December
2018  M  T  W  T  F  S  S       1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31       

Search the School of Mathematical SciencesPeople matching "Matrix analytic methods"Courses matching "Matrix analytic methods" 
Applications of Quantitative Methods in Finance I Together with MATHS 1009 Introduction to Financial Mathematics I, this course provides an introduction to the basic mathematical concepts and techniques used in finance and business and includes topics from calculus, linear algebra and probability, emphasising their interrelationships and applications to the financial area; introduces students to the use of computers in mathematics; develops problem solving skills with a particular emphasis on financial and business applications. Topics covered are: Calculus: differential and integral calculus with applications; functions of two real variables. Probability: basic concepts, conditional probability; probability distributions and expected value with applications to business and finance.
More about this course... 

Numerical Methods To explore complex systems, physicists, engineers, financiers and mathematicians require computational methods since mathematical models are only rarely solvable algebraically. Numerical methods, based upon sound computational mathematics, are the basic algorithms underpinning computer predictions in modern systems science. Such methods include techniques for simple optimisation, interpolation from the known to the unknown, linear algebra underlying systems of equations, ordinary differential equations to simulate systems, and stochastic simulation under unknown influences. Topics covered are: the mathematical and computational foundations of the numerical approximation and solution of scientific problems; simple optimisation; vectorisation; clustering; polynomial and spline interpolation; pattern recognition; integration and differentiation; solution of large scale systems of linear and nonlinear equations; modelling and solution with sparse equations; explicit schemes to solve ordinary differential equations; random numbers; stochastic system simulation
More about this course... 

Variational Methods and Optimal Control III Many problems of optimisation and control in the sciences and engineering seek to find the shape of a curve or surface satisfying certain conditions so as to maximise or minimise some quantity. For example, shape a yacht hull so as to minimise fluid drag. Variational methods involve an extension of calculus techniques to handle such problems. This course develops an appropriate methodology, illustrated by a variety of physical and engineering problems.
Topics covered are: Classical Calculus of Variations problems such as calculation of the shape of geodesics, the Cantenary, and the Brachystochrone; the derivation and use of the simpler EulerLagrange equations for secondorder (the EulerPoisson equation), multiple dependent variables (Hamilton's equations), and multiple independent variables (minimal surfaces); constrained problems and problems with nonintegral constraints; Euler's finite differences, Ritz's method and Kantorich's method; conservation laws and Noether's theorem; classification of extremals using second variation; optimal control via the Pontryagin Maximum Principle, and its applications to spaceflight calculations.
More about this course... 
Events matching "Matrix analytic methods" 
Stability of timeperiodic flows 15:10 Fri 10 Mar, 2006 :: G08 Mathematics Building University of Adelaide :: Prof. Andrew Bassom, School of Mathematics and
Statistics, University of Western Australia
Timeperiodic shear layers occur naturally in a wide
range of applications from engineering to physiology. Transition to
turbulence in such flows is of practical interest and there have been
several papers dealing with the stability of flows composed of a
steady component plus an oscillatory part with zero mean. In such
flows a possible instability mechanism is associated with the mean
component so that the stability of the flow can be examined using some
sort of perturbationtype analysis. This strategy fails when the mean
part of the flow is small compared with the oscillatory component
which, of course, includes the case when the mean part is precisely
zero.
This difficulty with analytical studies has meant that the stability
of purely oscillatory flows has relied on various numerical
methods. Until very recently such techniques have only ever predicted
that the flow is stable, even though experiments suggest that they do
become unstable at high enough speeds. In this talk I shall expand on
this discrepancy with emphasis on the particular case of the socalled
flat Stokes layer. This flow, which is generated in a deep layer of
incompressible fluid lying above a flat plate which is oscillated in
its own plane, represents one of the few exact solutions of the
NavierStokes equations. We show theoretically that the flow does
become unstable to waves which propagate relative to the basic motion
although the theory predicts that this occurs much later than has been
found in experiments. Reasons for this discrepancy are examined by
reference to calculations for oscillatory flows in pipes and
channels. Finally, we propose some new experiments that might reduce
this disagreement between the theoretical predictions of instability
and practical realisations of breakdown in oscillatory flows. 

A Bivariate Zeroinflated Poisson Regression Model and application to some Dental Epidemiological data 14:10 Fri 27 Oct, 2006 :: G08 Mathematics Building University of Adelaide :: University Prof Sudhir Paul
Data in the form of paired (pretreatment, posttreatment) counts arise in the study of the effects of several treatments after accounting for possible covariate effects. An example of such a data set comes from a dental epidemiological study in Belo Horizonte (the Belo Horizonte caries prevention study) which evaluated various programmes for reducing caries. Also, these data may show extra pairs of zeros than can be accounted for by a simpler model, such as, a bivariate Poisson regression model. In such situations we propose to use a zeroinflated bivariate Poisson regression (ZIBPR) model for the paired (pretreatment, posttreatment) count data. We develop EM algorithm to obtain maximum likelihood estimates of the parameters of the ZIBPR model. Further, we obtain exact Fisher information matrix of the maximum likelihood estimates of the parameters of the ZIBPR model and develop a procedure for testing treatment effects. The procedure to detect treatment effects based on the ZIBPR model is compared, in terms of size, by simulations, with an earlier procedure using a zeroinflated Poisson regression (ZIPR) model of the posttreatment count with the pretreatment count treated as a covariate. The procedure based on the ZIBPR model holds level most effectively. A further simulation study indicates good power property of the procedure based on the ZIBPR model. We then compare our analysis, of the decayed, missing and filled teeth (DMFT) index data from the caries prevention study, based on the ZIBPR model with the analysis using a zeroinflated Poisson regression model in which the pretreatment DMFT index is taken to be a covariate 

A mathematical look at dripping honey 15:10 Fri 4 May, 2007 :: G08 Mathematics Building University of Adelaide :: Dr Yvonne Stokes :: University of Adelaide
Honey dripping from an upturned spoon is an everyday example of a flow that extends and breaks up into drops. Such flows have been of interest for over 300 years, attracting the attention of Plateau and Rayleigh among others. Theoretical understanding has, however, lagged behind experimental investigation, with major progress being made only in the last two decades, driven by industrial applications including inkjet printing, spinning of polymer and glass fibres, blowmoulding of containers, light bulbs and glass tubing, and rheological measurement by fibre extension. Albeit, the exact details of the final stages of breakup are yet to be fully resolved.
An aspect that is relatively unexplored is the evolution of drop and filament from some initial configuration, and the influence of initial conditions on the final breakup. We will consider a drop of very viscous fluid hanging beneath a solid boundary, similar to honey dripping from an upturned spoon, using methods that allow examination of development and behaviour from early time, when a drop and filament begin to form, out to large times when the bulk of the fluid forms a drop at the bottom of a long thin filament which connects it with the upper boundary. The roles of gravity, inertia and surface tension will be examined. 

Flooding in the Sundarbans 15:10 Fri 18 May, 2007 :: G08 Mathematics Building University of Adelaide :: Steve Need
Media...The Sunderbans is a region of deltaic isles formed in the mouth of the Ganges
River on the border between India and Bangladesh. As the largest mangrove
forest in the world it is a world heritage site, however it is also home to
several remote communities who have long inhabited some regions. Many of the
inhabited islands are lowlying and are particularly vulnerable to flooding, a
major hazard of living in the region. Determining suitable levels of
protection to be provided to these communities relies upon accurate assessment
of the flood risk facing these communities. Only recently the Indian
Government commissioned a study into flood risk in the Sunderbans with a view
to determine where flood protection needed to be upgraded.
Flooding due to rainfall is limited due to the relatively small catchment sizes,
so the primary causes of flooding in the Sunderbans are unnaturally high tides,
tropical cyclones (which regularly sweep through the bay of Bengal) or some
combination of the two. Due to the link between tidal anomaly and drops in local
barometric pressure, the two causes of flooding may be highly correlated. I
propose stochastic methods for analysing the flood risk and present the early work
of a case study which shows the direction of investigation. The strategy involves
linking several components; a stochastic approximation to a hydraulic flood
routing model, FARIMA and GARCH models for storm surge and a stochastic model for
cyclone occurrence and tracking. The methods suggested are general and should have
applications in other cyclone affected regions. 

Adaptive Fast Convergence  Towards Optimal Reconstruction Guarantees for Phylogenetic Trees 16:00 Tue 1 Apr, 2008 :: School Board Room :: Schlomo Moran :: Computer Science Department, Technion, Haifa, Israel
One of the central challenges in phylogenetics is to be able to reliably resolve as much of the topology of the evolutionary tree from short taxonsequences. In the past decade much attention has been focused on studying fast converging reconstruction algorithms, which guarantee (w.h.p) correct reconstruction of the entire tree from sequences of nearminimal length (assuming some accepted model of sequence evolution along the tree). The major drawback of these methods is that when the sequences are too short to correctly reconstruct the tree in its entirety, they do not provide any reconstruction guarantee for sufficiently long edges. Specifically, the presence of some very short edges in the model tree may prevent these algorithms from reconstructing even edges of moderate length.
In this talk we present a stronger reconstruction guarantee called "adaptive fast convergence", which provides guarantees for the correct reconstruction of all sufficiently long edges of the original tree. We then present a general technique, which (unlike previous reconstruction techniques) employs dynamic edgecontraction during the reconstruction of the tree. We conclude by demonstrating how this technique is used to achieve adaptive fast convergence. 

Computational Methods for Phase Response Analysis of Circadian Clocks 15:10 Fri 18 Jul, 2008 :: G04 Napier Building University of Adelaide. :: Prof. Linda Petzold :: Dept. of Mechanical and Environmental Engineering, University of California, Santa Barbara
Circadian clocks govern daily behaviors of organisms in all kingdoms of life. In mammals, the master clock resides in the suprachiasmatic nucleus (SCN) of the hypothalamus. It is composed of thousands of neurons, each of which contains a sloppy oscillator  a molecular clock governed by a transcriptional feedback network. Via intercellular signaling, the cell population synchronizes spontaneously, forming a coherent oscillation. This multioscillator is then entrained to its environment by the daily light/dark cycle.
Both at the cellular and tissular levels, the most important feature of the clock is its ability not simply to keep time, but to adjust its time, or phase, to signals. We present the parametric impulse phase response curve (pIPRC), an analytical analog to the phase response curve (PRC) used experimentally. We use the pIPRC to understand both the consequences of intercellular signaling and the light entrainment process. Further, we determine which model components determine the phase response behavior of a single oscillator by using a novel model reduction technique. We reduce the number of model components while preserving the pIPRC and then incorporate the resultant model into a couple SCN tissue model. Emergent properties, including the ability of the population to synchronize spontaneously are preserved in the reduction. Finally, we present some mathematical tools for the study of synchronization in a network of coupled, noisy oscillators.


Free surface Stokes flows with surface tension 15:10 Fri 5 Sep, 2008 :: G03 Napier Building University of Adelaide :: Prof. Darren Crowdy :: Imperial College London
In this talk, we will survey a number of different
free boundary problems involving slow viscous (Stokes) flows
in which surface tension is active on the free boundary. Both steady
and unsteady flows will be considered. Motivating applications
range from industrial processes such as viscous sintering (where
endproducts are formed as a result of the surfacetensiondriven densification
of a compact of smaller particles that are heated in order that they
coalesce) to biological phenomena such as understanding how
organisms swim (i.e. propel themselves) at low Reynolds numbers.
Common to our approach to all these problems will be an
analytical/theoretical treatment of model problems via complex variable methods 
techniques wellknown at infinite Reynolds numbers
but used much less often in the Stokes regime. These model
problems can give helpful insights into the behaviour of the true
physical systems. 

Sloshing in tanks of liquefied natural gas (LNG) vessels 15:10 Wed 22 Apr, 2009 :: Napier LG29 :: Prof. Frederic Dias :: ENS, Cachan
The last scientific conversation I had with Ernie Tuck was on liquid impact. As a matter of fact, we discussed the paper by J.H. Milgram, Journal of Fluid Mechanics 37 (1969), entitled "The motion of a fluid in a cylindrical container with a free surface following vertical impact."
Liquid impact is a key issue in sloshing and in particular in sloshing in tanks of LNG vessels. Numerical simulations of sloshing have been performed by various groups, using various types of numerical methods. In terms of the numerical results, the outcome is often impressive, but the question remains of how relevant these results are when it comes to determining impact pressures. The numerical models are too simplified to reproduce the high variability of the measured pressures. In fact, for the time being, it is not possible to simulate accurately both global and local effects. Unfortunately it appears that local effects predominate over global effects when the behaviour of pressures is considered.
Having said this, it is important to point out that numerical studies can be quite useful to perform sensitivity analyses in idealized conditions such as a liquid mass falling under gravity on top of a horizontal wall and then spreading along the lateral sides. Simple analytical models inspired by numerical results on idealized problems can also be useful to predict trends.
The talk is organized as follows: After a brief introduction on the sloshing problem and on scaling laws, it will be explained to what extent numerical studies can be used to improve our understanding of impact pressures. Results on a liquid mass hitting a wall obtained by a finitevolume code with interface reconstruction as well as results obtained by a simple analytical model will be shown to reproduce the trends of experiments on sloshing.
This is joint work with L. Brosset (GazTransport & Technigaz), J.M. Ghidaglia (ENS Cachan) and J.P. Braeunig (INRIA). 

ChernSimons classes on loop spaces and diffeomorphism groups 13:10 Fri 12 Jun, 2009 :: School Board Room :: Prof Steve Rosenberg :: Boston University
The loop space LM of a Riemannian manifold M comes with a family of Riemannian metrics indexed by a Sobolev parameter. We can construct characteristic classes for LM using the Wodzicki residue instead of the usual matrix trace. The Pontrjagin classes of LM vanish, but the secondary or ChernSimons classes may be nonzero and may distinguish circle actions on M. There are similar results for diffeomorphism groups of manifolds. 

Strong PredictorCorrector Euler Methods for Stochastic Differential Equations 15:10 Fri 19 Jun, 2009 :: LG29 :: Prof. Eckhard Platen :: University of Technology, Sydney
This paper introduces a new class of numerical
schemes for the pathwise approximation of solutions of stochastic
differential equations (SDEs). The proposed family of strong
predictorcorrector Euler methods are designed to handle scenario
simulation of solutions of SDEs. It has the potential to overcome
some of the numerical instabilities that are often experienced
when using the explicit Euler method. This is of importance, for
instance, in finance where martingale dynamics arise for solutions
of SDEs with multiplicative diffusion coefficients. Numerical
experiments demonstrate the improved asymptotic stability
properties of the proposed symmetric predictorcorrector Euler
methods. 

Contemporary frontiers in statistics 15:10 Mon 28 Sep, 2009 :: Badger Labs G31 Macbeth Lectrue :: Prof. Peter Hall :: University of Melbourne
The availability of powerful computing equipment has had a dramatic impact on statistical methods and thinking, changing forever the way data are analysed. New data types, larger quantities of data, and new classes of research problem are all motivating new statistical methods. We shall give examples of each of these issues, and discuss the current and future directions of frontier problems in statistics. 

