__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.

I am also an affiliated member of the risk management institute and centre for quantitative

finance at NUS. I am an associate member of the stochastic analysis group at Imperial College London.

I am currently associate editor at:

American Journal of
Algorithms and Computing
(2012-)

Statistics
and Computing (2011-)

Stat
(2012-).

__Funding __

My Research is funded by the following grants:

AcRF Tier 2
Grant: `Approximate Computational Methods for High-Dimensional Systems’ (Co-PI
with Nott).

2014-2017, S$572820.

EPSRC Grant: `Advanced Stochastic Computation for
Stochastic Trees’ (Visiting Researcher with De Iorio,

Beskos and Balding). 2013-2016, £401382.

MOE Grant: `Approximate and High-Dimensional
Filtering’. 2012-2015, S$174200.

__Research Interests __

Bayesian Statistics.

Computational finance.

Markov chain theory.

For more information on my research, please see my Google
Scholar profile.

__Publications: Journals (40)__

(2014) Persing A. & Jasra A.
Twisting the alive particle filter. Meth. Comp.
Appl. Probab. (to
appear). arXiv.

(2014) Wang J.
& Jasra A. Monte Carlo
algorithms for computing alpha-permanents. Stat. Comp. (to
appear). Preliminary.

(2014) Yildirim, S., Singh S. S., Dean T., & Jasra A. Parameter
estimation in HMMs with intractable likelihoods via SMC. JCGS (to appear). arXiv.

(2014) Kantas,
N., Beskos, A., & Jasra,
A. SMC for inverse problems:
a case study for Navier Stokes. SIAM/ASA JUQ (to
appear). arXiv.

(2014) Jasra,
A. On
the behaviour of the backward Feynman-Kac formula.
J. Appl. Probab. (to
appear). arXiv.

(2014) Dean, T., Singh, S., Jasra,
A. & Peters, G. Estimation
of HMMs with Intractable Likelihoods. Scand. J. Statist. (to appear). arXiv.

(2014) Zhang,
X., Nott, D., Yau, C. & Jasra,
A. A
sequential algorithm for fast fitting of mixtures. JCGS (to appear). arXiv.

(2014) Ehrlich,
E., Jasra, A., & Kantas,
N. Gradient
free parameter estimation for intractable HMMs. Meth. Comp.
Appl. Probab. (to
appear). arXiv.

(2014) Cozzini,
A., Jasra, A. Montana G. & Persing
A. Bayesian
Mixture of Lasso Regressions., Comput. Stat. Data Anal.
77, 84-97. arXiv.

(2014) Beskos, A., Crisan, D. & Jasra, A. On the stability of SMC
in high-dimensions. Ann. Appl. Probab. 24, 1396-1445. arXiv**.**

(2014) Jasra, A., Kantas,
N. & Ehrlich E. Approximate
inference for observation driven time series. TOMACS, 24, article 13. arXiv.

(2014) Martin, J., Jasra, A., Singh, S., Whiteley,
N., Del Moral, P. & McCoy, E. ABC
Smoothing. Stoch. Anal. Appl. 32, 397-422. arXiv.

(2014) Beskos, A., Crisan D., Jasra, A. & Whiteley, N. Error bounds for SMC in
high-dimensions. Adv. Appl. Probab. 46, 279-306. arXiv.

(2014) Wang J.,
Jasra A. & De Iorio M. Computational
methods for network models. J. Comp.
Biol. 21, 141-161. arXiv.

(2014) Jasra, A., Kantas N. & Persing, A. Bayesian
inference for partially observed stopped processes Stat. Comp. 24, 1-20. arXiv.

(2013) Cozzini, A., Jasra, A. &
Montana, G. Model-based
clustering with gene ranking. J. Bio. Comp. Biol. 11, 1341007.
arXiv.

(2013) Martin,
J., Jasra, A. & McCoy, E. Inference for a
class of partially observed point process. Ann. Inst. Statist. Math.
65, 413-437. arXiv.

(2013) Persing
A. & Jasra A. Likelihood
estimation for hidden Markov models, Stat. Prob. Lett. 83, 1433-1442. Preliminary.

(2012) Tsagaris, T, Jasra, A & Adams, N. Robust
and Adaptive algorithms for online portfolio selection. Quant.
Finance. 12, 1651-1662. arXiv.

