Read on to find out more about the seminar abstracts and biographies of our researchers here at the Phenomics and Bioinformatics Research Centre.
Dr Ettore Stella
3D reconstruction systems for ndt quality control
The talk concerns about systems for recovery 3d information of scene by vision analysis. Some applications in industrial automation, infrastructure monitoring and quality control will be presented. The talk will give a brief description of research activity at Institute of Study on Intelligent Systems for Automation of Italian National Research Council (ISSIA).
Ettore Stella, received the degree in Computer Science at University of Bari on 1984 cum laude. Since June 1984 until November 1987, collaborated with IESI-CNR on topics about Computer Vision and Robotics. Since November 1987 until July 1990 became researcher of National Space Plan (C.N.R.) at Centro di Geodesia Spaziale (Matera) and he worked on Space Robotic project. Since September 1990 is researcher at ISSIA-CNR (ex IESI) in Bari and he works on Computer Vision and Robotic topics. Since December 2001 he is Senior Researcher (Primo Ricercatore) at ISSIA-CNR. Since 2004 he is associated professor in Computer Science at University of Basilicata (Matera), for TLC engineering faculty. From a professional point of view, Ettore Stella, has certified experience on: industrial automation, robotics, computer vision, high-performance computing, software design and development. He was supervisor of several degree thesis for University of Bari, Lecce and Basilicata. He is scientific chief of several research projects (industrial and governative). He is co-author of more than 100 papers on international journals and proceeding of conferences. He was co-author of book chapters and international patents.
Associate Professor Tim Brodribb
Green evolution- taking the sex out of plant evolution
Macroevolutionary succession in the terrestrial flora is traditionally explained by changes in the reproductive parts of plants. Our work provides evidence that major transitions in plant evolution are also marked by functional innovations that may better explain the success of one plant clade over another. I will focus on two such transitions; firstly the evolution of complex stomatal control in seed plants, and secondly the evolution of super-efficient water transport in angiosperm leaves.
Since commencing my PhD with Prof Bob Hill (now at Uni Adelaide) Tim Brodribb has used physiological techniques to determine how changes in water transport and photosynthetic systems are related to patterns of plant ecology and evolution. Tim received his PhD Conifer physiological evolution from UTAS in 1997. He has been a research fellow at UTAS from 1999 to 2000 then a Putnam Fellow Harvard University (USA)-2001-2005, Australian Research Fellow at UTAS (2005-2010) and ARC Future Fellow at UTAS since 2010.
Professor Rosemary Bailey
Circular designs balanced for neighbours at distances one and two
We consider experiments where the experimental units are arranged in a circle or in a single line in space or time. If neighbouring treatments may affect the response on an experimental unit, then we need a model which includes the effects of direct treatments, left neighbours and right neighbours. It is desirable that each ordered pair of treatments occurs just once as neighbours and just once with a single unit in between. A circular design with this property is equivalent to a special type of quasigroup.
In one variant of this, self-neighbours are forbidden. In a further variant, it is assumed that the left-neighbour effect is the same as the right-neighbour effect, so all that is needed is that each unordered pair of treatments occurs just once as neighbours and just once with a single unit in between.
I shall report progress on finding methods of constructing the three types of design.
Rosemary is a Professor of Mathematics and Statistics in the School of Mathematics and Statistics at the University of St Andrews. She took up the post in March 2013, having retired from Queen Mary, University of London at the end of September 2012. She is a Professor Emerita of Statistics in the School of Mathematical Sciences at QMUL. From January to June 2013 she is also G. C. Stewart Fellow at Caius College Cambridge.
Her first job was as a technician in the Medical Research Council's Air Pollution Research Unit at St Bartholomew's Hospital Medical College. She entered data, and helped to analyse it, in the pre-computer age. Her second was as a teacher of Mathematics and French at Queen Elizabeth School in Ilorin, Nigeria, working with Voluntary Service Overseas. The volunteers had all of two weeks' training in teaching, and she had to pick up the French on the spot after the French teacher left.