Modelling and pricing for portfolio credit derivatives 15:10 Fri 16 Oct, 2009 :: MacBeth Lecture Theatre :: Dr Ben Hambly :: University of Oxford
The current financial crisis has been in part precipitated by the
growth of complex credit derivatives and their mispricing. This talk
will discuss some of the background to the `credit crunch', as well as
the models and methods used currently. We will then develop an alternative
view of large basket credit derivatives, as functions of a stochastic
partial differential equation, which addresses some of the shortcomings. 

Analytic torsion for twisted de Rham complexes 13:10 Fri 30 Oct, 2009 :: School Board Room :: Prof Mathai Varghese :: University of Adelaide
We define analytic torsion for the twisted de Rham complex, consisting of differential forms on a compact Riemannian manifold X with coefficients in a flat vector bundle E, with a differential given by a flat connection on E plus a closed odd degree differential form on X. The definition in our case is more complicated than in the case discussed by RaySinger, as it uses pseudodifferential operators. We show that this analytic torsion is independent of the choice of metrics on X and E, establish some basic functorial properties, and compute it in many examples. We also establish the relationship of an invariant version of analytic torsion for Tdual circle bundles with closed 3form flux. This is joint work with Siye Wu. 

Eigenanalysis of fluidloaded compliant panels 15:10 Wed 9 Dec, 2009 :: Santos Lecture Theatre :: Prof Tony Lucey :: Curtin University of Technology
This presentation concerns the fluidstructure interaction (FSI) that occurs between a fluid flow and an arbitrarily deforming flexible boundary considered to be a flexible panel or a compliant coating that comprises the wetted surface of a marine vehicle. We develop and deploy an approach that is a hybrid of computational and theoretical techniques. The system studied is twodimensional and linearised disturbances are assumed. Of particular novelty in the present work is the ability of our methods to extract a full set of fluidstructure eigenmodes for systems that have strong spatial inhomogeneity in the structure of the flexible wall.
We first present the approach and some results of the system in which an ideal, zeropressure gradient, flow interacts with a flexible plate held at both its ends. We use a combination of boundaryelement and finitedifference methods to express the FSI system as a single matrix equation in the interfacial variable. This is then couched in statespace form and standard methods used to extract the system eigenvalues. It is then shown how the incorporation of spatial inhomogeneity in the stiffness of the plate can be either stabilising or destabilising. We also show that adding a further restraint within the streamwise extent of a homogeneous panel can trigger an additional type of hydroelastic instability at low flow speeds. The mechanism for the fluidtostructure energy transfer that underpins this instability can be explained in terms of the pressuresignal phase relative to that of the wall motion and the effect on this relationship of the added wall restraint.
We then show how the idealflow approach can be conceptually extended to include boundarylayer effects. The flow field is now modelled by the continuity equation and the linearised perturbation momentum equation written in velocityvelocity form. The nearwall flow field is spatially discretised into rectangular elements on an Eulerian grid and a variant of the discretevortex method is applied. The entire fluidstructure system can again be assembled as a linear system for a single set of unknowns  the flowfield vorticity and the wall displacements  that admits the extraction of eigenvalues. We then show how stability diagrams for the fullycoupled finite flowstructure system can be assembled, in doing so identifying classes of wallbased or fluidbased and spatiotemporal wave behaviour.


A solution to the GromovVaserstein problem 15:10 Fri 29 Jan, 2010 :: Engineering North N 158 Chapman Lecture Theatre :: Prof Frank Kutzschebauch :: University of Berne, Switzerland
Any matrix in $SL_n (\mathbb C)$ can be written as a product of elementary matrices using the Gauss elimination process. If instead of the field of complex numbers, the entries in the matrix are elements of a more general ring, this becomes a delicate question. In particular, rings of complexvalued functions on a space are interesting cases. A deep result of Suslin gives an affirmative answer for the polynomial ring in $m$ variables in case the size $n$ of the matrix is at least 3. In the topological category, the problem was solved by Thurston and Vaserstein. For holomorphic functions on $\mathbb C^m$, the problem was posed by Gromov in the 1980s. We report on a complete solution to Gromov's problem. A main tool is the OkaGrauertGromov hprinciple in complex analysis. Our main theorem can be formulated as follows: In the absence of obvious topological obstructions, the Gauss elimination process can be performed in a way that depends holomorphically on the matrix. This is joint work with Bj\"orn Ivarsson. 

The fluid mechanics of gels used in tissue engineering 15:10 Fri 9 Apr, 2010 :: Santos Lecture Theatre :: Dr Edward Green :: University of Western Australia
Tissue engineering could be called 'the science of spare parts'.
Although currently in its infancy, its longterm aim is to grow
functional tissues and organs in vitro to replace those which have
become defective through age, trauma or disease. Recent experiments
have shown that mechanical interactions between cells and the materials
in which they are grown have an important influence on tissue
architecture, but in order to understand these effects, we first need to
understand the mechanics of the gels themselves.
Many biological gels (e.g. collagen) used in tissue engineering have a
fibrous microstructure which affects the way forces are transmitted
through the material, and which in turn affects cell migration and other
behaviours. I will present a simple continuum model of gel mechanics,
based on treating the gel as a transversely isotropic viscous material.
Two canonical problems are considered involving thin twodimensional
films: extensional flow, and squeezing flow of the fluid between two
rigid plates. Neglecting inertia, gravity and surface tension, in each
regime we can exploit the thin geometry to obtain a leadingorder
problem which is sufficiently tractable to allow the use of analytical
methods. I discuss how these results could be exploited practically to
determine the mechanical properties of real gels. If time permits, I
will also talk about work currently in progress which explores the
interaction between gel mechanics and cell behaviour. 

Random walk integrals 13:10 Fri 16 Apr, 2010 :: School Board Room :: Prof Jonathan Borwein :: University of Newcastle
Following Pearson in 1905, we study the expected distance of a twodimensional walk in the plane with unit steps in random directionswhat Pearson called a "ramble". A series evaluation and recursions are obtained making it possible to explicitly determine this distance for small number of steps. Closed form expressions for all the moments of a 2step and a 3step walk are given, and a formula is conjectured for the 4step walk. Heavy use is made of the analytic continuation of the underlying integral. 

Mathematical epidemiology with a focus on households 15:10 Fri 23 Apr, 2010 :: Napier G04 :: Dr Joshua Ross :: University of Adelaide
Mathematical models are now used routinely to inform national and global policymakers on issues that threaten human health or which have an adverse impact on the economy. In the first part of this talk I will provide an overview of mathematical epidemiology starting with the classical deterministic model and leading to some of the current challenges. I will then present some of my recently published work which provides computationallyefficient methods for studying a mathematical model incorporating household structure. We will conclude by briefly discussing some "workinprogess" which utilises these methods to address the issues of inference, and mixing pattern and contact structure, for emerging infections. 

Understanding convergence of meshless methods: Vortex methods and smoothed particle hydrodynamics 15:10 Fri 14 May, 2010 :: Santos Lecture Theatre :: A/Prof Lou Rossi :: University of Delaware
Meshless methods such as vortex methods (VMs) and smoothed particle
hydrodynamics (SPH) schemes offer many advantages in fluid flow computations.
Particlebased computations naturally adapt to complex flow geometries
and so provide a high degree of computational efficiency. Also, particle
based methods avoid CFL conditions because flow quantities are
integrated along characteristics. There are many approaches to
improving numerical methods, but one of the most effective routes
is quantifying the error through the direct estimate of residual
quantities. Understanding the residual for particle schemes requires
a different approach than for meshless schemes but the rewards are
significant. In this seminar, I will outline a general approach to
understanding convergence that has been effective in creating high
spatial accuracy vortex methods, and then I will discuss some recent
investigations in the accuracy of diffusion operators used in SPH
computations. Finally, I will provide some sample NavierStokes
computations of high Reynolds number flows using BlobFlow, an open
source implementation of the high precision vortex method. 

A variance constraining ensemble Kalman filter: how to improve forecast using climatic data of unobserved variables 15:10 Fri 28 May, 2010 :: Santos Lecture Theatre :: A/Prof Georg Gottwald :: The University of Sydney
Data assimilation aims to solve one of the fundamental problems ofnumerical weather prediction  estimating the optimal state of the
atmosphere given a numerical model of the dynamics, and sparse, noisy
observations of the system. A standard tool in attacking this
filtering problem is the Kalman filter.
We consider the problem when only partial observations are available.
In particular we consider the situation where the observational space
consists of variables which are directly observable with known
observational error, and of variables of which only their climatic
variance and mean are given. We derive the corresponding Kalman
filter in a variational setting.
We analyze the variance constraining Kalman filter (VCKF) filter for
a simple linear toy model and determine its range of optimal
performance. We explore the variance constraining Kalman filter in an
ensemble transform setting for the Lorenz96 system, and show that
incorporating the information on the variance on some unobservable
variables can improve the skill and also increase the stability of
the data assimilation procedure.
Using methods from dynamical systems theory we then systems where the
unobserved variables evolve deterministically but chaotically on a
fast time scale.
This is joint work with Lewis Mitchell and Sebastian Reich.


On affine BMW algebras 13:10 Fri 25 Jun, 2010 :: Napier 208 :: Prof Arun Ram :: University of Melbourne
I will describe a family of algebras of tangles (which give rise to link invariants
following the methods of ReshetikhinTuraev and Jones) and describe some aspects of their
structure and their representation theory. The main goal will be to explain how to use
universal Verma modules for the symplectic group to compute the representation theory
of affine BMW (BirmanMurakamiWenzl) algebras. 

Adjoint methods for adaptive error control, optimization, and uncertainty quantification 15:10 Fri 16 Jul, 2010 :: Napier G03 :: Dr Varis Carey :: Colorado State University
We give an introduction to the use of adjoint equations (and solutions) for numerical error control and
solution enhancement of PDEs. In addition, the same equations can be used for optimization routines and
uncertainty quantification. We discuss the modification of these methods in the context of
operator splitting and to nonvariational (e.g. finite volume) methods. Finally, we conclude with an application
of the method to the shallow water equations and discuss some of the hurdles that need to be overcome
when extending adjoint methodologies to ocean and atmospheric modeling. 

EynardOrantin invariants and enumerative geometry 13:10 Fri 6 Aug, 2010 :: Ingkarni Wardli B20 (Suite 4) :: Dr Paul Norbury :: University of Melbourne
As a tool for studying enumerative problems in geometry Eynard and Orantin associate multilinear differentials to any plane curve. Their work comes from matrix models but does not require matrix models (for understanding or calculations). In some sense they describe deformations of complex structures of a curve and conjectural relationships to deformations of Kahler structures of an associated object. I will give an introduction to their invariants via explicit examples, mainly to do with the moduli space of Riemann surfaces, in which the plane curve has genus zero. 

Simultaneous confidence band and hypothesis test in generalised varyingcoefficient models 15:05 Fri 10 Sep, 2010 :: Napier LG28 :: Prof Wenyang Zhang :: University of Bath
Generalised varyingcoefficient models (GVC) are very important
models. There are a considerable number of literature addressing these models.
However, most of the existing literature are devoted to the estimation
procedure. In this talk, I will systematically investigate the statistical
inference for GVC, which includes confidence band as well as hypothesis test. I
will show the asymptotic distribution of the maximum discrepancy between the
estimated functional coefficient and the true functional coefficient. I will
compare different approaches for the construction of confidence band and
hypothesis test. Finally, the proposed statistical inference methods are used to
analyse the data from China about contraceptive use there, which leads to some
interesting findings. 

Totally disconnected, locally compact groups 15:10 Fri 17 Sep, 2010 :: Napier G04 :: Prof George Willis :: University of Newcastle
Locally compact groups occur in many branches of mathematics. Their study falls into two cases: connected groups, which occur as automorphisms of smooth structures such as spheres for example; and totally disconnected groups, which occur as automorphisms of discrete structures such as trees. The talk will give an overview of the currently developing structure theory of totally disconnected locally compact groups.
Techniques for analysing totally disconnected groups will be described that correspond to the familiar Lie group methods used to treat connected groups. These techniques played an essential role in the recent solution of a problem raised by R. Zimmer and G. Margulis concerning commensurated subgroups of arithmetic groups.


Statistical physics and behavioral adaptation to Creation's main stimuli: sex and food 15:10 Fri 29 Oct, 2010 :: E10 B17 Suite 1 :: Prof Laurent Seuront :: Flinders University and South Australian Research and Development Institute
Animals typically search for food and mates, while avoiding predators. This is particularly critical for keystone organisms such as intertidal gastropods and copepods (i.e. millimeterscale crustaceans) as they typically rely on nonvisual senses for detecting, identifying and locating mates in their two and threedimensional environments. Here, using stochastic methods derived from the field of nonlinear physics, we provide new insights into the nature (i.e. innate vs. acquired) of the motion behavior of gastropods and copepods, and demonstrate how changes in their behavioral properties can be used to identify the tradeoffs between foraging for food or sex. The gastropod Littorina littorea hence moves according to fractional Brownian motions while foraging for food (in accordance with the fractal nature of food distributions), and switch to Brownian motion while foraging for sex. In contrast, the swimming behavior of the copepod Temora longicornis belongs to the class of multifractal random walks (MRW; i.e. a form of anomalous diffusion), characterized by a nonlinear moment scaling function for distance versus time. This clearly differs from the traditional Brownian and fractional Brownian walks expected or previously detected in animal behaviors. The divergence between MRW and Levy flight and walk is also discussed, and it is shown how copepod anomalous diffusion is enhanced by the presence and concentration of conspecific waterborne signals, and is dramatically increasing malefemale encounter rates. 

Real analytic sets in complex manifolds I: holomorphic closure dimension 13:10 Fri 4 Mar, 2011 :: Mawson 208 :: Dr Rasul Shafikov :: University of Western Ontario
After a quick introduction to real and complex analytic sets,
I will discuss possible notions of complex dimension of real sets, and then discuss a structure theorem for the holomorphic closure dimension which is defined as the dimension of the smallest complex analytic germ containing the real germ. 

Real analytic sets in complex manifolds II: complex dimension 13:10 Fri 11 Mar, 2011 :: Mawson 208 :: Dr Rasul Shafikov :: University of Western Ontario
Given a real analytic set R, denote by A the subset of R of points through which there is a nontrivial complex variety contained in R, i.e., A consists of points in R of positive complex dimension. I will discuss the structure of the set A. 