(2012) Jasra,
A., Singh, S, Martin, J & McCoy E. Filtering
via ABC, Stat. Comp. 22, 1223-1237. (in the
special issue on ABC: introduction).

(2012) Del Moral, P., Doucet, A. & Jasra, A. An
Adaptive SMC Method for Approximate Bayesian Computation. Stat. Comp. 22, 1009-1020.

(2012) Whiteley, N., Kantas, N. & Jasra, A. Linear
variance for particle approximations of F-K formulae. Stoch. Proc. Appl. 122, 1840-1865.

(2012) Del Moral, P., Doucet, A. & Jasra, A. On Adaptive Resampling Procedures for SMC Methods,
Bernoulli. 18, 252-272.

(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. 17, 987-1014.

(2011) Jasra,
A. & Holmes CC. Stochastic
Boosting Algorithms, Stat. Comp. 21, 335-347.

(2011)
Jasra, A. & Del Moral, P. SMC
for option pricing, Stoch. Anal. Appl. 29, 292-316.

(2011) Jasra,
A. Stephens, DA, Doucet, A, & Tsagaris, T., Inference
for Levy driven SV Models, Scand. J. Statist. 38, 1-22.

(2009) Jasra,
A. & Doucet, A. SMC
Methods for Diffusions, Proc.

(2009) Holmes, CC & Jasra, A. Antithetic
Methods for Gibbs Samplers, JCGS. 18, 401-414.

(2009) Pei, T., Jasra, A., Hand D. J., Zhu, A.
& Zhou, C. DECODE:
a new method for clusters in spatial data, Data Min. Know. Disc. 18,
337-369.

(2008) Jasra,
A, & Doucet, A, Stability
of SMC Samplers. Stat. Prob. Lett. 78, 3062-3069.

(2008) Andrieu,
C, Jasra, A, Doucet, A
& Del Moral, P, A
note on the convergence of the Equi-Energy Sampler,
Stoch. Anal. Appl. 26, 298-313.

(2008) Jasra,
A, Doucet, A, Stephens, DA & Holmes, CC, Interacting
SMC Samplers, Comput. Stat. Data Anal. 10, 1765-1791.

(2008) Jasra,
A, & Yang, C, A
regeneration proof of the CLT for uniformly ergodic
Markov chains, Stat. Prob. Lett. 78, 1649-1655.

(2007) Jasra,
A, Stephens, DA, & Holmes, CC Population-based
reversible Jump MCMC, Biometrika. 94, 787-807.

(2007) Jasra,
A, Stephens DA & Holmes, CC, On
population-based simulation for static inference、Stat.
Comp. 17, 263-279.

(2006) Jasra,
A, Stephens, DA, Gallagher, KL & Holmes, CC, Bayesian Mixture
Modelling in Geochronology via MCMC, Math. Geol. 38, 269-300.

(2006) Del Moral, P, Doucet, A & Jasra, A, Sequential
Monte Carlo Samplers, JRSSB. 68, 411-436. 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. 20, 50-67.

__Publications: Conference/ In Books/ Discussions/Book
Reviews (11)__

(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 (7)__

These are all submitted (or about to be)
preprints.

(2014) Persing,
A., Jasra A., Beskos A.,
Balding D. & De Iorio M. A simulation approach
for change-points on trees.

(2014) Wang, S., Shi, T., Zhang, L., Jasra, A., Zeng, M. Extended H_{\infty}
finite time control.

(2014) Zhang, L, Wang, S., Karimi, H. R. & Jasra A.
Robust finite-time control of delayed systems.

(2014) Beskos,
A., Jasra, A., Kantas N.
& Thiery A. On the convergence
of adaptive SMC methods. The previous article is here.

(2014) Jasra,
A. ABC for a class of
time series models.

(2013) Jasra, A.,
Lee, A., Zhang X. & Yau, C.
The alive particle
filter.

(2013) Campanella,
G., De Iorio, M., Jasra, A.
& Chadeau-Hyam, M. The TimeMachine
package for inference on stochastic trees. Manual.