Her first and second degrees were both in Mathematics, at the University of Oxford, where she was a member of St Hugh's College. My DPhil thesis was about finite permutation groups; she was supervised by Graham Higman.
Rosemary joined the fledging Open University in 1972. During her time there she was seconded to the Statistics Department in the University of Edinburgh, where she held a Science Research Council post-doctoral research fellowship. Under the supervision of Desmond Patterson of the Agricultural Research Council's Unit of Statistics, she converted herself into a statistician, learning about design of experiments by immersing herself in Fisher's, Yates's and Nelder's papers, listening to her ARCUS colleagues, and teaching an MSc course on the subject.
Wanting to gain some practical experience of real experiments, she joined the Statistics Department of Rothamsted Experimental Station in 1981, intending to stay for two years. She ended up staying for ten.
In 1991 she moved back into academia, being Professor of Mathematical Sciences at Goldsmiths College in the University of London and then Professor of Statistics at QMUL. In both places she spent four years as head of department or school.
Professor Bob Anderssen
Recovering information about grain hardness from SKCS 4100 measurements
A key requirement for efficient plant breeding is to have good (quantitative) phenotypes which allow different genotypes to be quick and easily classified into representative equivalence classes. The use of different measures of grain hardness for wheat has a long history. The differences in the particle size distributions of the flours milled from hard and soft wheats have been used to compare their baking performance and to highlight the differences in the genetics of the relationship between starch granules and the gluten proteins which surround them.
On an SKCS 4100 device, the response of an individual grain to its compression can be measured as an individual crush response profile (iCRP). It has been popular since the invention of the device to use the incremental change in an iCRP to compute an SKCS HI value. Though there is considerable variability in the iCRPs for a set of grains from the same variety, it appears to be stochastic since, for sufficiently large numbers of randomly chosen grains of the same wheat variety, the averaging of their iCRPs consistently gives the same average crush response profile (aCRP). The advantage of the aCRPs is that (i) they are rheological encapsulations of the dynamics of the fractioning of individual wheat grains under compression, and (ii) the rheological features in their double hump structure can be used to define various quantitative phenotypes (the rheological phenotype phases (RPPs)).
The talk will explain how the RPPs identify clear differences in the biological structure of hexaploid and durum wheats. Though the emphasis of the talk is the science, measurement and interpretation of wheat grain hardness, there is a strong connection to fundamental aspects of mathematics through the rheology which will be briefly mentioned.
Based on collaborative research with R. Haraszi, A. Juhasz, L. Tamas, M. Rakszgei, M. Sissons, F. R. de Hoog, R. J. Loy
Bob Anderssen completed BSc and MSc degrees, which tended to focused on applied and computational mathematics, at the University of Queensland. His current and continuing interest in inverse problems, especially in applications, was initiated by his MSc studies on the computational recovery of information about the electrical conductivity of the Earth from electromagnetic measurements made on the Earth’s surface.
His PhD in mathematics, on the numerical performance of variational methods, was obtained at the University of Adelaide, where he was also a tutor in mathematics. In 2008, he received an honorary DSc (honoris causa) from La Trobe University, and, in 2010, was awarded an Order of Australia Medal.
He taught mathematics for one year at Monash, where he gave the third year numerical analysis lectures, before accepting a full time research position at the ANU in computational mathematics. His interests in inverse problems were stimulated through collaboration with seismologists on the recovery of information about the density structure of the Earth from the measurements of its free oscillations after a major earthquake. It was also during this period that his interest in the numerical differentiation of observational data and the solution of integral equations surfaced through interaction with biologists and statisticians.
In 1979, because of his keen interest in the application of mathematics to real-world problems and industrial inverse problems, he accepted a position in industrial and computational mathematics in the CSIRO Division of Mathematics and Statistics.
He has held visiting positions at a number of international universities including Stanford, Princeton, Cambridge (UK), Linz, TU-Munich and TU-Vienna, and at the Johann Radon Institute of Computational and Applied Mathematics (RICAM) of the Austrian Academy of Sciences, and given invited lectures at an even bigger group including Harvard, Oxford, the University of Vienna, the Ecole Polytechnique, Oberwolfach and the Fields Institute.