Bioinspired computation in combinatorial optimization: algorithms and their computational complexity 15:10 Fri 11 Mar, 2011 :: 7.15 Ingkarni Wardli :: Dr Frank Neumann :: The University of Adelaide
Media...Bioinspired computation methods, such as evolutionary algorithms and ant colony
optimization, are being applied successfully to complex engineering and
combinatorial optimization problems. The computational complexity analysis of
this type of algorithms has significantly increased the theoretical
understanding of these successful algorithms. In this talk, I will give an
introduction into this field of research and present some important results
that we achieved for problems from combinatorial optimization. These results
can also be found in my recent textbook "Bioinspired Computation in
Combinatorial Optimization  Algorithms and Their Computational Complexity". 

Modelling of Hydrological Persistence in the MurrayDarling Basin for the Management of Weirs 12:10 Mon 4 Apr, 2011 :: 5.57 Ingkarni Wardli :: Aiden Fisher :: University of Adelaide
The lakes and weirs along the lower Murray River in Australia are aggregated and
considered as a sequence of five reservoirs. A seasonal Markov chain model for
the system will be implemented, and a stochastic dynamic program will be used to
find optimal release strategies, in terms of expected monetary value (EMV), for
the competing demands on the water resource given the stochastic nature of
inflows. Matrix analytic methods will be used to analyse the system further, and
in particular enable the full distribution of first passage times between any
groups of states to be calculated. The full distribution of first passage times
can be used to provide a measure of the risk associated with optimum EMV
strategies, such as conditional value at risk (CVaR). The sensitivity of the
model, and risk, to changing rainfall scenarios will be investigated. The effect
of decreasing the level of discretisation of the reservoirs will be explored.
Also, the use of matrix analytic methods facilitates the use of hidden states to
allow for hydrological persistence in the inflows. Evidence for hydrological
persistence of inflows to the lower Murray system, and the effect of making
allowance for this, will be discussed. 

On parameter estimation in population models 15:10 Fri 6 May, 2011 :: 715 Ingkarni Wardli :: Dr Joshua Ross :: The University of Adelaide
Essential to applying a mathematical model to a realworld application is
calibrating the model to data. Methods for calibrating population models
often become computationally infeasible when the populations size (more generally
the size of the state space) becomes large, or other complexities such as
timedependent transition rates, or sampling error, are present. Here we
will discuss the use of diffusion approximations to perform estimation in several
scenarios, with successively reduced assumptions: (i) under the assumption
of stationarity (the process had been evolving for a very long time with
constant parameter values); (ii) transient dynamics (the assumption of stationarity
is invalid, and thus only constant parameter values may be assumed); and, (iii)
timeinhomogeneous chains (the parameters may vary with time) and accounting
for observation error (a sample of the true state is observed). 

The Cauchy integral formula 12:10 Mon 9 May, 2011 :: 5.57 Ingkarni Wardli :: Stephen Wade :: University of Adelaide
In this talk I will explain a simple method used for calculating the Hilbert transform of an analytic function, and provide some assurance that this isn't a bad thing to do in spite of the somewhat ominous presence of infinite areas. As it turns out this type of integral is not without an application, as will be demonstrated by one application to a problem in fluid mechanics. 

Optimal experimental design for stochastic population models 15:00 Wed 1 Jun, 2011 :: 7.15 Ingkarni Wardli :: Dr Dan Pagendam :: CSIRO, Brisbane
Markov population processes are popular models for studying a wide range of
phenomena including the spread of disease, the evolution of chemical reactions
and the movements of organisms in population networks (metapopulations). Our
ability to use these models effectively can be limited by our knowledge about
parameters, such as disease transmission and recovery rates in an epidemic.
Recently, there has been interest in devising optimal experimental designs for
stochastic models, so that practitioners can collect data in a manner that
maximises the precision of maximum likelihood estimates of the parameters for
these models. I will discuss some recent work on optimal design for a variety
of population models, beginning with some simple oneparameter models where the
optimal design can be obtained analytically and moving on to more complicated
multiparameter models in epidemiology that involve latent states and
nonexponentially distributed infectious periods. For these more complex
models, the optimal design must be arrived at using computational methods and we
rely on a Gaussian diffusion approximation to obtain analytical expressions for
Fisher's information matrix, which is at the heart of most optimality criteria
in experimental design. I will outline a simple crossentropy algorithm that
can be used for obtaining optimal designs for these models. We will also
explore the improvements in experimental efficiency when using the optimal
design over some simpler designs, such as the design where observations are
spaced equidistantly in time. 

Inference and optimal design for percolation and general random graph models (Part I) 09:30 Wed 8 Jun, 2011 :: 7.15 Ingkarni Wardli :: Dr Andrei Bejan :: The University of Cambridge
The problem of optimal arrangement of nodes of a random weighted graph
is discussed in this workshop. The nodes of graphs under study are fixed, but
their edges are random and established according to the so called
edgeprobability function. This function is assumed to depend on the weights
attributed to the pairs of graph nodes (or distances between them) and a
statistical parameter. It is the purpose of experimentation to make inference on
the statistical parameter and thus to extract as much information about it as
possible. We also distinguish between two different experimentation scenarios:
progressive and instructive designs.
We adopt a utilitybased Bayesian framework to tackle the optimal design problem
for random graphs of this kind. Simulation based optimisation methods, mainly
Monte Carlo and Markov Chain Monte Carlo, are used to obtain the solution. We
study optimal design problem for the inference based on partial observations of
random graphs by employing data augmentation technique. We prove that the
infinitely growing or diminishing node configurations asymptotically represent
the worst node arrangements. We also obtain the exact solution to the optimal
design problem for proximity (geometric) graphs and numerical solution for
graphs with threshold edgeprobability functions.
We consider inference and optimal design problems for finite clusters from bond
percolation on the integer lattice $\mathbb{Z}^d$ and derive a range of both
numerical and analytical results for these graphs. We introduce innerouter
plots by deleting some of the lattice nodes and show that the ÃÂÃÂ«mostly populatedÃÂÃÂ
designs are not necessarily optimal in the case of incomplete observations under
both progressive and instructive design scenarios. Some of the obtained results
may generalise to other lattices. 

Inference and optimal design for percolation and general random graph models (Part II) 10:50 Wed 8 Jun, 2011 :: 7.15 Ingkarni Wardli :: Dr Andrei Bejan :: The University of Cambridge
The problem of optimal arrangement of nodes of a random weighted graph
is discussed in this workshop. The nodes of graphs under study are fixed, but
their edges are random and established according to the so called
edgeprobability function. This function is assumed to depend on the weights
attributed to the pairs of graph nodes (or distances between them) and a
statistical parameter. It is the purpose of experimentation to make inference on
the statistical parameter and thus to extract as much information about it as
possible. We also distinguish between two different experimentation scenarios:
progressive and instructive designs.
We adopt a utilitybased Bayesian framework to tackle the optimal design problem
for random graphs of this kind. Simulation based optimisation methods, mainly
Monte Carlo and Markov Chain Monte Carlo, are used to obtain the solution. We
study optimal design problem for the inference based on partial observations of
random graphs by employing data augmentation technique. We prove that the
infinitely growing or diminishing node configurations asymptotically represent
the worst node arrangements. We also obtain the exact solution to the optimal
design problem for proximity (geometric) graphs and numerical solution for
graphs with threshold edgeprobability functions.
We consider inference and optimal design problems for finite clusters from bond
percolation on the integer lattice $\mathbb{Z}^d$ and derive a range of both
numerical and analytical results for these graphs. We introduce innerouter
plots by deleting some of the lattice nodes and show that the ÃÂÃÂÃÂÃÂ«mostly populatedÃÂÃÂÃÂÃÂ
designs are not necessarily optimal in the case of incomplete observations under
both progressive and instructive design scenarios. Some of the obtained results
may generalise to other lattices. 

Spectra alignment/matching for the classification of cancer and control patients 12:10 Mon 8 Aug, 2011 :: 5.57 Ingkarni Wardli :: Mr Tyman Stanford :: University of Adelaide
Proteomic timeofflight mass spectrometry produces a spectrum based on the peptides (chains of amino acids) in each patientâs serum sample. The spectra contain data points for an xaxis (peptide weight) and a yaxis (peptide frequency/count/intensity). It is our end goal to differentiate cancer (and subtypes) and control patients using these spectra. Before we can do this, peaks in these data must be found and common peptides to different spectra must be found. The data are noisy because of biotechnological variation and calibration error; data points for different peptide weights may in fact be same peptide. An algorithm needs to be employed to find common peptides between spectra, as performing alignment âby handâ is almost infeasible. We borrow methods suggested in the literature by metabolomic gas chromatographymass spectrometry and extend the methods for our purposes. In this talk I will go over the basic tenets of what we hope to achieve and the process towards this.


Laplace's equation on multiplyconnected domains 12:10 Mon 29 Aug, 2011 :: 5.57 Ingkarni Wardli :: Mr Hayden Tronnolone :: University of Adelaide
Various physical processes take place on multiplyconnected domains
(domains with some number of 'holes'), such as the stirring of a fluid
with paddles or the extrusion of material from a die. These systems may
be described by partial differential equations (PDEs). However, standard
numerical methods for solving PDEs are not wellsuited to such examples:
finite difference methods are difficult to implement on
multiplyconnected domains, especially when the boundaries are irregular
or moving, while finite element methods are computationally expensive.
In this talk I will describe a fast and accurate numerical method for
solving certain PDEs on twodimensional multiplyconnected domains,
considering Laplace's equation as an example. This method takes
advantage of complex variable techniques which allow the solution to be
found with spectral accuracy provided the boundary data is smooth. Other
advantages over traditional numerical methods will also be discussed. 

Twisted Morava Ktheory 13:10 Fri 9 Sep, 2011 :: 7.15 Ingkarni Wardli :: Dr Craig Westerland :: University of Melbourne
Morava's extraordinary Ktheories K(n) are a family of generalized cohomology theories which behave in some ways like Ktheory (indeed, K(1) is mod 2 Ktheory). Their construction exploits Quillen's description of cobordism in terms of formal group laws and LubinTate's methods in class field theory for constructing abelian extensions of number fields. Constructed from homotopytheoretic methods, they do not admit a geometric description (like deRham cohomology, Ktheory, or cobordism), but are nonetheless subtle, computable invariants of topological spaces. In this talk, I will give an introduction to these theories, and explain how it is possible to define an analogue of twisted Ktheory in this setting. Traditionally, Ktheory is twisted by a threedimensional cohomology class; in this case, K(n) admits twists by (n+2)dimensional classes. This work is joint with Hisham Sati. 

Mathematical modelling of lobster populations in South Australia 12:10 Mon 12 Sep, 2011 :: 5.57 Ingkarni Wardli :: Mr John Feenstra :: University of Adelaide
Just how many lobsters are there hanging around the South Australian coastline? How is this number changing over time? What is the demographic breakdown of this number? And what does it matter? Find out the answers to these questions in my upcoming talk. I will provide a brief flavour of the kinds of quantitative methods involved, showcasing relevant applications of regression, population modelling, estimation, as well as simulation. A product of these analyses are biological performance indicators which are used by government to help decide on fishery controls such as yearly total allowable catch quotas. This assists in maintaining the sustainability of the fishery and hence benefits both the fishers and the lobsters they catch. 

Estimating transmission parameters for the swine flu pandemic 15:10 Fri 23 Sep, 2011 :: 7.15 Ingkarni Wardli :: Dr Kathryn Glass :: Australian National University
Media...Following the onset of a new strain of influenza with pandemic potential, policy makers need specific advice on how fast the disease is spreading, who is at risk, and what interventions are appropriate for slowing transmission. Mathematical models play a key role in comparing interventions and identifying the best response, but models are only as good as the data that inform them. In the early stages of the 2009 swine flu outbreak, many researchers estimated transmission parameters  particularly the reproduction number  from outbreak data. These estimates varied, and were often biased by data collection methods, misclassification of imported cases or as a result of early stochasticity in case numbers. I will discuss a number of the pitfalls in achieving good quality parameter estimates from early outbreak data, and outline how best to avoid them.
One of the early indications from swine flu data was that children were disproportionately responsible for disease spread. I will introduce a new method for estimating agespecific transmission parameters from both outbreak and seroprevalence data. This approach allows us to take account of empirical data on human contact patterns, and highlights the need to allow for asymmetric mixing matrices in modelling disease transmission between age groups. Applied to swine flu data from a number of different countries, it presents a consistent picture of higher transmission from children. 

Estimating disease prevalence in hidden populations 14:05 Wed 28 Sep, 2011 :: B.18 Ingkarni Wardli :: Dr Amber Tomas :: The University of Oxford
Estimating disease prevalence in "hidden" populations such as injecting
drug users or men who have sex with men is an important public health
issue. However, traditional designbased estimation methods are
inappropriate because they assume that a list of all members of the
population is available from which to select a sample. Respondent Driven
Sampling (RDS) is a method developed over the last 15 years for sampling
from hidden populations. Similarly to snowball sampling, it leverages the
fact that members of hidden populations are often socially connected to
one another. Although RDS is now used around the world, there are several
common population characteristics which are known to cause estimates
calculated from such samples to be significantly biased. In this talk I'll
discuss the motivation for RDS, as well as some of the recent developments
in methods of estimation. 

Likelihoodfree Bayesian inference: modelling drug resistance in Mycobacterium tuberculosis 15:10 Fri 21 Oct, 2011 :: 7.15 Ingkarni Wardli :: Dr Scott Sisson :: University of New South Wales
Media...A central pillar of Bayesian statistical inference is Monte Carlo integration, which is based on obtaining random samples from the posterior distribution. There are a number of standard ways to obtain these samples, provided that the likelihood function can be numerically evaluated. In the last 10 years, there has been a substantial push to develop methods that permit Bayesian inference in the presence of computationally intractable likelihood functions. These methods, termed ``likelihoodfree'' or approximate Bayesian computation (ABC), are now being applied extensively across many disciplines.
In this talk, I'll present a brief, nontechnical overview of the ideas behind likelihoodfree methods. I'll motivate and illustrate these ideas through an analysis of the epidemiological fitness cost of drug resistance in Mycobacterium tuberculosis. 

Stability analysis of nonparallel unsteady flows via separation of variables 15:30 Fri 18 Nov, 2011 :: 7.15 Ingkarni Wardli :: Prof Georgy Burde :: BenGurion University
Media...The problem of variables separation in the linear stability
equations, which govern the disturbance behavior in viscous
incompressible fluid flows, is discussed.
Stability of some unsteady nonparallel threedimensional flows (exact
solutions of the NavierStokes equations)
is studied via separation of variables using a semianalytical, seminumerical approach.
In this approach, a solution with separated variables is defined in a new coordinate system which is sought together with the solution form. As the result, the linear stability problems are reduced to eigenvalue problems for ordinary differential equations which can be solved numerically.
In some specific cases, the eigenvalue
problems can be solved analytically. Those unique examples of exact
(explicit) solution of the nonparallel unsteady flow stability
problems provide a very useful test for methods used in the
hydrodynamic stability theory. Exact solutions of the stability problems for some stagnationtype flows are presented. 

