Read on to find out more about the seminar abstracts and biographies of our researchers here at the Phenomics and Bioinformatics Research Centre.
Dr 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.