He has been president of the Australian Mathematical Society and chair of the National Committee for Mathematics. He has been awarded the George Szekeres, Joe Moyal and the ANZIAM medals , given the G. S. Watson Annual Lecture at La Trobe University in Bendigo and is a Fellow of the Australian Mathematics Society.
His current research has focuses on theoretical polymer dynamics, vibrating piano strings (the Stuart piano), the flow and deformation of wheat flour dough from a plant breeding perspective, pattern formation in plants, and the analysis and interpretation of spectroscopic data.
His current community/professional activities include being the CSIRO advisor to the Editor of CSIRO’s Mathematics-by-Email and, on a regular basis when schools are in session, participating in CSIRO’s Mathematicians-in-Schools by being one of the mathematicians. In the latter activity, his goal, when talking to primary school students, is to engage and stimulate their interest in mathematics by discussing various mathematical patterns which illustrate important mathematical properties.
His hobbies include gardening, hiking and classical music.
Associate Professor Scott McCue
Shatter, bounce, adhere or spread: droplets impacting and spreading on leaf surfaces
An important component of research into agrichemical spraying is to determine retention rates of spray droplets by plant foliage. At an elementary level, we may assume that when a droplet impacts on a leaf, it may either shatter, bounce or adhere. I will discuss some simple mathematical models for these outcomes that are based on energy balance arguments, and present some research on simulating whole plant spraying that uses these models. Another interesting question is how droplets may spread across a leaf surface once deposited. I will present a primitive mathematical model for this process, as well as a complicated one. The complicated model is based on applying a lubrication approximation to derive a thin film type governing equation which is fourth order, nonlinear and parabolic. This work is part of the ARC Linkage Project LP100200476 funded by the ARC and industry partners Syngenta, Dow AgroSciences, Croplands/NuFarm, Bill Gordon Enterprises and Plant Protection Chemistry NZ Ltd.
Scott McCue was award a PhD in Applied Mathematics from the University of Queensland in May 2000. His PhD supervisor was Professor Lawrence Forbes. Scott was a Postdoctoral Research Fellow at the University of Nottingham from 2000-2001 and then at the University of Wollongong from 2002-2004. In 2004 Scott took up a position as Lecturer in Applied Mathematics at Griffith University. He moved to QUT in 2007 and is now Associate Professor in Mathematics. His research interests include fluid mechanics, heat and mass transfer, interfacial dynamics and mathematical biology.
Professor Anuj Srivastava
A Computational Framework for Statistical Shape Analysis
Shape analysis and modeling of 2D and 3D objects has important applications in many branches of science and engineering. The general goals in shape analysis include: derivation of efficient shape metrics, computation of shape templates, representation of dominant shape variability in a shape class, and development of probability models that characterize shape variation within and across classes. While past work on shape analysis is dominated by point representations -- finite sets of ordered or triangulated points on objects' boundaries -- the emphasis has lately shifted to continuous formulations.The shape analysis of parameterized curves and surfaces introduces an additional shape invariance, the re-parametrization group, in additional to the standard invariants of rigid motions and global scales. Treating re-parameterization as a tool for registration of points across objects, we incorporate this group in shape analysis, in the same way orientation is handled in Procrustes analysis. For shape analysis of parameterized curves, I will describe elastic Riemannian metrics and corresponding mathematical representations, called square-root functions, that allows optimal registration and analysis using simple tools. This framework provides proper metrics, geodesics, and sample statistics of shapes. These sample statistics are further useful in statistical modeling of shapes in different shape classes. I will demonstrate these ideas using applications from computer vision, medical image analysis, protein structure analysis, 3D face recognition, and human activity recognition in videos.