Plurisubharmonic subextensions as envelopes of disc functionals 13:10 Fri 2 Mar, 2012 :: B.20 Ingkarni Wardli :: A/Prof Finnur Larusson :: University of Adelaide
I will describe new joint work with Evgeny Poletsky. We prove a disc formula for the largest plurisubharmonic subextension of an upper semicontinuous function on a domain $W$ in a Stein manifold to a larger domain $X$ under suitable conditions on $W$ and $X$. We introduce a related equivalence relation on the space of analytic discs in $X$ with boundary in $W$. The quotient is a complex manifold with a local biholomorphism to $X$, except it need not be Hausdorff. We use our disc formula to generalise Kiselman's minimum principle. We show that his infimum function is an example of a plurisubharmonic subextension. 

Are Immigrants Discriminated in the Australian Labour Market? 12:10 Mon 7 May, 2012 :: 5.57 Ingkarni Wardli :: Ms Wei Xian Lim :: University of Adelaide
Media...In this talk, I will present what I did in my honours project, which was to determine if immigrants, categorised as immigrants from English speaking countries and NonEnglish speaking countries, are discriminated in the Australian labour market. To determine if discrimination exists, a decomposition of the wage function is applied and analysed via regression analysis. Two different methods of estimating the unknown parameters in the wage function will be discussed:
1. the Ordinary Least Square method,
2. the Quantile Regression method.
This is your rare chance of hearing me talk about nonnanomathematics related stuff! 

The classification of Dynkin diagrams 12:10 Mon 21 May, 2012 :: 5.57 Ingkarni Wardli :: Mr Alexander Hanysz :: University of Adelaide
Media...The idea of continuous symmetry is often described in mathematics via Lie groups. These groups can be classified by their root systems: collections of vectors satisfying certain symmetry properties. The root systems are described in a concise way by Dynkin diagrams, and it turns out, roughly speaking, that there are only seven possible shapes for a Dynkin diagram.
In this talk I'll describe some simple examples of Lie groups, explain what a root system is, and show how a Dynkin diagram encodes this information. Then I'll give a very brief sketch of the methods used to classify Dynkin diagrams. 

Enhancing the Jordan canonical form 15:10 Fri 1 Jun, 2012 :: B.21 Ingkarni Wardli :: A/Prof Anthony Henderson :: The University of Sydney
Media...In undergraduate linear algebra, we teach the Jordan canonical form theorem:
that every similarity class of n x n complex matrices contains a special
matrix which is blockdiagonal with each block having a very simple form (a single eigenvalue repeated down the diagonal,
ones on the superdiagonal, and zeroes elsewhere). This is of course very
useful for matrix calculations.
After explaining some of the general context of this result,
I will focus on a case which, despite its close proximity to the Jordan
canonical form theorem, has only recently been worked out: the classification
of pairs of a vector and a matrix.


IGA Workshop: Dendroidal sets 14:00 Tue 12 Jun, 2012 :: Ingkarni Wardli B17 :: Dr Ittay Weiss :: University of the South Pacific
Media...A series of four 2hour lectures by Dr. Ittay Weiss.
The theory of dendroidal sets was introduced by Moerdijk and Weiss in 2007 in the study of homotopy operads in algebraic topology. In the five years that have past since then several fundamental and highly nontrivial results were established. For instance, it was established that dendroidal sets provide models for homotopy operads in a way that extends the JoyalLurie approach to homotopy categories. It can be shown that dendroidal sets provide new models in the study of nfold loop spaces. And it is very recently shown that dendroidal sets model all connective spectra in a way that extends the modeling of certain spectra by Picard groupoids.
The aim of the lecture series will be to introduce the concepts mentioned above, present the elementary theory, and understand the scope of the results mentioned as well as discuss the potential for further applications. Sources for the course will include the article "From Operads to Dendroidal Sets" (in the AMS volume on mathematical foundations of quantum field theory (also on the arXiv)) and the lecture notes by Ieke Moerdijk "simplicial methods for operads and algebraic geometry" which resulted from an advanced course given in Barcelona 3 years ago.
No prior knowledge of operads will be assumed nor any knowledge of homotopy theory that is more advanced then what is required for the definition of the fundamental group. The basics of the language of presheaf categories will be recalled quickly and used freely. 

Comparison of spectral and wavelet estimators of transfer function for linear systems 12:10 Mon 18 Jun, 2012 :: B.21 Ingkarni Wardli :: Mr Mohd Aftar Abu Bakar :: University of Adelaide
Media...We compare spectral and wavelet estimators of the response amplitude operator (RAO) of a linear system, with various input signals and added noise scenarios. The comparison is based on a model of a heaving buoy wave energy device (HBWED), which oscillates vertically as a single mode of vibration linear system.
HBWEDs and other single degree of freedom wave energy devices such as the oscillating wave surge convertors (OWSC) are currently deployed in the ocean, making single degree of freedom wave energy devices important systems to both model and analyse in some detail. However, the results of the comparison relate to any linear system.
It was found that the wavelet estimator of the RAO offers no advantage over the spectral estimators if both input and response time series data are noise free and long time series are available. If there is noise on only the response time series, only the wavelet estimator or the spectral estimator that uses the crossspectrum of the input and response signals in the numerator should be used. For the case of noise on only the input time series, only the spectral estimator that uses the crossspectrum in the denominator gives a sensible estimate of the RAO. If both the input and response signals are corrupted with noise, a modification to both the input and response spectrum estimates can provide a good estimator of the RAO. However, a combination of wavelet and spectral methods is introduced as an alternative RAO estimator.
The conclusions apply for autoregressive emulators of sea surface elevation, impulse, and pseudorandom binary sequences (PRBS) inputs. However, a wavelet estimator is needed in the special case of a chirp input where the signal has a continuously varying frequency. 

Ktheory and unbounded Fredholm operators 13:10 Mon 9 Jul, 2012 :: Ingkarni Wardli B19 :: Dr Jerry Kaminker :: University of California, Davis
There are several ways of viewing elements of K^1(X). One
of these is via families of unbounded selfadjoint Fredholm operators on X. Each operator will have discrete spectrum, with infinitely many positive and negative eigenvalues of finite multiplicity. One can associate to such a family a geometric object, its graph, and the Chern character and other invariants of the family can be studied from this perspective. By restricting the dimension of the eigenspaces one may sometimes use algebraic topology to completely determine the family up to equivalence. This talk will describe the general framework and some applications to families on lowdimensional manifolds
where the methods work well. Various notions related to spectral flow, the index gerbe and Berry phase play roles which will be discussed. This is joint work with Ron Douglas.


Inquirybased learning: yesterday and today 15:30 Mon 9 Jul, 2012 :: Ingkarni Wardli B19 :: Prof Ron Douglas :: Texas A&M University
Media...The speaker will report on a project to develop and promote approaches to mathematics instruction closely related to the Moore method  methods which are called inquirybased learning  as well as on his personal experience of the Moore method. For background, see the speaker's article in the May 2012 issue of the Notices of the American Mathematical Society. To download the article, click on "Media" above. 

2012 AMSISSAI Lecture: Approximate Bayesian computation (ABC): advances and limitations 11:00 Fri 13 Jul, 2012 :: Engineering South S112 :: Prof Christian Robert :: Universite ParisDauphine
Media...The lack of closed form likelihoods has been the bane of Bayesian computation for many years and, prior to the introduction of MCMC methods, a strong impediment to the propagation of the Bayesian paradigm. We are now facing models where an MCMC completion of the model towards closedform likelihoods seems unachievable and where a further degree of approximation appears unavoidable. In this talk, I will present the motivation for approximative Bayesian computation (ABC) methods, the consistency results already available, the various Monte Carlo implementations found in the current literature, as well as the inferential, rather than computational, challenges set by these methods. A recent advance based on empirical likelihood will also be discussed. 

Knot Theory 12:10 Mon 10 Sep, 2012 :: B.21 Ingkarni Wardli :: Mr Konrad Pilch :: University of Adelaide
Media...The ancient Chinese used it, the Celts had this skill in spades, it was a big skill of seafarers and pirates, and even now we need it if only to be able to wear shoes! This talk will be about Knot Theory. Knot theory has a colourful and interesting past and I will touch on the why, the what and the when of knots in mathematics. I shall also discuss the major problems concerning knots including the different methods of classification of knots, the unresolved questions about knots, and why have they even been studied. It will be a thorough immersion that will leave you knotted! 

Krylov Subspace Methods or: How I Learned to Stop Worrying and Love GMRes 12:10 Mon 17 Sep, 2012 :: B.21 Ingkarni Wardli :: Mr David Wilke :: University of Adelaide
Media...Many problems within applied mathematics require the solution of a linear system of equations. For instance, models of arterial umbilical blood flow are obtained through a finite element approximation, resulting in a linear, n x n system. For small systems the solution is (almost) trivial, but what happens when n is large? Say, n ~ 10^6? In this case matrix inversion is expensive (read: completely impractical) and we seek approximate solutions in a reasonable time.
In this talk I will discuss the basic theory underlying Krylov subspace methods; a class of nonstationary iterative methods which are currently the methodsofchoice for large, sparse, linear systems. In particular I will focus on the method of Generalised Minimum RESiduals (GMRes), which is of the most popular for nonsymmetric systems. It is hoped that through this presentation I will convince you that a) solving linear systems is not necessarily trivial, and that b) my lack of any tangible results is not (entirely) a result of my own incompetence. 

Complex analysis in low Reynolds number hydrodynamics 15:10 Fri 12 Oct, 2012 :: B.20 Ingkarni Wardli :: Prof Darren Crowdy :: Imperial College London
Media...It is a wellknown fact that the methods of complex analysis provide great advantage
in studying physical problems involving a harmonic field satisfying Laplace's equation.
One example is in ideal fluid mechanics (infinite Reynolds number)
where the absence of viscosity, and the
assumption of zero vorticity, mean that it is possible to introduce a socalled
complex potential  an analytic function from which all physical quantities of
interest can be inferred.
In the opposite limit of zero Reynolds number flows which are slow and viscous
and the governing fields are not harmonic
it is much less common to employ the methods of complex analysis
even though they continue to be relevant in certain circumstances.
This talk will give an overview of a variety of problems involving slow viscous Stokes
flows where complex analysis can be usefully employed to gain theoretical
insights. A number of example problems will be considered including
the locomotion of lowReynoldsnumber microorganisms and microrobots,
the friction properties of superhydrophobic surfaces in microfluidics and
problems of viscous sintering and the manufacture of microstructured optic fibres (MOFs). 

Twisted analytic torsion and adiabatic limits 13:10 Wed 5 Dec, 2012 :: Ingkarni Wardli B17 :: Mr Ryan Mickler :: University of Adelaide
We review MathaiWu's recent extension of RaySinger analytic torsion to supercomplexes. We explore some new results relating these two torsions, and how we can apply the adiabatic spectral sequence due to Forman and Farber's analytic deformation theory to compute some spectral invariants of the complexes involved, answering some questions that were posed in MathaiWu's paper.


Twistor theory and the harmonic hull 15:10 Fri 8 Mar, 2013 :: B.18 Ingkarni Wardli :: Prof Michael Eastwood :: Australian National University
Media...Harmonic functions are realanalytic and so automatically extend as functions of complex variables. But how far do they extend? This question may be answered by twistor theory, the Penrose transform, and associated conformal geometry. Nothing will be supposed about such matters: I shall base the constructions on an elementary yet mysterious formula of Bateman from 1904. This is joint work with Feng Xu. 

How fast? Bounding the mixing time of combinatorial Markov chains 15:10 Fri 22 Mar, 2013 :: B.18 Ingkarni Wardli :: Dr Catherine Greenhill :: University of New South Wales
Media...A Markov chain is a stochastic process which is "memoryless",
in that the next state of the chain depends only on the current state,
and not on how it got there. It is a classical result that an ergodic
Markov chain has a unique stationary distribution.
However, classical theory does not provide any information on the rate of
convergence to stationarity. Around 30 years ago, the mixing time of
a Markov chain was introduced to measure the number of steps required
before the distribution of the chain is within some small distance of
the stationary distribution. One reason why this is important is that
researchers in areas such as physics and biology use Markov chains to
sample from large sets of interest. Rigorous bounds on the mixing time
of their chain allows these researchers to have confidence in their results.
Bounding the mixing time of combinatorial Markov chains can be a challenge, and there are only a few approaches available. I will discuss the main methods and give examples for each (with pretty pictures). 

What in the world is a chebfun? 12:10 Mon 15 Apr, 2013 :: B.19 Ingkarni Wardli :: Hayden Tronnolone :: University of Adelaide
Media...Good question. Many functions encountered in practice can be wellapproximated by a linear combination of Chebyshev polynomials, which then allows the use of some powerful numerical techniques. I will give a very brief overview of the theory behind some of these methods, demonstrate how they may be implemented using the MATLAB package known as Chebfun, and answer the question posed in the title along the way.
No knowledge of approximation theory or MATLAB is required, however, you will need to accept the transliteration "Chebyshev". 

Models of cellextracellular matrix interactions in tissue engineering 15:10 Fri 3 May, 2013 :: B.18 Ingkarni Wardli :: Dr Ed Green :: University of Adelaide
Media...Tissue engineers hope in future to be able to grow functional tissues in vitro to replace those that are damaged by injury, disease, or simple wear and tear. They use cell culture methods, such as seeding cells within collagen gels, that are designed to mimic the cells' environment in vivo. Amongst other factors, it is clear that mechanical interactions between cells and the extracellular matrix (ECM) in which they reside play an important role in tissue development. However, the mechanics of the ECM is complex, and at present, its role is only partly understood. In this talk, I will present mathematical models of some simple cellECM interaction problems, and show how they can be used to gain more insight into the processes that regulate tissue development. 

Markov decision processes and interval Markov chains: what is the connection? 12:10 Mon 3 Jun, 2013 :: B.19 Ingkarni Wardli :: Mingmei Teo :: University of Adelaide
Media...Markov decision processes are a way to model processes which involve some sort of decision making and interval Markov chains are a way to incorporate uncertainty in the transition probability matrix. How are these two concepts related? In this talk, I will give an overview of these concepts and discuss how they relate to each other. 

Khomology and the quantization commutes with reduction problem 12:10 Fri 5 Jul, 2013 :: 7.15 Ingkarni Wardli :: Prof Nigel Higson :: Pennsylvania State University
The quantization commutes with reduction problem for Hamiltonian actions of compact Lie groups was solved by Meinrenken in the mid1990s using geometric techniques, and solved again shortly afterwards by Tian and Zhang using analytic methods. In this talk I shall outline some of the close links that exist between the problem, the two solutions, and the geometric and analytic versions of Khomology theory that are studied in noncommutative geometry. I shall try to make the case for Khomology as a useful conceptual framework for the solutions and (at least some of) their various generalizations. 

