl.
(2012) Del Moral, P., Doucet, A. & Jasra, A. On Adaptive Resampling Procedures for SMC Methods, Bernoulli.
(2011) Andrieu, C, Jasra, A, Doucet, A & Del Moral, P, On Non-Linear Markov chain Monte Carlo, Bernoulli.
(2011) Jasra, A. & Holmes CC. Stochastic Boosting Algorithms, Stat. Comp.
(2011) Jasra, A. & Del Moral, P. SMC for option pricing, Stoch. Anal. Appl.
(2011) Jasra, A. Stephens, DA, Doucet, A, & Tsagaris, T., Inference for Levy driven SV Models, Scand. J. Statist.
A. & Doucet, A. SMC
Methods for Diffusions, Proc.
(2009) Holmes, CC & Jasra, A. Antithetic Methods for Gibbs Samplers, J. Comp. Graph Stat.
(2009) Pei, T., Jasra, A., Hand D. J., Zhu, A. & Zhou, C. DECODE: a new method for discovering clusters in spatial data, Data Min. Know. Discov.
(2008) Jasra, A, & Doucet, A, Stability of Sequential Monte Carlo Samplers. Stat. Prob. Lett.
(2008) Andrieu, C, Jasra, A, Doucet, A & Del Moral, P, A note on the convergence of the Equi-Energy Sampler, Stoch. Anal. Appl.
(2008) Jasra, A, Doucet, A, Stephens, DA & Holmes, CC, Interacting SMC Samplers, Comput. Stat. and Data Analy.
(2008) Jasra, A, & Yang, C, A regeneration proof of the CLT for uniformly ergodic Markov chains, Stat. Prob. Lett.
(2007) Jasra, A, Stephens, DA, & Holmes, CC Population-based reversible Jump MCMC, Biometrika.
(2007) Jasra, A, Stephens DA & Holmes, CC, On population-based simulation for static inference、Stat. Comp.
(2006) Jasra, A, Stephens, DA, Gallagher, KL & Holmes, CC, Bayesian Mixture Modelling in Geochronology via Markov chain Monte Carlo, Math. Geol.
(2005) Jasra A, Holmes CC & Stephens DA, MCMC methods and the label switching problem in Bayesian mixture modelling, Stat. Sci.
Publications: Conference/ In Books/ Discussions/Book Reviews
(2012) Jasra, A. Review of `Understanding Probability’. Asia Pacific Mathematics News Letter.
(2012) Barthelme’ S., Chopin, N., Jasra A. & Singh, S. Comments on the paper of Fearnhead & Prangle.
(Thanks to Christian Robert for producing the linked document), JRSSB.
(2012) Jasra, A. Comments on the paper of Fearnhead & Prangle. JRSSB.
(2012) Jasra, A. Review of `Exploring Monte Carlo Methods’. Materials Today.
(2011) Jasra, A. & Singh, S. Comments on the paper of Girolami & Calderhead, JRSSB.
(2007) Hoffman, M., Doucet, A. De Freitas, N. & Jasra, A. Bayesian Policy Learning with Trans-Dimensional MCMC, NIPS.
(2007) Andrieu, C, Jasra, A, Doucet, A & Del Moral, P, Convergence of the Equi-Energy Sampler,
(2007) Andrieu, C, Jasra, A, Doucet, A & Del
Moral, P, Non-Linear Markov chain
(2006) Gallagher, KL, Jasra, A, Stephens, DA & Holmes, CC, A new approach to mixture modelling for geochronology,
16th Annual V M Goldschmidt Conference.
(2006) Doucet, A, Montesano, L & Jasra, A, Optimal filtering for partially observed point processes, ICASSP.
(2006) Del Moral, P, Doucet, A & Jasra, A, Sequential Monte Carlo for Bayesian Computation, Bayesian Statistics 8.
These are all submitted (or about to be) preprints.
(2013) Wang J., Jasra A. & De Iorio M. Computational methods for a class of network models.
(2013) Jasra A. & Wang J. An adaptive SMC method for permanents.
(2013) Jasra, A., Lee, A., Zhang X. & Yau, C. The alive particle filter.
(2013) Jasra, A., Kantas,N. Approximate inference for observation driven time series models.
(2013) Campanella, G., De Iorio, M., Jasra, A. & Chadeau-Hyam, M. The TimeMachine package for inference on stochastic trees. Manual.