Anuj Srivastava is a Professor in the Department of Statistics at the Florida State University in Tallahassee, FL. He obtained his PhD degree in Electrical Engineering from Washington University in St. Louis in 1996 and was a postdoc at Division of Applied Mathematics at Brown University during 1996-1997. He joined the Department of Statistics at the Florida State University in 1997 as an Assistant Professor. Subsequently, he was promoted to Associate Professor in 2003 and to full Professor in 2007. He has held visiting positions at INRIA, Sophia Antipolis, France; Universit Catholique de Louvain, Belgium; and University of Lille, France. He is also a recipient of the Durham International Senior Fellowship from Durham University in UK for 2014. His areas of research include statistics on nonlinear manifolds, statistical image understanding, functional data analysis, and statistical shape analysis. He has published more than 180 papers in refereed journals and proceedings of refereed international conferences. He has been an associate editor for Journal of Statistical Planning and Inference, IEEE Transactions on Signal Processing, and IEEE Transactions on Pattern Analysis and Machine Intelligence.
Professor Mike Wilkinson
The importance of scale, plasticity and heterogeneity when describing biological systems
Professor Mike Wilkinson is Head of the School of Agriculture, Food and Wine at the University of Adelaide, Director of the Waite Research Institute, and Director of The Plant Accelerator. The UK-born research scientist, who joined the University in September 2011, is best known for his work on quantifying the risks associated with GM crops, and has published extensively in this area. Prior to immigrating to Adelaide in 2011, Professor Wilkinson established the world’s first Master of Science focused on training regulators of GM crops, a project funded by the Bill and Melinda Gates Foundation. A specialist in plant genetics, Professor Wilkinson has previously worked at the Scottish Crop Research Institute in crop research and cytogenetics, was Director of the Institute of Biological Sciences at Aberystwyth University and also Trustee of the National Botanic Gardens in Wales. He has a PhD from the University of Leicester in hybridization and evolutionary processes in wild grasses.
Associate Professor Antonio Robles-Kelly
Imaging spectroscopy for scene analysis
Imaging spectroscopy technology captures and processes image data in tens or hundreds of bands covering a broad spectral range. Compared to traditional monochrome and Red/Green/Blue (RGB) cameras, the multispectral and hyperspectral image sensors used for imaging spectroscopy can provide an information-rich representation of the spectral response of materials. In this talk, I will focus on the potential of imaging spectroscopy for scene analysis. I will explain why scene analysis in the scope of imaging spectroscopy involves the ability to robustly encode material properties, object composition and concentrations of primordial components in the scene. I will also elaborate on the use of statistical pattern recognition techniques and physics-based computer vision for shape analysis. In the talk, I will give examples of how this combination of a broad domain of application with the use of key technologies makes imaging spectroscopy a worthwhile opportunity. For surveillance, imaging spectroscopy can be used for biometrics and recognition. In computational photography, images may be enhanced taking into account each specific material type in the scene and, for food security, health and precision agriculture, fruit can be graded and pests can be detected before symptoms are apparent to the naked eye.
Antonio Robles-Kelly received the B.Eng. degree in electronics and telecommunications in 1998. In 2001 he received the William Gibbs/Plessey Award to the best research proposal and, in 2003, the Ph.D. degree in computer science from the University of York. He remained at the University of York until December 2004 as a Research Associate under the Mathematics for IT (MathFIT) initiative of the Engineering and Physical Sciences Research Council (EPSRC). In 2005, he took a research scientist appointment with NICTA.
After working on surveillance systems with query capabilities, in 2006 he was appointed project leader of the Spectral Imaging project and later promoted to Principal Researcher and Research Leader. He is also an adjunct Associate Professor at the ANU and currently serves as an Associate Editor of the IET Computer Vision and Pattern Recognition journals. His research interests are in the areas of computer vision, statistical pattern recognition, computer vision and image processing. Dr. Robles-Kelly has been a Chair, co-chair, and technical committee member of several mainstream computer-vision and pattern-recognition conferences.
Associate Professor Victor Sadras
Crop Adaptation to Elevated Temperature and Drought
The seminar outlines research of the Crop Ecophysiology team at SARDI. Current research seeks to understand the adaptation of crops to stresses. Main crops include annuals (cereals, pulses) and perennials (grapevine, olive); emphasis is placed on heat stress, water deficit and the interaction between water and nitrogen. The seminar will show changes in the phenotype of wheat crops in response to selection for yield over the last five decades. It will also outline the effects of elevated temperature on vine physiology, berry composition and wine attributes.