The Hamiltonian Cycle Problem and Markov Decision Processes 15:10 Fri 2 Aug, 2013 :: B.18 Ingkarni Wardli :: Prof Jerzy Filar :: Flinders University
Media...We consider the famous Hamiltonian cycle problem (HCP) embedded in a Markov decision process (MDP). More specifically, we consider a moving object on a graph G where, at each vertex, a controller may select an arc emanating from that vertex according to a probabilistic decision rule. A stationary policy is simply a control where these decision rules are time invariant. Such a policy induces a Markov chain on the vertices of the graph. Therefore, HCP is equivalent to a search for a stationary policy that induces a 01 probability transition matrix whose nonzero entries trace out a Hamiltonian cycle in the graph. A consequence of this embedding is that we may consider the problem over a number of, alternative, convex  rather than discrete  domains. These include: (a) the space of stationary policies, (b) the more restricted but, very natural, space of doubly stochastic matrices induced by the graph, and (c) the associated spaces of socalled "occupational measures". This approach to the HCP has led to both theoretical and algorithmic approaches to the underlying HCP problem. In this presentation, we outline a selection of results generated by this line of research. 

What is Tight Clustering? 12:10 Mon 12 Aug, 2013 :: B.19 Ingkarni Wardli :: Chris Davies :: University of Adelaide
Media...Most clustering methods partition the observations in such a way that those in the same cluster are more similar to each other than they are to observations in different clusters. However, in some situations you might not want to assign all observations into clusters. That is, you might prefer to consider some subjects to have characteristics so dissimilar from others that they are not assigned to any cluster. In this seminar I will describe an algorithm that can be used to assign some observations into tight and stable clusters, while leaving some observations unassigned. 

Ktheory and solid state physics 12:10 Fri 13 Sep, 2013 :: Ingkarni Wardli B19 :: Dr Keith Hannabuss :: Balliol College, Oxford
More than 50 years ago Dyson showed that there is a ninefold classification of random matrix models, the classes of which are each associated with Riemannian symmetric spaces. More recently it was realised that a related argument enables one to classify the insulating properties of fermionic systems (with the addition of an extra class to give 10 in all), and can be described using Ktheory. In this talk I shall give a survey of the ideas, and a brief outline of work with Guo Chuan Thiang. 

Classification Using Censored Functional Data 15:10 Fri 18 Oct, 2013 :: B.18 Ingkarni Wardli :: A/Prof Aurore Delaigle :: University of Melbourne
Media...We consider classification of functional data. This problem has received a lot of attention in the literature in the case where the curves are all observed on the same interval. A difficulty in applications is that the functional curves can be supported on quite different intervals, in which case standard methods of analysis cannot be used. We are interested in constructing classifiers for curves of this type. More precisely, we consider classification of functions supported on a compact interval, in cases where the training sample consists of functions observed on other intervals, which may differ among the training curves.
We propose several methods, depending on whether or not the observable intervals
overlap by a significant amount. In the case where these intervals differ a lot, our procedure involves extending the curves outside the interval where they were observed. We suggest a new nonparametric approach for doing this.
We also introduce flexible ways of combining potential differences in shapes of the curves from different populations, and potential differences between the endpoints of
the intervals where the curves from each population are observed. 

Developing Multiscale Methodologies for Computational Fluid Mechanics 12:10 Mon 11 Nov, 2013 :: B.19 Ingkarni Wardli :: Hammad Alotaibi :: University of Adelaide
Media...Recently the development of multiscale methods is one of the most fertile research areas in mathematics, physics, engineering and computer science. The need for multiscale modeling comes usually from the fact that the available macroscale models are not accurate enough, and the microscale models are not efficient enough. By combining both viewpoints, one hopes to arrive at a reasonable compromise between accuracy and efficiency.
In this seminar I will give an overview of the recent efforts on developing multiscale methods such as patch dynamics scheme which is used to address an important class of time dependent multiscale problems. 

Holomorphic null curves and the conformal CalabiYau problem 12:10 Tue 28 Jan, 2014 :: Ingkarni Wardli B20 :: Prof Franc Forstneric :: University of Ljubljana
Media...I shall describe how methods of complex analysis can be used to give new results on the conformal CalabiYau problem concerning the existence of bounded metrically complete minimal surfaces in real Euclidean 3space R^3. We shall see in particular that every bordered Riemann surface admits a proper complete holomorphic immersion into the ball of C^2, and a proper complete embedding as a
holomorphic null curve into the ball of C^3. Since the real and the imaginary parts of a holomorphic null curve in C^3 are conformally immersed minimal surfaces in R^3, we obtain a bounded complete conformal minimal immersion of any bordered Riemann surface into R^3. The main advantage of our methods, when compared to the existing ones in the literature, is that we do not need to change the conformal type of the Riemann surface. (Joint work with A. Alarcon, University of Granada.)


CARRYING CAPACITY FOR FINFISH AQUACULTURE IN SPENCER GULF: RAPID ASSESSMENT USING HYDRODYNAMIC AND NEARFIELD, SEMI  ANALYTIC SOLUTIONS 15:10 Fri 11 Apr, 2014 :: 5.58 Ingkarni Wardli :: Associate Professor John Middleton :: SARDI Aquatic Sciences and University of Adelaide
Aquaculture farming involves daily feeding of finfish and a subsequent excretion of nutrients into Spencer Gulf. Typically, finfish farming is done in six or so 50m diameter cages and over 600m X 600m lease sites. To help regulate the industry, it is desired that the finfish feed rates and the associated nutrient flux into the ocean are determined such that the maximum nutrient concentration c does not exceed a prescribed value (say cP) for ecosystem health. The prescribed value cP is determined by guidelines from the E.P.A. The concept is known as carrying capacity since limiting the feed rates limits the biomass of the farmed finfish.
Here, we model the concentrations that arise from a constant input flux (F) of nutrients in a source region (the cage or lease) using the (depthaveraged) two dimensional, advection diffusion equation for constant and sinusoidal (tides) currents. Application of the divergence theorem to this equation results in a new scale estimate of the maximum flux F (and thus feed rate) that is given by
F= cP /T* (1)
where cP is the maximum allowed concentration and T* is a new time scale of âflushingâ that involves both advection and diffusion. The scale estimate (1) is then shown to compare favourably with mathematically exact solutions of the advection diffusion equation that are obtained using Greenâs functions and Fourier transforms. The maximum nutrient flux and associated feed rates are then estimated everywhere in Spencer Gulf through the development and validation of a hydrodynamic model. The model provides seasonal averages of the mean currents U and horizontal diffusivities KS that are needed to estimate T*. The diffusivities are estimated from a shear dispersal model of the tides which are very large in the gulf. The estimates have been provided to PIRSA Fisheries and Aquaculture to assist in the sustainable expansion of finfish aquaculture.


Bayesian Indirect Inference 12:10 Mon 14 Apr, 2014 :: B.19 Ingkarni Wardli :: Brock Hermans :: University of Adelaide
Media...Bayesian likelihoodfree methods saw the resurgence of Bayesian statistics through the use of computer sampling techniques. Since the resurgence, attention has focused on socalled 'summary statistics', that is, ways of summarising data that allow for accurate inference to be performed. However, it is not uncommon to find data sets in which the summary statistic approach is not sufficient.
In this talk, I will be summarising some of the likelihoodfree methods most commonly used (don't worry if you've never seen any Bayesian analysis before), as well as looking at Bayesian Indirect Likelihood, a new way of implementing Bayesian analysis which combines new inference methods with some of the older computational algorithms. 

Outlier removal using the Bayesian information criterion for groupbased trajectory modelling 12:10 Mon 28 Apr, 2014 :: B.19 Ingkarni Wardli :: Chris Davies :: University of Adelaide
Media...Attributes measured longitudinally can be used to define discrete paths of measurements, or trajectories, for each individual in a given population. Groupbased trajectory modelling methods can be used to identify subgroups of trajectories within a population, such that trajectories that are grouped together are more similar to each other than to trajectories in distinct groups. Existing methods generally allocate every individual trajectory into one of the estimated groups. However this does not allow for the possibility that some individuals may be following trajectories so different from the rest of the population that they should not be included in a groupbased trajectory model. This results in these outlying trajectories being treated as though they belong to one of the groups, distorting the estimated trajectory groups and any subsequent analyses that use them.
We have developed an algorithm for removing outlying trajectories based on the maximum change in Bayesian information criterion (BIC) due to removing a single trajectory. As well as deciding which trajectory to remove, the number of groups in the model can also change. The decision to remove an outlying trajectory is made by comparing the loglikelihood contributions of the observations to those of simulated samples from the estimated groupbased trajectory model. In this talk the algorithm will be detailed and an application of its use will be demonstrated. 

Networkbased approaches to classification and biomarker identification in metastatic melanoma 15:10 Fri 2 May, 2014 :: B.21 Ingkarni Wardli :: Associate Professor Jean Yee Hwa Yang :: The University of Sydney
Media...Finding prognostic markers has been a central question in much of current research in medicine and biology. In the last decade, approaches to prognostic prediction within a genomics setting are primarily based on changes in individual genes / protein. Very recently, however, network based approaches to prognostic prediction have begun to emerge which utilize interaction information between genes. This is based on the believe that largescale molecular interaction networks are dynamic in nature and changes in these networks, rather than changes in individual genes/proteins, are often drivers of complex diseases such as cancer.
In this talk, I use data from stage III melanoma patients provided by Prof. Mann from Melanoma Institute of Australia to discuss how network information can be utilize in the analysis of gene expression analysis to aid in biological interpretation. Here, we explore a number of novel and previously published networkbased prediction methods, which we will then compare to the common singlegene and geneset methods with the aim of identifying more biologically interpretable biomarkers in the form of networks. 

Computing with groups 15:10 Fri 30 May, 2014 :: B.21 Ingkarni Wardli :: Dr Heiko Dietrich :: Monash University
Media...Groups are algebraic structures which show up in many branches of
mathematics and other areas of science; Computational Group Theory is
on the cutting edge of pure research in group theory and its interplay
with computational methods.
In this talk, we consider a practical aspect
of Computational Group Theory: how to represent a group in a computer,
and how to work with such a description efficiently. We will first
recall some wellestablished methods for permutation group; we will
then discuss some recent progress for matrix groups. 

All's Fair in Love and Statistics 12:35 Mon 28 Jul, 2014 :: B.19 Ingkarni Wardli :: Annie Conway :: University of Adelaide
Media...Earlier this year Wired.com published an article about a "math genius" who found true love after scraping and analysing data from a dating site. In this talk I will be investigating the actual mathematics that he used, in particular methods for clustering categorical data, and whether or not the approach was successful. 

Frequentist vs. Bayesian. 12:10 Mon 18 Aug, 2014 :: B.19 Ingkarni Wardli :: David Price :: University of Adelaide
Media...Abstract: There are two frameworks in which we can do statistical analyses. Choosing one framework over the other can be* as controversial as choosing between team Jacob and... that other guy. In this talk, I aim to give a very very simple explanation of the main difference between frequentist and Bayesian methods. I'll probably flip a coin and show you a video too.
* to people who really care. 

Ideal membership on singular varieties by means of residue currents 12:10 Fri 29 Aug, 2014 :: Ingkarni Wardli B20 :: Richard Larkang :: University of Adelaide
On a complex manifold X, one can consider the following ideal membership problem: Does a holomorphic function on X belong to a given ideal of holomorphic functions on X? Residue currents give a way of expressing analytically this essentially algebraic problem. I will discuss some basic cases of this, why such an analytic description might be useful, and finish by discussing a generalization of this to singular varieties. 

Testing Statistical Association between Genetic Pathways and Disease Susceptibility 12:10 Mon 1 Sep, 2014 :: B.19 Ingkarni Wardli :: Andy Pfieffer :: University of Adelaide
Media...A major research area is the identification of genetic pathways associated with various diseases. However, a detailed comparison of methods that have been designed to ascertain the association between pathways and diseases has not been performed.
I will give the necessary biological background behind GenomeWide Association Studies (GWAS), and explain the shortfalls in traditional GWAS methodologies. I will then explore various methods that use information about genetic pathways in GWAS, and explain the challenges in comparing these methods. 

Inferring absolute population and recruitment of southern rock lobster using only catch and effort data 12:35 Mon 22 Sep, 2014 :: B.19 Ingkarni Wardli :: John Feenstra :: University of Adelaide
Media...Abundance estimates from a datalimited version of catch survey analysis are compared to those from a novel oneparameter deterministic method. Bias of both methods is explored using simulation testing based on a more complex datarich stock assessment population dynamics fishery operating model, exploring the impact of both varying levels of observation error in data as well as model process error. Recruitment was consistently better estimated than legal size population, the latter most sensitive to increasing observation errors. A hybrid of the datalimited methods is proposed as the most robust approach. A more statistically conventional errorinvariables approach may also be touched upon if enough time. 

Spectral asymptotics on random Sierpinski gaskets 12:10 Fri 26 Sep, 2014 :: Ingkarni Wardli B20 :: Uta Freiberg :: Universitaet Stuttgart
Self similar fractals are often used in modeling porous media. Hence, defining a Laplacian and a Brownian motion on such sets describes transport through such materials. However, the assumption of strict self similarity could be too restricting. So, we present several models of random fractals which could be used instead. After recalling the classical approaches of random homogenous and recursive random fractals, we show how to interpolate between these two model classes with the help of so called Vvariable fractals. This concept (developed by Barnsley, Hutchinson & Stenflo) allows the definition of new families of random fractals, hereby the parameter V describes the degree of `variability' of the realizations. We discuss how the degree of variability influences the geometric, analytic and stochastic properties of these sets.  These results have been obtained with Ben Hambly (University of Oxford) and John Hutchinson (ANU Canberra). 

A Hybrid Markov Model for Disease Dynamics 12:35 Mon 29 Sep, 2014 :: B.19 Ingkarni Wardli :: Nicolas Rebuli :: University of Adelaide
Media...Modelling the spread of infectious diseases is fundamental to protecting ourselves from potentially devastating epidemics. Among other factors, two key indicators for the severity of an epidemic are the size of the epidemic and the time until the last infectious individual is removed. To estimate the distribution of the size and duration of an epidemic (within a realistic population) an epidemiologist will typically use Monte Carlo simulations of an appropriate Markov process. However, the number of states in the simplest Markov epidemic model, the SIR model, is quadratic in the population size and so Monte Carlo simulations are computationally expensive. In this talk I will discuss two methods for approximating the SIR Markov process and I will demonstrate the approximation error by comparing probability distributions and estimates of the distributions of the final size and duration of an SIR epidemic. 

Topology, geometry, and moduli spaces 12:10 Fri 10 Oct, 2014 :: Ingkarni Wardli B20 :: Nick Buchdahl :: University of Adelaide
In recent years, moduli spaces of one kind or
another have been shown to be of great utility, this
quite apart from their inherent interest. Many of their
applications involve their topology, but as we all know,
understanding of topological structures is often
facilitated through the use of geometric methods, and
some of these moduli spaces carry geometric structures that are
considerable interest in their own right.
In this talk, I will describe some of the background and
the ideas in this general context, focusing on questions
that I have been considering lately together with my
colleague Georg Schumacher from Marburg in Germany, who
was visiting us recently. 