(2013) Nott, D., Zhang, X.,Yau C. & Jasra, A. A sequential algorithm for fast fitting of mixtures.
(2012) Jasra, A., & Kantas, N. Static parameter estimation for ABC approximations of HMMs.
(2012) Martin, J., Jasra, A., Singh, S. S., Whiteley, N. & McCoy, E. ABC Smoothing.
(2012) Cozzini, A., Jasra, A. & Montana G. A Bayesian Mixture of Lasso Regressions with t-Errors.
(2011) Beskos, A., Crisan, D. & Jasra, A. On the stability of sequential Monte Carlo methods in high dimensions. New version.
(2010) Dean, T., Singh, S., Jasra, A. & Peters, G. Parameter Estimation for Hidden Markov Models with Intractable Likelihoods.
This list includes co-authors (past/present, including those on minor publications such as comments), former advisors
and those whom I have been involved with as co-supervisors of students + postdocs.
David Balding (UCL, Genetics Institute).
Simon Barthelme’ (Berlin University of Technology).
Alex Beskos (NUS, Statistics).
Marc Chadeau (Imperial College London, School of Public Health).
Hock Peng Chan(NUS, Statistics)
Nicolas Chopin (CREST-ENSAE).
Dan Crisan (Imperial College London, Mathematics).
Tom Dean (DPFM)
Pierre Del Moral (Universite’ Bordeaux, Mathematics).
Nando De Freitas (University of British Columbia, CS).
Maria De Iorio (University College London, Statistics).
Arnaud Doucet (University of Oxford, Statistics).
Kerry Gallagher (Universitie Rennes, Geosciences).
Chris Holmes (
Nikolas Kantas (University College London, Statistics).
Anthony Lee (University of Warwick, Statistics).
Emma McCoy (Imperial College London, Statistics)
Giovanni Montana (Imperial College London, Statistics)
David Nott (NUS, Statistics)
Gareth Peters (University College London + UNSW, Maths and Statistics)
Sumeetpal Singh (University of Cambridge, Engineering).
Dave Stephens (
Theo Tsagaris (Tudor Capital).
Nick Whiteley (University of Bristol, Statistics).
Chris Yau (Imperial College London, Statistics)
Research Students and Post-Docs
If you would like to do a PhD with me, please go through NUS. Many of my students should graduate in this calendar year (starting 06/13), so
I can supervise/advise new students.
S. Wang (CSC, from September 2013). Co-supervision.
C. W. Heng (NUS, 2012-Present). 2nd Supervisor, with Hock Peng Chan.
J. Wang (NUS, 2012-Present). Joint with David Nott.
A. Persing (IC, 2011-Present). Joint with Dan Crisan and Leonardo Bottolo.
X. Zhang (IC, 2011-Present). Joint with Chris Yau.
E. Ehrlich (IC, 2011-2013), PhD.
Co-Supervisor: Nikolas Kantas.
J. Martin (IC, 2008-2012), PhD.
Co-Supervisor: Emma McCoy.
A. Cozzini (IC, 2010-2012), PhD.
Co-Supervisor: Giovanni Montana.
C. Oduneye (IC, 2010-2011), PhD.
Co-Supervisor: David Stephens.
M. Bottone (IC, 2009-2010), MPhil.
Co-Supervisor: David Stephens.
I. Shiekh (IC, 2008-2010), PhD.
Co-Supervisor: Emma McCoy.
In August 2012 I taught ST5223 Statistical Models: Theory and Applications. The notes are available here.
The non-assessed problem sheets are here:
From August 2013 I will be teaching ST2334 Probability and Statistics. Notes, subject to change.
It should be possible (at least for those at NUS) to view a video of the lectures online, this was from last semester:
Some example sheets, in brackets are the associated section of the notes:
Joint Expectations (2.3.4)
Joint PMFs (2.3.4)
Conditional Expectations (2.3.5)
More Conditional Expectations (2.3.5)
Continuous Random Variables (2.4.1)
Notes on Integration (Useful for Sections 2.4 onwards)
Non-Assessed problem sheets:
Examination: Here is a check-list that should assist your revision.
Imperial College London
I taught M3S4\M4S4 Applied probability. The notes are available on request.
I taught M3S9\M4S9 Stochastic Simulation. The notes are available on request.
Block S16, Office 04-04
Department of Statistics and Applied Probability
National University of Singapore
6 Science Drive 2,
phone: (+65) 66011410