A/Prof. Victor Sadras is the Principal Crop Ecophysiologist with the South Australian Research & Development Institute. His research focus is the adaptation of crops to environmental stresses, including water deficit, extreme temperatures, nutrient deficit, soil physical and chemical constraints (e.g. compaction, salinity), pathogens and insects. He has measured and modelled aspects of the water, carbon and nitrogen economies of wheat, sunflower, maize, soybean, cotton, grapevine and olive in rain-fed and irrigated systems of Australia, Argentina and Spain. He is co-editor in chief of Field Crops Research, and associated editor of Crop and Pasture Science, Irrigation Science and European Journal of Agronomy. He has published 143 papers in peer-reviewed journals.
Dr Hamid Laga
Statistical Shape Analysis: Theory and Applications
Quantifying similarities and differences between shapes, referred to as shape analysis, is a fundamental problem and a building block to many applications. In biology, evolutionary relationships among living and extinct species are discovered through the analysis of morphological data obtained by measuring phenotypic properties of representative organisms. To understand ontogenetic development, speciation, or evolutionary adaptation, it is important to quantify the similarity or dissimilarity of objects affected or produced by the phenomena under study. In medical imaging, studying shapes of 3D anatomical structures in the brain and comparing their evolution to typical growth patterns are of particular interest because many diseases can be linked to alterations of these shapes. Shape similarity problem appears also in many other branches of science, including computer graphics, computer vision, biometrics, bioinformatics, geology, and anthropology. In these applications, one studies the shape of objects for modelling longitudinal changes (e.g., anatomical growth patterns), for modelling differences within and across populations (e.g., species evolution and interconnection), and for synthesizing shapes with given properties (e.g., 3D modelling and animation in computer graphics).
In this talk I will review the recent theoretical developments in the field of 2D and 3D shape analysis. I will particularly focus on our recent work on statistical shape analysis on non-linear Riemannian manifolds. In this non-linear space, shapes become points and deformations become trajectories. Geodesics (i.e., shortest paths on the manifold) correspond to the optimal amount of bending and stretching needed to align one shape onto another. The length of geodesics is a proper metric that quantifies similarities between shapes. This enables us to (1) compute shape statistics (average shapes, covariance, and high order statistics) in the shape space, (2) characterize the continuous variability in shape populations with probability models such as Gaussians or Mixtures of Gaussians, and (3) statistical inference of shapes.
I will show the application of this framework to: plant phenotyping (plant shape analysis), correspondence and registration between 3D shapes that undergo elastic deformations, 3D shape symmetrisation, 3D face recognition, and shape analysis in medical imaging.
The work described here was done in collaboration with Professor Anuj Srivastava (Florida State University) and Dr. Sebastian Kurtek (Ohio State University).
Hamid Laga received his M.Sc (2003) and PhD (2006) degrees in Computer Science from Tokyo Institute of Technology in the area of 3D shape analysis and retrieval. He is currently a senior research fellow at the Phenomics and Bioinformatics Research Centre (PBRC) of the University of South Australia working on 3D modelling of plants. Prior to Joining UniSA, Hamid worked as Associate Professor at the Institut Telecom, Telecom Lille1 in France (2010-2012), Assistant Professor at Tokyo Institute of Technology (2006-2010), and Post-Doctoral fellow at Nara Institute of Science and Technology in Japan (2006). His research interests span various fields of computer vision, computer graphics, and pattern recognition, with a special focus on the 3D acquisition, modelling and analysis of static and deformable shapes. His contributions in these fields received the Best Paper Award at the IEEE International Conference on Shape Modeling (2006), the Best Paper Award at NICOGRAPH Paper Context (2007), the International Paper Grand Prix (Best Paper Award) by the Japan Society of Art and Science (2008), and the APRS/IAPR Best Paper Prize at the IEEE International Conference on Digital Image Computing, Techniques and Applications (DICTA) 2012.