Optimally Chosen Quadratic Forms for Partitioning Multivariate Data 13:10 Tue 14 Oct, 2014 :: Ingkarni Wardli 715 Conference Room :: Assoc. Prof. Inge Koch :: School of Mathematical Sciences
Media...Quadratic forms are commonly used in linear algebra. For ddimensional vectors they have a matrix representation, Q(x) = x'Ax, for some symmetric matrix A. In statistics quadratic forms are defined for ddimensional random vectors, and one of the bestknown quadratic forms is the Mahalanobis distance of two random vectors.
In this talk we want to partition a quadratic form Q(X) = X'MX, where X is a random vector, and M a symmetric matrix, that is, we want to find a ddimensional random vector W such that Q(X) = W'W. This problem has many solutions. We are interested in a solution or partition W of X such that pairs of corresponding variables (X_j, W_j) are highly correlated and such that W is simpler than the given X.
We will consider some natural candidates for W which turn out to be suboptimal in the sense of the above constraints, and we will then exhibit the optimal solution. Solutions of this type are useful in the wellknown Tsquare statistic. We will see in examples what these solutions look like. 

The SerreGrothendieck theorem by geometric means 12:10 Fri 24 Oct, 2014 :: Ingkarni Wardli B20 :: David Roberts :: University of Adelaide
The SerreGrothendieck theorem implies that every torsion
integral 3rd cohomology class on a finite CWcomplex is the invariant
of some projective bundle. It was originally proved in a letter by
Serre, used homotopical methods, most notably a Postnikov
decomposition of a certain classifying space with divisible homotopy
groups. In this talk I will outline, using work of the algebraic
geometer Offer Gabber, a proof for compact smooth manifolds using
geometric means and a little Ktheory. 

Happiness and social information flow: Computational social science through data. 15:10 Fri 7 Nov, 2014 :: EM G06 (Engineering & Maths Bldg) :: Dr Lewis Mitchell :: University of Adelaide
The recent explosion in big data coming from online social networks has led to an increasing interest in bringing quantitative methods to bear on questions in social science. A recent highprofile example is the study of emotional contagion, which has led to significant challenges and controversy. This talk will focus on two issues related to emotional contagion, namely remotesensing of populationlevel wellbeing and the problem of information flow across a social network. We discuss some of the challenges in working with massive online data sets, and present a simple tool for measuring largescale happiness from such data. By combining over 10 million geolocated messages collected from Twitter with traditional census data we uncover geographies of happiness at the scale of states and cities, and discuss how these patterns may be related to traditional wellbeing measures and public health outcomes. Using tools from information theory we also study information flow between individuals and how this may relate to the concept of predictability for human behaviour. 

Happiness and social information flow: Computational social science through data. 15:10 Fri 7 Nov, 2014 :: EM G06 (Engineering & Maths Bldg) :: Dr Lewis Mitchell :: University of Adelaide
The recent explosion in big data coming from online social networks has led to an increasing interest in bringing quantitative methods to bear on questions in social science. A recent highprofile example is the study of emotional contagion, which has led to significant challenges and controversy. This talk will focus on two issues related to emotional contagion, namely remotesensing of populationlevel wellbeing and the problem of information flow across a social network. We discuss some of the challenges in working with massive online data sets, and present a simple tool for measuring largescale happiness from such data. By combining over 10 million geolocated messages collected from Twitter with traditional census data we uncover geographies of happiness at the scale of states and cities, and discuss how these patterns may be related to traditional wellbeing measures and public health outcomes. Using tools from information theory we also study information flow between individuals and how this may relate to the concept of predictability for human behaviour. 

Modelling segregation distortion in multiparent crosses 15:00 Mon 17 Nov, 2014 :: 5.57 Ingkarni Wardli :: Rohan Shah (joint work with B. Emma Huang and Colin R. Cavanagh) :: The University of Queensland
Construction of highdensity genetic maps has been made feasible by lowcost highthroughput genotyping technology; however, the process is still complicated by biological, statistical and computational issues. A major challenge is the presence of segregation distortion, which can be caused by selection, difference in fitness, or suppression of recombination due to introgressed segments from other species. Alien introgressions are common in major crop species, where they have often been used to introduce beneficial genes from wild relatives.
Segregation distortion causes problems at many stages of the map construction process, including assignment to linkage groups and estimation of recombination fractions. This can result in incorrect ordering and estimation of map distances. While discarding markers will improve the resulting map, it may result in the loss of genomic regions under selection or containing beneficial genes (in the case of introgression).
To correct for segregation distortion we model it explicitly in the estimation of recombination fractions. Previously proposed methods introduce additional parameters to model the distortion, with a corresponding increase in computing requirements. This poses difficulties for large, densely genotyped experimental populations. We propose a method imposing minimal additional computational burden which is suitable for highdensity map construction in large multiparent crosses. We demonstrate its use modelling the known Sr36 introgression in wheat for an eightparent complex cross.


On the analyticity of CRdiffeomorphisms 12:10 Fri 13 Mar, 2015 :: Engineering North N132 :: Ilya Kossivskiy :: University of Vienna
One of the fundamental objects in several complex variables is CRmappings. CRmappings naturally occur in complex analysis as boundary values of mappings between domains, and as restrictions of holomorphic mappings onto real submanifolds. It was already observed by Cartan that smooth CRdiffeomorphisms between CRsubmanifolds in C^N tend to be very regular, i.e., they are restrictions of holomorphic maps. However, in general smooth CRmappings form a more restrictive class of mappings. Thus, since the inception of CRgeometry, the following general question has been of fundamental importance for the field: Are CRequivalent realanalytic CRstructures also equivalent holomorphically? In joint work with Lamel, we answer this question in the negative, in any positive CRdimension and CRcodimension. Our construction is based on a recent dynamical technique in CRgeometry, developed in my earlier work with Shafikov. 

Group Meeting 15:10 Fri 24 Apr, 2015 :: N218 Engineering North :: Dr Ben Binder :: University of Adelaide
Talk (Dr Ben Binder): How do we quantify the filamentous growth in a yeast colony?
Abstract: In this talk we will develop a systematic method to measure the spatial patterning of yeast colony morphology. The methods are applicable to other physical systems with circular spatial domains, for example, batch mixing fluid devices. A hybrid modelling approach of the yeast growth process will also be discussed.
After the seminar, Ben will start a group discussion by sharing some information and experiences on attracting honours/PhD students to the group. 

Haven't I seen you before? Accounting for partnership duration in infectious disease modeling 15:10 Fri 8 May, 2015 :: Level 7 Conference Room Ingkarni Wardli :: Dr Joel Miller :: Monash University
Media...Our ability to accurately predict and explain the spread of an infectious disease is a significant factor in our ability to implement effective interventions. Our ability to accurately model disease spread depends on how accurately we capture the various effects. This is complicated by the fact that infectious disease spread involves a number of time scales. Four that are particularly relevant are: duration of infection in an individual, duration of partnerships between individuals, the time required for an epidemic to spread through the population, and the time required for the population structure to change (demographic or otherwise).
Mathematically simple models of disease spread usually make the implicit assumption that the duration of partnerships is by far the shortest time scale in the system. Thus they miss out on the tendency for infected individuals to deplete their local pool of susceptibles. Depending on the details of the disease in question, this effect may be significant.
I will discuss work done to reduce these assumptions for "SIR" (SusceptibleInfectedRecovered) diseases, which allows us to interpolate between populations which are static and populations which change partners rapidly in closed populations (no entry/exit). I will then discuss early results in applying these methods to diseases such as HIV in which the population time scales are relevant. 

An EngineerMathematician Duality Approach to Finite Element Methods 12:10 Mon 18 May, 2015 :: Napier LG29 :: Jordan Belperio :: University of Adelaide
Media...The finite element method has been a prominently used numerical technique for engineers solving solid mechanics, electromagnetic and heat transfer problems for over 30 years. More recently the finite element method has been used to solve fluid mechanics problems, a field where finite difference methods are more commonly used.
In this talk, I will introduce the basic mathematics behind the finite element method, the similarity between the finite element method and finite difference method and comparing how engineers and mathematicians use finite element methods. I will then demonstrate two solutions to the wave equation using the finite element method. 

People smugglers and statistics 12:10 Mon 25 May, 2015 :: Ingkarni Wardli 715 Conference Room :: Prof. Patty Solomon :: School of Mathematical Sciences
Media...In 2012 the Commonwealth Chief Scientist asked for my advice on the statistics being used in people smuggling prosecutions. Many defendants come from poor fishing villages in Indonesia, where births are not routinely recorded and the age of the defendant is not known. However mandatory jail sentences apply in Australia for individuals convicted of people smuggling which do not apply to children less than 18 years old  so assessing the age of each defendant is very important. Following an Australian Human Rights Commission inquiry into the treatment of individuals suspected of people smuggling, the AttorneyGeneral's department sought advice from the Chief Scientist, which is where I come in. I'll present the methods used by the prosecution and defence, which are both wrong, and introduce the prosecutor's fallacy.


Mathematical Modeling and Analysis of Active Suspensions 14:10 Mon 3 Aug, 2015 :: Napier 209 :: Professor Michael Shelley :: Courant Institute of Mathematical Sciences, New York University
Complex fluids that have a 'bioactive' microstructure, like
suspensions of swimming bacteria or assemblies of immersed biopolymers
and motorproteins, are important examples of socalled active matter.
These internally driven fluids can have strange mechanical properties,
and show persistent activitydriven flows and selforganization. I will
show how firstprinciples PDE models are derived through reciprocal
coupling of the 'active stresses' generated by collective microscopic
activity to the fluid's macroscopic flows. These PDEs have an
interesting analytic structures and dynamics that agree qualitatively
with experimental observations: they predict the transitions to flow
instability and persistent mixing observed in bacterial suspensions, and
for microtubule assemblies show the generation, propagation, and
annihilation of disclination defects. I'll discuss how these models
might be used to study yet more complex biophysical systems.


Natural Optimisation (No Artificial Colours, Flavours or Preservatives) 12:10 Mon 21 Sep, 2015 :: Benham Labs G10 :: James Walker :: University of Adelaide
Media...Sometimes nature seems to have the best solutions to complicated optimisation problems. For example ant colonies have a clever way of optimising the amount of food brought to the colony using pheromones, the process of natural selection gives rise to species which are optimally suited to their environment and although this process is not technically natural, for centuries people have been using properties of crystal formation to make steel with optimal properties. In this talk I will discuss nonconvex optimisation and some optimisation methods inspired by natural processes. 

Analytic complexity of bivariate holomorphic functions and cluster trees 12:10 Fri 2 Oct, 2015 :: Ingkarni Wardli B17 :: Timur Sadykov :: Plekhanov University, Moscow
The KolmogorovArnold theorem yields a representation of a multivariate continuous function in terms of a composition of functions which depend on at most two variables. In the analytic case, understanding the complexity of such a representation naturally leads to the notion of the analytic complexity of (a germ of) a bivariate multivalued analytic function. According to Beloshapka's local definition, the order of complexity of any univariate function is equal to zero while the nth complexity class is defined recursively to consist of functions of the form a(b(x,y)+c(x,y)), where a is a univariate analytic function and b and c belong to the (n1)th complexity class. Such a represenation is meant to be valid for suitable germs of multivalued holomorphic functions.
A randomly chosen bivariate analytic functions will most likely have infinite analytic complexity. However, for a number of important families of special functions of mathematical physics their complexity is finite and can be computed or estimated. Using this, we introduce the notion of the analytic complexity of a binary tree, in particular, a cluster tree, and investigate its properties.


ChernSimons classes on loop spaces and diffeomorphism groups 12:10 Fri 16 Oct, 2015 :: Ingkarni Wardli B17 :: Steve Rosenberg :: Boston University
Media...Not much is known about the topology of the diffeomorphism group Diff(M) of manifolds M of dimension four and higher. We'll show that for a class of manifolds of dimension 4k+1, Diff(M) has infinite fundamental group. This is proved by translating the problem into a question about ChernSimons classes on the tangent bundle to the loop space LM. To build the CS classes, we use a family of metrics on LM associated to a Riemannian metric on M. The curvature of these metrics takes values in an algebra of pseudodifferential operators. The main technical step in the CS construction is to replace the ordinary matrix trace in finite dimensions with the Wodzicki residue, the unique trace on this algebra. The moral is that some techniques in finite dimensional Riemannian geometry can be extended to some examples in infinite dimensional geometry.


Use of epidemic models in optimal decision making 15:00 Thu 19 Nov, 2015 :: Ingkarni Wardli 5.57 :: Tim Kinyanjui :: School of Mathematics, The University of Manchester
Media...Epidemic models have proved useful in a number of applications in epidemiology. In this work, I will present two areas that we have used modelling to make informed decisions. Firstly, we have used an age structured mathematical model to describe the transmission of Respiratory Syncytial Virus in a developed country setting and to explore different vaccination strategies. We found that delayed infant vaccination has significant potential in reducing the number of hospitalisations in the most vulnerable group and that most of the reduction is due to indirect protection. It also suggests that marked public health benefit could be achieved through RSV vaccine delivered to age groups not seen as most at risk of severe disease. The second application is in the optimal design of studies aimed at collection of householdstratified infection data. A design decision involves making a tradeoff between the number of households to enrol and the sampling frequency. Two commonly used study designs are considered: crosssectional and cohort. The search for an optimal design uses Bayesian methods to explore the joint parameterdesign space combined with Shannon entropy of the posteriors to estimate the amount of information for each design. We found that for the crosssectional designs, the amount of information increases with the sampling intensity while the cohort design often exhibits a tradeoff between the number of households sampled and the intensity of followup. Our results broadly support the choices made in existing data collection studies. 

Mathematical modelling of the immune response to influenza 15:00 Thu 12 May, 2016 :: Ingkarni Wardli B20 :: Ada Yan :: University of Melbourne
Media...The immune response plays an important role in the resolution of primary influenza infection and prevention of subsequent infection in an individual. However, the relative roles of each component of the immune response in clearing infection, and the effects of interaction between components, are not well quantified.
We have constructed a model of the immune response to influenza based on data from viral interference experiments, where ferrets were exposed to two influenza strains within a short time period. The changes in viral kinetics of the second virus due to the first virus depend on the strains used as well as the interval between exposures, enabling inference of the timing of innate and adaptive immune response components and the role of crossreactivity in resolving infection. Our model provides a mechanistic explanation for the observed variation in viruses' abilities to protect against subsequent infection at short interexposure intervals, either by delaying the second infection or inducing stochastic extinction of the second virus. It also explains the decrease in recovery time for the second infection when the two strains elicit crossreactive cellular adaptive immune responses. To account for intersubject as well as intervirus variation, the model is formulated using a hierarchical framework. We will fit the model to experimental data using Markov Chain Monte Carlo methods; quantification of the model will enable a deeper understanding of the effects of potential new treatments.