__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 (University of Melbourne,
Maths, Stats & Genetics).

Alex
Beskos (UCL, 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 (Cantab Capital)

Pierre
Del Moral (UNSW, Maths and Statistics).

Nando De Freitas (University
of Oxford, CS).

Maria De Iorio (University College London, Statistics).

Arnaud Doucet (University
of Oxford, Statistics).

Kerry
Gallagher (Universitie Rennes, Geosciences).

Chris
Holmes (

Nikolas Kantas (Imperial College London, Statistics).

Anthony
Lee (University of Warwick, Statistics).

Emma McCoy (Imperial College
London, Statistics)

Giovanni Montana (Kings
College London, Engineering)

David Nott (NUS, Statistics)

Gareth
Peters (University College London, Statistics)

Sumeetpal Singh (University of Cambridge, Engineering).

Dave
Stephens (

Alexandre
Thiery (NUS, Statistics).

Theo Tsagaris
(Tudor Capital).

Nick Whiteley
(University of Bristol, Statistics).

Chris Yau
(Wellcome Trust, Oxford).

Sinan Yildirim
(University of Bristol, Statistics).

Lixian
Zhang (Harbin Inst. Technology, Astronautics).

__Research Students and Post-Docs__

**Post-Docs:
**

**Current:**

Daniel
Paulin (NUS, From July 2014). With Thiery and Nott.

Yan Zhou (NUS,
May 2014-present). With Nott.

Victor Ong (NUS, Jan 2014-present). With Nott.

Adam Persing (UCL, Oct 2013-present). With De Iorio, Beskos & Balding.

**Completed:**

Pierre
Jacob (NUS, Oct 2012-Oct 2013). Now at Oxford.

**Research
Students: **

Please note that I will **not** be taking new PhD students AY 2014-2015.

**Current:**

Y. Xu (NUS, from Aug 2014). Joint with David Nott.

D. Chen (NUS, 2014-Present). Joint with Alex Thiery.

D. Sen (NUS, 2014-Present). Joint with Alex Thiery (main advisor) and Alex Beskos.

E. A. Muzaffer (NUS,
2013-Present). Joint with Alex Beskos.

S. Wang (CSC, 2013-Present).

C. W. Heng (NUS,
2012-Present). 2^{nd} Supervisor, with Hock Peng Chan.

J. Wang (NUS, 2012-Present). Joint with David Nott.

**Completed:**

X. Zhang (IC, 2011-2013), PhD.

Co-Supervisor: Chris Yau.

Now in finance in China.

A.Persing (IC, 2011-2013), PhD.

Co-Supervisor: Dan Crisan
and Leonardo Bottolo.

Now post-doc at UCL (London).

E. Ehrlich (IC, 2011-2013), PhD.

Co-Supervisor: Nikolas Kantas.

Now in data analytics in California.

J. Martin (IC,
2008-2012), PhD.

Co-Supervisor: Emma McCoy.

Now post-doc at UCL (London).

A. Cozzini (IC, 2010-2012),
PhD.

Co-Supervisor: Giovanni Montana.

Now in finance/sports betting in London.

C. Oduneye (IC, 2010-2011),
PhD.

Co-Supervisor: David Stephens.

Now head of credit risk at an investment bank in
London/Singapore.

M. Bottone (IC, 2009-2010),
MPhil.

Co-Supervisor: David Stephens.

Now doing a PhD.

I. Shiekh (IC, 2008-2010),
PhD.

Co-Supervisor: Emma McCoy.

Now an energy analyst in London.

__Teaching__

__NUS__

__ST5219__

In Semester 1 of AY 2014/15 I will teach
ST5219 Bayesian Hierarchical Models. The notes (subject to change) are
available here.

The non-assessed problem sheets are here:

__ST5223__

In Semester 2 of AY 2013/14 I taught ST5223 Statistical
Models: Theory and Applications. The notes are available here.

The non-assessed problem sheets are here:

Previous Exam Papers:

__ST2334__

In Semester 1 of AY 2013/14 I taught ST2334
Probability and Statistics. Notes,
subject to change.

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:

__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 04-02

Department of Statistics and Applied Probability

National University of Singapore

6 Science Drive 2,

Singapore, 117546

e-mail: stajaATnus.edu.sg
(please replace AT with @)

phone: (+65)
66011410