Ajay Jasra
Associate
Professor, Department of Statistics and
Applied Probability (DSAP), National
University of Singapore.
Degrees,
Positions & Editorial Work
Since 12/2011-: Associate Professor (Tenure Track),
DSAP, National University of Singapore, SG.
09/2008-12/2011:
Assistant Professor (Tenured), Mathematics,
Imperial College London.
03/2008-09/2008:
Lecturer, Institute of Statistical Mathematics,
JP.
10/2006-03/2008:
Chapman Fellow of Mathematics, Mathematics, Imperial College London.
02/2006-10/2006:
Research Associate, Engineering,
10/2005-02/2006:
Research Associate, Statistics,
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:
American Journal of
Algorithms and Computing
(2012-)
Statistics
and Computing (2011-)
Stat
(2012-).
Research Interests
Bayesian Statistics.
Computational finance.
Markov chain theory.
For more information on my research, please see my Google
Scholar profile.
Publications: Journals
(2013) Beskos, A., Crisan D., Jasra, A. & Whiteley, N. Error bounds and normalizing constants for
SMC. Adv. Appl. Probab. (to appear). Arxiv
version.
(2013) Cozzini,
A., Jasra, A. & Montana, G. Model-based
clustering with gene ranking. J. Bio. Comp. Biol. (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.
(2013) Persing A. & Jasra A. Likelihood
estimation for hidden Markov models, Stat.
Prob. Lett. Preliminary version.
(2012)
Tsagaris, T, Jasra, A &
Adams, N. Robust
and Adaptive algorithms for online portfolio selection. Quant. Finance. Arxiv
version.
(2012) Jasra, A., Singh, S,
Martin, J & McCoy E. Filtering
via ABC, Stat. Comp. (in the special issue on ABC: introduction).
(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) Jasra, A, De Iorio, M. & Chadeau-Hyam M The Time Machine. Proc.
(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.
(2009) Jasra,
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.
(2006) Del Moral, P, Doucet, A & Jasra, A, Sequential
Monte Carlo Samplers, JRSSB. A related note
is available here.
(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,
ESIAM Proc.
(2007) Andrieu, C, Jasra, A, Doucet, A & Del
Moral, P, Non-Linear Markov chain
ESIAM Proc.
(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.
Technical Reports
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.
Collaborators
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.
Christophe
Andrieu (
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
Post-Docs:
Pierre
Jacob (NUS, 2012-2013). See Christian Robert’s blog for
some info on Pierre.
Adam Persing.
Research Students:
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.
Current:
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.
Completed:
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.
Teaching
NUS
ST5223
In August 2012 I taught ST5223 Statistical Models:
Theory and Applications. The notes are available here.
The non-assessed problem sheets are here:
ST2334
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:
Bayes Theorem
and the Theorem of Total Probability (1.3)
The Binomial
and Poisson Distribution (2.3.1)
The Geometric and
Negative Binomial Distribution + MGFs (2.3.3)
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.
Here is a mock exam (which
is a little easy) with solutions.
This is a make-up exam which was
conducted on 26/4, with solutions.
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.
Contact Details
Block S16, Office 04-04
Department of Statistics and Applied Probability
National University of Singapore
6 Science Drive 2,
Singapore, 117546
e-mail: staja@nus.edu.sg
phone: (+65)
66011410