Harmonic Analysis in Rough Contexts 15:10 Fri 13 May, 2016 :: Engineering South S112 :: Dr Pierre Portal :: Australian National University
Media...In recent years, perspectives on what constitutes the ``natural" framework within which to conduct various forms of mathematical analysis have shifted substantially. The common theme of these shifts can be described as a move towards roughness, i.e. the elimination of smoothness assumptions that had previously been considered fundamental. Examples include partial differential equations on domains with a boundary that is merely Lipschitz continuous, geometric analysis on metric measure spaces that do not have a smooth structure, and stochastic analysis of dynamical systems that have nowhere differentiable trajectories.
In this talk, aimed at a general mathematical audience, I describe some of these shifts towards roughness, placing an emphasis on harmonic analysis, and on my own contributions. This includes the development of heat kernel methods in situations where such a kernel is merely a distribution, and applications to deterministic and stochastic partial differential equations. 

Time series analysis of paleoclimate proxies (a mathematical perspective) 15:10 Fri 27 May, 2016 :: Engineering South S112 :: Dr Thomas Stemler :: University of Western Australia
Media...In this talk I will present the work my colleagues from the School of
Earth and Environment (UWA), the "trans disciplinary methods" group of
the Potsdam Institute for Climate Impact Research, Germany, and I did to
explain the dynamics of the AustralianSouth East Asian monsoon system
during the last couple of thousand years.
From a time series perspective paleoclimate proxy series are more or
less the monsters moving under your bed that wake you up in the middle
of the night. The data is clearly nonstationary, nonuniform sampled in
time and the influence of stochastic forcing or the level of measurement
noise are more or less unknown. Given these undesirable properties
almost all traditional time series analysis methods fail.
I will highlight two methods that allow us to draw useful conclusions
from the data sets. The first one uses Gaussian kernel methods to
reconstruct climate networks from multiple proxies. The coupling
relationships in these networks change over time and therefore can be
used to infer which areas of the monsoon system dominate the complex
dynamics of the whole system. Secondly I will introduce the
transformation cost time series method, which allows us to detect
changes in the dynamics of a nonuniform sampled time series. Unlike the
frequently used interpolation approach, our new method does not corrupt
the data and therefore avoids biases in any subsequence analysis. While
I will again focus on paleoclimate proxies, the method can be used in
other applied areas, where regular sampling is not possible.


Holomorphic Flexibility Properties of Spaces of Elliptic Functions 12:10 Fri 29 Jul, 2016 :: Ingkarni Wardli B18 :: David Bowman :: University of Adelaide
The set of meromorphic functions on an elliptic curve naturally possesses the structure of a complex manifold. The component of degree 3 functions is 6dimensional and enjoys several interesting complexanalytic properties that make it, loosely speaking, the opposite of a hyperbolic manifold. Our main result is that this component has a 54sheeted branched covering space that is an Oka manifold. 

Probabilistic Meshless Methods for Bayesian Inverse Problems 15:10 Fri 5 Aug, 2016 :: Engineering South S112 :: Dr Chris Oates :: University of Technology Sydney
Media...This talk deals with statistical inverse problems that involve partial differential equations (PDEs) with unknown parameters. Our goal is to account, in a rigorous way, for the impact of discretisation error that is introduced at each evaluation of the likelihood due to numerical solution of the PDE. In the context of meshless methods, the proposed, modelbased approach to discretisation error encourages statistical inferences to be more conservative in the presence of significant solver error. In addition, (i) a principled learningtheoretic approach to minimise the impact of solver error is developed, and (ii) the challenge of nonlinear PDEs is considered. The method is applied to parameter inference problems in which nonnegligible solver error must be accounted for in order to draw valid statistical conclusions. 

Predicting turbulence 14:10 Tue 30 Aug, 2016 :: Napier 209 :: Dr Trent Mattner :: School of Mathematical Sciences
Media...Turbulence is characterised by threedimensional unsteady fluid motion over a wide range of spatial and temporal scales. It is important in many problems of technological and scientific interest, such as drag reduction, energy production and climate prediction.
Turbulent flows are governed by the NavierStokes equations, which are a nonlinear system of partial differential equations. Typically, numerical methods are needed to find solutions to these equations. In turbulent flows, however, the resulting computational problem is usually intractable. Filtering or averaging the NavierStokes equations mitigates the computational problem, but introduces new quantities into the equations. Mathematical models of turbulence are needed to estimate these quantities. One promising turbulence model consists of a random collection of fluid vortices, which are themselves approximate solutions of the NavierStokes equations. 

What is the best way to count votes? 13:10 Mon 12 Sep, 2016 :: Hughes 322 :: Dr Stuart Johnson :: School of Mathematical Sciences
Media...Around the world there are many different ways of counting votes in elections, and even within Australia there are different methods in use in various states. Which is the best method? Even for the simplest case of electing one person in a single electorate there is no easy answer to this, in fact there is a famous result  Arrow's Theorem  which tells us that there is no perfect way of counting votes. I will describe a number of different methods along with their problems before giving a more precise statement of the theorem and outlining a proof 

A principled experimental design approach to big data analysis 15:10 Fri 23 Sep, 2016 :: Napier G03 :: Prof Kerrie Mengersen :: Queensland University of Technology
Media...Big Datasets are endemic, but they are often notoriously difficult to analyse because of their size, complexity, history and quality. The purpose of this paper is to open a discourse on the use of modern experimental design methods to analyse Big Data in order to answer particular questions of interest. By appeal to a range of examples, it is suggested that this perspective on Big Data modelling and analysis has wide generality and advantageous inferential and computational properties. In particular, the principled experimental design approach is shown to provide a flexible framework for analysis that, for certain classes of objectives and utility functions, delivers equivalent answers compared with analyses of the full dataset. It can also provide a formalised method for iterative parameter estimation, model checking, identification of data gaps and evaluation of data quality. Finally it has the potential to add value to other Big Data sampling algorithms, in particular divideandconquer strategies, by determining efficient subsamples. 

SIR epidemics with stages of infection 12:10 Wed 28 Sep, 2016 :: EM218 :: Matthieu Simon :: Universite Libre de Bruxelles
Media...This talk is concerned with a stochastic model for the spread of an epidemic in a closed homogeneously mixing population. The population is subdivided into three classes of individuals: the susceptibles, the infectives and the removed cases. In short, an infective remains infectious during a random period of time. While infected, it can contact all the susceptibles present, independently of the other infectives. At the end of the infectious period, it becomes a removed case and has no further part in the infection process.
We represent an infectious period as a set of different stages that an infective can go through before being removed. The transitions between stages are ruled by either a Markov process or a semiMarkov process. In each stage, an infective makes contaminations at the epochs of a Poisson process with a specific rate.
Our purpose is to derive closed expressions for a transform of different statistics related to the end of the epidemic, such as the final number of susceptibles and the area under the trajectories of all the infectives. The analysis is performed by using simple matrix analytic methods and martingale arguments. Numerical illustrations will be provided at the end of the talk. 

What is index theory? 12:10 Tue 21 Mar, 2017 :: Inkgarni Wardli 5.57 :: Dr Peter Hochs :: School of Mathematical Sciences
Media...Index theory is a link between topology, geometry and analysis. A typical theorem in index theory says that two numbers are equal: an analytic index and a topological index. The first theorem of this kind was the index theorem of Atiyah and Singer, which they proved in 1963. Index theorems have many applications in maths and physics. For example, they can be used to prove that a differential equation must have a solution. Also, they imply that the topology of a space like a sphere or a torus determines in what ways it can be curved. Topology is the study of geometric properties that do not change if we stretch or compress a shape without cutting or glueing. Curvature does change when we stretch something out, so it is surprising that topology can say anything about curvature. Index theory has many surprising consequences like this.


Stokes' Phenomenon in Translating Bubbles 15:10 Fri 2 Jun, 2017 :: Ingkarni Wardli 5.57 :: Dr Chris Lustri :: Macquarie University
This study of translating air bubbles in a HeleShaw cell containing viscous fluid reveals the critical role played by surface tension in these systems. The standard zerosurfacetension model of HeleShaw flow predicts that a continuum of bubble solutions exists for arbitrary flow translation velocity. The inclusion of small surface tension, however, eliminates this continuum of solutions, instead producing a discrete, countably infinite family of solutions, each with distinct translation speeds. We are interested in determining this discrete family of solutions, and understanding why only these solutions are permitted.
Studying this problem in the asymptotic limit of small surface tension does not seem to give any particular reason why only these solutions should be selected. It is only by using exponential asymptotic methods to study the Stokesâ structure hidden in the problem that we are able to obtain a complete picture of the bubble behaviour, and hence understand the selection mechanism that only permits certain solutions to exist.
In the first half of my talk, I will explain the powerful ideas that underpin exponential asymptotic techniques, such as analytic continuation and optimal truncation. I will show how they are able to capture behaviour known as Stokes' Phenomenon, which is typically invisible to classical asymptotic series methods. In the second half of the talk, I will introduce the problem of a translating air bubble in a HeleShaw cell, and show that the behaviour can be fully understood by examining the Stokes' structure concealed within the problem. Finally, I will briefly showcase other important physical applications of exponential asymptotic methods, including submarine waves and particle chains. 

Complex methods in real integral geometry 12:10 Fri 28 Jul, 2017 :: Engineering Sth S111 :: Mike Eastwood :: University of Adelaide
There are wellknown analogies between holomorphic integral transforms such as the Penrose transform and real integral transforms such as the Radon, Funk, and John transforms. In fact, one can make a precise connection between them and hence use complex methods to establish results in the real setting. This talk will introduce some simple integral transforms and indicate how complex analysis may be applied. 

Exact coherent structures in high speed flows 15:10 Fri 28 Jul, 2017 :: Ingkarni Wardli B17 :: Prof Philip Hall :: Monash University
In recent years, there has been much interest in the relevance of nonlinear solutions of the NavierStokes equations to fully turbulent flows. The solutions must be calculated numerically at moderate Reynolds numbers but in the limit of high Reynolds numbers asymptotic methods can be used to greatly simplify the computational task and to uncover the key physical processes sustaining the nonlinear states. In particular, in confined flows exact coherent structures defining the boundary between the laminar and turbulent attractors can be constructed. In addition, structures which capture the essential physical properties of fully turbulent flows can be found. The extension of the ideas to boundary layer flows and current work attempting to explain the law of the wall will be discussed.


The Markovian binary tree applied to demography and conservation biology 15:10 Fri 27 Oct, 2017 :: Ingkarni Wardli B17 :: Dr Sophie Hautphenne :: University of Melbourne
Markovian binary trees form a general and tractable class of continuoustime branching processes, which makes them wellsuited for realworld applications. Thanks to their appealing probabilistic and computational features, these processes have proven to be an excellent modelling tool for applications in population biology. Typical performance measures of these models include the extinction probability of a population, the distribution of the population size at a given time, the total progeny size until extinction, and the asymptotic population composition. Besides giving an overview of the main performance measures and the techniques involved to compute them, we discuss recently developed statistical methods to estimate the model parameters, depending on the accuracy of the available data. We illustrate our results in human demography and in conservation biology. 

Stochastic Modelling of Urban Structure 11:10 Mon 20 Nov, 2017 :: Engineering Nth N132 :: Mark Girolami :: Imperial College London, and The Alan Turing Institute
Media...Urban systems are complex in nature and comprise of a large number of individuals that act according to utility, a measure of net benefit pertaining to preferences. The actions of individuals give rise to an emergent behaviour, creating the socalled urban structure that we observe. In this talk, I develop a stochastic model of urban structure to formally account for uncertainty arising from the complex behaviour. We further use this stochastic model to infer the components of a utility function from observed urban structure. This is a more powerful modelling framework in comparison to the ubiquitous discrete choice models that are of limited use for complex systems, in which the overall preferences of individuals are difficult to ascertain. We model urban structure as a realization of a Boltzmann distribution that is the invariant distribution of a related stochastic differential equation (SDE) that describes the dynamics of the urban system. Our specification of Boltzmann distribution assigns higher probability to stable configurations, in the sense that consumer surplus (demand) is balanced with running costs (supply), as characterized by a potential function. We specify a Bayesian hierarchical model to infer the components of a utility function from observed structure. Our model is doublyintractable and poses significant computational challenges that we overcome using recent advances in Markov chain Monte Carlo (MCMC) methods. We demonstrate our methodology with case studies on the London retail system and airports in England. 

Quantifying language change 15:10 Fri 1 Jun, 2018 :: Horace Lamb 1022 :: A/Prof Eduardo Altmann :: University of Sydney
Mathematical methods to study natural language are increasingly important because of the ubiquity of textual data in the Internet. In this talk I will discuss mathematical models and statistical methods to quantify the variability of language, with focus on two problems: (i) How the vocabulary of languages changed over the last centuries? (ii) How the language of scientific disciplines relate to each other and evolved in the last decades? One of the main challenges of these analyses stem from universal properties of word frequencies, which show high temporal variability and are fattailed distributed. The later feature dramatically affects the statistical properties of entropybased estimators, which motivates us to compare vocabularies using a generalized JensonShannon divergence (obtained from entropies of order alpha). 

Quantifying language change 15:10 Fri 1 Jun, 2018 :: Napier 208 :: A/Prof Eduardo Altmann :: University of Sydney
Mathematical methods to study natural language are increasingly important because of the ubiquity of textual data in the Internet. In this talk I will discuss mathematical models and statistical methods to quantify the variability of language, with focus on two problems: (i) How the vocabulary of languages changed over the last centuries? (ii) How the language of scientific disciplines relate to each other and evolved in the last decades? One of the main challenges of these analyses stem from universal properties of word frequencies, which show high temporal variability and are fattailed distributed. The later feature dramatically affects the statistical properties of entropybased estimators, which motivates us to compare vocabularies using a generalized JensonShannon divergence (obtained from entropies of order alpha). 

The topology and geometry of spaces of YangMillsHiggs flow lines 11:10 Fri 27 Jul, 2018 :: Barr Smith South Polygon Lecture theatre :: Graeme Wilkin :: National University of Singapore
Given a smooth complex vector bundle over a compact Riemann surface, one can define the space of Higgs bundles and an energy functional on this space: the YangMillsHiggs functional. The gradient flow of this functional resembles a nonlinear heat equation, and the limit of the flow detects information about the algebraic structure of the initial Higgs bundle (e.g. whether or not it is semistable). In this talk I will explain my work to classify ancient solutions of the YangMillsHiggs flow in terms of their algebraic structure, which leads to an algebrogeometric classification of YangMillsHiggs flow lines. Critical points connected by flow lines can then be interpreted in terms of the Hecke correspondence, which appears in Wittenâs recent work on Geometric Langlands. This classification also gives a geometric description of spaces of unbroken flow lines in terms of secant varieties of the underlying Riemann surface, and in the remaining time I will describe work in progress to relate the (analytic) Morse compactification of these spaces by broken flow lines to an algebrogeometric compactification by iterated blowups of secant varieties. 

Minmax theory for hypersurfaces of prescribed mean curvature 11:10 Fri 17 Aug, 2018 :: Barr Smith South Polygon Lecture theatre :: Jonathan Zhu :: Harvard University
We describe the construction of closed prescribed mean curvature (PMC) hypersurfaces using minmax methods. Our theory allows us to show the existence of closed PMC hypersurfaces in a given closed Riemannian manifold for a generic set of ambient prescription functions. This set includes, in particular, all constant functions as well as analytic functions if the manifold is real analytic. The described work is joint with Xin Zhou. 

How long does it take to get there? 11:10 Fri 19 Oct, 2018 :: Engineering North N132 :: Professor Herbert Huppert :: University of Cambridge
In many situations involving nonlinear partial differential equations, requiring much numerical calculation because there is no analytic solution, it is possible to find a similarity solution to the resulting (still nonlinear) ordinary differential equation; sometimes even analytically, but it is generally independent of the initial conditions. The similarity solution is said to approach the real solution for t >> tau, say. But what is tau? How does it depend on the parameters of the problem and the initial conditions? Answers will be presented for a variety of problems and the audience will be asked to suggest others if they know of them.


Some advances in the formulation of analytical methods for linear and nonlinear dynamics 15:10 Tue 20 Nov, 2018 :: EMG07 :: Dr Vladislav Sorokin :: University of Auckland
In the modern engineering, it is often necessary to solve problems involving strong parametric excitation and (or) strong nonlinearity. Dynamics of micro and nanoscale electromechanical systems, wave propagation in structures made of corrugated composite materials are just examples of those. Numerical methods, although able to predict systems behavior for specific sets of parameters, fail to provide an insight into underlying physics. On the other hand, conventional analytical methods impose severe restrictions on the problem parameters space and (or) on types of the solutions.
Thus, the quest for advanced tools to deal with linear and nonlinear structural dynamics still continues, and the lecture is concerned with an advanced formulation of an analytical method. The principal novelty aspect is that the presence of a small parameter in governing equations is not requested, so that dynamic problems involving strong parametric excitation and (or) strong nonlinearity can be considered. Another advantage of the method is that it is free from conventional restrictions on the excitation frequency spectrum and applicable for problems involving combined multiple parametric and (or) direct excitations with incommensurate frequencies, essential for some applications.
A use of the method will be illustrated in several examples, including analysis of the effects of corrugation shapes on dispersion relation and frequency bandgaps of structures and dynamics of nonlinear parametric amplifiers. 
News matching "Matrix analytic methods" 
ARC Grant successes Congratulations to Tony Roberts, Charles Pearce, Robert Elliot, Andrew Metcalfe and all their collaborators on their success in the current round of ARC grants. The projects are "Development of innovative technologies for oil production based on the advanced theory of suspension flows in porous media" (Tony Roberts et al.), "Perturbation and approximation methods for linear operators with applications to train control, water resource management and evolution of physical systems" (Charles Pearce et al.),
"Risk Measures and Management in Finance and Actuarial Science Under RegimeSwitching Models" (Robert Elliott et al.) and "A new flood design methodology for a variable and changing climate" (Andrew Metcalfe et al.) Posted Mon 26 Oct 09. 

ARC Grant successes The School of Mathematical Sciences has again had outstanding success in the ARC Discovery and Linkage Projects schemes.
Congratulations to the following staff for their success in the Discovery Project scheme:
Prof Nigel Bean, Dr Josh Ross, Prof Phil Pollett, Prof Peter Taylor, New methods for improving active adaptive management in biological systems, $255,000 over 3 years;
Dr Josh Ross, New methods for integrating population structure and stochasticity into models of disease dynamics, $248,000 over three years;
A/Prof Matt Roughan, Dr Walter Willinger, Internet trafficmatrix synthesis, $290,000 over three years;
Prof Patricia Solomon, A/Prof John Moran, Statistical methods for the analysis of critical care data, with application to the Australian and New Zealand Intensive Care Database, $310,000 over 3 years;
Prof Mathai Varghese, Prof Peter Bouwknegt, Supersymmetric quantum field theory, topology and duality, $375,000 over 3 years;
Prof Peter Taylor, Prof Nigel Bean, Dr Sophie Hautphenne, Dr Mark Fackrell, Dr Malgorzata O'Reilly, Prof Guy Latouche, Advanced matrixanalytic methods with applications, $600,000 over 3 years.
Congratulations to the following staff for their success in the Linkage Project scheme:
Prof Simon Beecham, Prof Lee White, A/Prof John Boland, Prof Phil Howlett, Dr Yvonne Stokes, Mr John Wells, Paving the way: an experimental approach to the mathematical modelling and design of permeable pavements, $370,000 over 3 years;
Dr Amie Albrecht, Prof Phil Howlett, Dr Andrew Metcalfe, Dr Peter Pudney, Prof Roderick Smith, Saving energy on trains  demonstration, evaluation, integration, $540,000 over 3 years
Posted Fri 29 Oct 10. 

Summer Research Student Thomas Brown wins the AMSI/Cambridge University Press Prize for 2013 Congratulations to Thomas Brown, jointly supervised by Ed Green and Ben Binder who won the AMSI/Cambridge University Press Prize for the best talk at the 2013 CSIRO Big Day In, recently held this month.
After completion of their summer project, vacation scholars must submit a project report which summarises the project and addresses the nature of the topic, methods of investigation, results found, and benefits of the experience. The scholars then present a 15minute presentation about their project at the CSIRO Big Day In (BDI). This experience enables students to meet and socialise with their peers, gain experience presenting to their colleagues and supervisors and learn about a range of careers in science by interacting with several CSIRO scientists (including mathematicians) in a discussion panel.
This is a very pleasing result for Thomas, Ed and Ben as well as for the School of Mathematical Sciences. Well done Thomas.
Posted Fri 15 Feb 13. 
Publications matching "Matrix analytic methods"Publications 

Medical imaging and processing methods for cardiac flow reconstruction Wong, Kelvin; Kelso, Richard; Worthley, Stephen; Sanders, Prashanthan; Mazumdar, Jagan; Abbott, Derek, Journal of Mechanics in Medicine and Biology 9 (1–20) 2009  Portfolio risk minimization and differential games Elliott, Robert; Siu, T, Nonlinear AnalysisTheory Methods & Applications In Press (–) 2009  SiciakZahariuta extremal functions, analytic discs and polynomial hulls Larusson, Finnur; Sigurdsson, R, Mathematische Annalen 345 (159–174) 2009  Learning fuzzy rules with evolutionary algorithms  An analytic approach Kroeske, Jens; Ghandar, Adam; Michalewicz, Zbigniew; Neumann, F, 10th International Conference on Parallel Problem Solving from Nature, Germany 01/09/08  Characterization of matrixexponential distributions Bean, Nigel; Fackrell, Mark; Taylor, Peter, Stochastic Models 24 (339–363) 2008  Oriented bond percolation and phase transitions: an analytic approach Pearce, Charles, International Conference on Numerical Analysis and Applied Mathematics, Corfu, Greece 16/09/07  Monogenic functions in conformal geometry Eastwood, Michael; Ryan, J, Symmetry, Integrability and Geometry: Methods and Applications 84 (1–14) 2007  Nonclassical symmetry solutions for reactiondiffusion equations with explicity spatial dependence Hajek, Bronwyn; Edwards, M; Broadbridge, P; Williams, G, Nonlinear AnalysisTheory Methods & Applications 67 (2541–2552) 2007  Symmetries and invariant differential pairings Eastwood, Michael, Symmetry, Integrability and Geometry: Methods and Applications 113 (1–10) 2007  Traffic matrix estimation method and apparatus Duffield, N; Greenberg, A; Klincewicz, J; Roughan, Matthew; Zhang, Y,  Fractional analytic index Varghese, Mathai; Melrose, R; Singer, I, Journal of Differential Geometry 74 (265–292) 2006  Methodology in metaanalysis: a study from critical care metaanalytic practice Moran, John; Solomon, Patricia; Warn, D, Health Services and Outcomes Research Methodology 5 (207–226) 2006  Methods of constrained and unconstrained approximation for mappings in probability spaces Torokhti, Anatoli; Howlett, P; Pearce, Charles, chapter in Modern Applied Mathematics (Narosa Publishing House) 83–129, 2005  Boundary element methods for infiltration from irrigation channels Lobo, Maria; Clements, David, The International Conference on Boundary Element Techniques VI, Montreal, Canada 27/07/05  A 3D nonhydrostatic pressure model for small amplitude free surface flows Lee, Jong; Teubner, Michael; Nixon, John; Gill, Peter, International Journal for Numerical Methods in Fluids 50 (649–672) 2005  An analytic modelling approach for network routing algorithms that use "antlike" mobile agents Bean, Nigel; Costa, Andre, Computer NetworksThe International Journal of Computer and Telecommunications Networking 49 (243–268) 2005  Applications of the artificial compressibility method for turbulent open channel flows Lee, Jong; Teubner, Michael; Nixon, John; Gill, Peter, International Journal for Numerical Methods in Fluids 51 (617–633) 2005  Ramaswami's duality and probabilistic algorithms for determining the rate matrix for a structured GI/M/1 Markov chain Hunt, Emma, The ANZIAM Journal 46 (485–493) 2005  Traffic matrix reloaded: Impact of routing changes Teixeira, R; Duffield, N; Rexford, J; Roughan, Matthew, Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence 3431 (251–264) 2005  An introduction to programming and numerical methods in MATLAB Otto, S; Denier, James, (SpringerVerlag) 2005  A probabilistic algorithm for finding the rate matrix of a blockGI/M/1 Markov chain Hunt, Emma, The ANZIAM Journal 45 (457–475) 2004  A sufficient condition for the uniform exponential stability of timevarying systems with noise Grammel, G; Maizurna, Isna, Nonlinear AnalysisTheory Methods & Applications 56 (951–960) 2004  Spectral decomposition methods for the computation of RMS values in an active suspension Pearce, Charles; Thompson, A, Vehicle System Dynamics 42 (395–411) 2004  Second moments of a matrix analytic model of machine maintenance Green, David; Metcalfe, Andrew, IMA International Conference on Modelling in Industrial Maintenance and Reliability (5th: 2004), Salford, United Kingdom 05/04/04  Arborescences, matrixtrees and the accumulated sojourn time in a Markov process Pearce, Charles; Falzon, L, chapter in Stochastic analysis and applications Volume 3 (Nova Science Publishers) 147–168, 2003  A Probabilistic algorithm for determining the fundamental matrix of a block M/G/1 Markov chain Hunt, Emma, Mathematical and Computer Modelling 38 (1203–1209) 2003  Dynamics of the cell and its extracellular matrix  A simple mathematical approach Saha, Asit; Mazumdar, Jagan, IEEE Transactions on NanoBioscience 2 (89–93) 2003  Edge of the wedge theory in hypoanalytic manifolds Eastwood, Michael; Graham, C, Communications in Partial Differential Equations 28 (2003–2028) 2003  Numerical model of electrical potential within the human head Nixon, John; Rasser, Paul; Teubner, Michael; Clark, C; Bottema, M, International Journal for Numerical Methods in Engineering 56 (2353–2366) 2003  An InformationTheoretic Approach to Traffic Matrix Estimation Zhang, Y; Roughan, Matthew; Lund, C; Donoho, D, Ulrich, Karlsruche, Germany 25/08/03  Nonclassical description of analytic cohomology Bailey, T; Eastwood, Michael; Gindikin, S,  A matrix analytic model for machine maintenance Green, David; Metcalfe, Andrew; Swailes, D, MatrixAnalytic Methods: Theory and Applications, Adelaide, Australia 14/07/02  Martingale methods for analysing singleserver queues Roughan, Matthew; Pearce, Charles, Queueing Systems 41 (205–239) 2002  Mathematical methods for spatially cohesive reserve design McDonnell, Mark; Possingham, Hugh; Ball, Ian; Cousins, Elizabeth, Environmental Modeling & Assessment 7 (107–114) 2002  Comparison of spinal myotatic reflexes in human adults investigated with crosscorrelation and signal averaging methods Miller, S; Clark, J; Eyre, J; Kelly, S; Lim, E; McClelland, V; McDonough, S; Metcalfe, Andrew, Brain Research 899 (47–65) 2001  Csiszr fdivergence, Ostrowski's inequality and mutual information Dragomir, S; Gluscevic, Vido; Pearce, Charles, Nonlinear AnalysisTheory Methods & Applications 47 (2375–2386) 2001  Some new bounds for singular values and eigenvalues of matrix products Lu, LZ; Pearce, Charles, Annals of Operations Research 98 (141–148) 2001  The modelling and numerical simulation of causal nonlinear systems Howlett, P; Torokhti, Anatoli; Pearce, Charles, Nonlinear AnalysisTheory Methods & Applications 47 (5559–5572) 2001  Truncationtype methods and Bcklund transformations for ordinary differential equations: The third and fifth Painlev equations Gordoa, P; Joshi, Nalini; Pickering, A, Glasgow Mathematical Journal 43A (23–32) 2001  Martingale methods in dynamic portfolio allocation with distortion operators Hamada, M; Sherris, M; Van Der Hoek, John, Quantitative Methods in Finance (2001), Sydney, Australia 12/12/01  Reporting of clinical trials using group sequential methods Moran, John; Peake, Sandra; Solomon, Patricia, Critical care and Resuscitation 3 (146–147) 2001  Metaanalysis, overviews and publication bias Solomon, Patricia; Hutton, Jonathon, Statistical Methods in Medical Research 10 (245–250) 2001  Analytic continuation of vector bundles with Lpcurvature Harris, A; Tonegawa, Y, International Journal of Mathematics 11 (29–40) 2000  Disease surveillance and data collection issues in epidemic modelling Solomon, Patricia; Isham, V, Statistical Methods in Medical Research 9 (259–277) 2000  Explicit finite difference methods for variable velocity advection in the presence of a source Noye, Brian, Computers & Fluids 29 (385–399) 2000  Numerical study of the stability of some explicit finitedifference methods for oscillatory advection Noye, Brian; McInerney, David, The ANZIAM Journal 42 (C1076–C1096) 2000  Disease surveillance and intervention studies in developing countries Solomon, Patricia, Statistical Methods in Medical Research 9 (183–184) 2000 
Advanced search options
You may be able to improve your search results by using the following syntax:
Query  Matches the following 

Asymptotic Equation  Anything with "Asymptotic" or "Equation". 
+Asymptotic +Equation  Anything with "Asymptotic" and "Equation". 
+Stokes "NavierStokes"  Anything containing "Stokes" but not "NavierStokes". 
Dynam*  Anything containing "Dynamic", "Dynamical", "Dynamicist" etc. 
