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  • Home
  • About
    • Vision & Mission
    • Join OzGrav
    • Mental Health and Wellbeing
    • Getting started in OzGrav
    • Funding Opportunities
    • Diversity and Inclusion
    • Code of Conduct
    • OzGrav Mentoring Program
    • Nodes & Partners
    • Facilities & Capabilities
    • Reports >
      • Annual Reports
      • Industry Success Stories
      • Strategic Plan
    • Member resources
  • Our People
    • Chief Investigators
    • Partner Investigators
    • Associate Investigators
    • Postdocs and Students >
      • Faces of OzGrav
    • Professional & Outreach staff
    • Governance Advisory Committee
    • Scientific Advisory Committee
    • Executive Committee
    • Equity & Diversity Committee
    • Early Career Researcher Committee
    • Professional Development Committee
    • Research Translation Committee
    • OzGrav Alumni
  • Research Themes
    • Instrumentation
    • Data/Astro
    • How to write a research brief
  • Education and Outreach
  • Events
    • OzFink workshop 2023
    • 2022 OzGrav ECR Workshop and Annual Retreat
    • Upcoming and Past Events
  • News/Media
    • News
    • Newsletter
    • Binary Neutron Star Discovery
  • Contact Us

CERA-Swinburne BIG DATA workshop

When: 9am-12:30pm Friday 21st July 2017
Where: Swinburne University, VR Theatre, Hawthorn VIC 3122 (directions)
What: Swinburne is hosting an interdisciplinary workshop with the Centre for Eye Research Australia (CERA). The theme of the workshop is “Big Data” and we will explore cross-sectoral collaboration in a morning of talks and networking.  
Registration: Spaces are very limited so please register to attend here. 

Program

Time
Session
09:00-09:05
​Swinburne DVC-R&D Aleksandar Subic (Swin): Welcome  and workshop opening
09:05-09:20
​Matthew Bailes (Swin): Gravitational Wave Discovery
09:20-09:40
Peter van Wijngaarden (CERA): Hyperspectral imaging
09:40-10:00
Chris Fluke (Swin): Visualisation ​
10:00-10:25
Morning Tea
10:25-10:45
Mingguang He (CERA): Automated retinal grading
10:45-11:05
Feng Wang (Swin): Computational chemistry
11:05-11:25
Paul Baird (CERA): Genomic sequencing
11:25-11:45
Jarrod Hurley (Swin): Supercomputing + Colin Jacobs (Swin): Machine learning
11:45-12:00
Matthew Bailes (Swin): wrap-up and next steps
12:00-12:30
Lunch

Abstracts

Speaker: Matthew Bailes
Title: Gravitational Wave Discovery
​Abstract: 100 years after Einstein's completed his masterpiece, the General Theory of Relativity, astronomers used an amazing apparatus (LIGO) to detect the gravitational waves from two merging black holes a billion light years away as, for a brief fraction of a second they outshone every star in the Universe put together. In this talk, Professor Matthew Bailes, the Director of the new Australian Research Council Centre of Excellence for Gravitational Wave Discovery (OzGrav), will describe how astronomers observe the relativistic universe, the computational challenges of detecting these elusive signals amongst petabytes of data, and what these observations are revealing about the Universe.
Speaker: ​Peter van Wijngaarden
​Title: Satellite imaging technology to detect the early signs of glaucoma and Alzheimer’s disease in the retina ​
Abstract: We aim to be the first group in the world to bring hyperspectral imaging, based on NASA satellite technology, to the clinic to improve the care of Australians with glaucoma, a leading cause of blindness, and Alzheimer’s disease, the leading cause of dementia. The deposition of abnormal proteins in the retina in Alzheimer’s disease and structural changes in the nerve cells affected by glaucoma scatter light in characteristic ways which we can detect with our camera during the early stages of disease. We will validate our approach by imaging people with early stage glaucoma and those with Alzheimer’s disease.
Speaker: Chris Fluke
Title: Visualising the Universe
Abstract: The volume and velocity of modern astronomical datasets poses many challenges for visualisation based knowledge discovery.   Swinburne University’s Centre for Astrophysics & Supercomputing is tackling these challenges using accelerated architectures, novel displays, and virtual reality.  I will present an overview of our recent work including visualising terabyte-scale hyperspectral data cubes (from radio astronomy), GPU-based shading for visualisation and analysis, and a simple workflow for creating immersive virtual reality experiences and interactive PDF figures as a way to communicate, share and explore multi-dimensional datasets.

Speaker: Mingguang He
Title: Integration of retinal photography and artificial intelligence to build an opportunistic screening service
Abstract: More than 500,000 Australian adults suffer from vision impairment or blindness. While 80% of vision loss is avoidable through early detection, prevention and treatment strategies, up to 50% of major eye diseases remain undiagnosed in Australia. However, identification of disease from retinal photographs is highly dependent on interpretation by trained professionals. Using deep learning technology, we have developed the first fully automated artificial intelligence retinal grading and diagnosis system for the major eye diseases of diabetic retinopathy, glaucoma, age-related macular degeneration and cataract, which enables immediate and accurate reporting of results.
​
This project seeks to combine the accuracy and efficiency of our novel grading system with the accessibility of GP and endocrinology clinic-based screening to create an automated opportunistic screening model that will facilitate earlier detection of eye diseases and improved patient outcomes.
​
Speaker: Feng Weng
Title: Computer aided study for properties of drugs
Abstract: The coming fourth industrial revolution will be digital and computer simulation driven. Physical properties of almost all materials should be predictable, in principle, by solving the quantum-mechanical equations governing their constituent electrons. One needs to understand insight and rational of the properties and structures of drugs, in order to achieve inverse design for new drugs with given functions and properties. In this presentation, I will discuss computer aided study for properties of a number of small radiosensitisers, chromophore anti-cancer drugs as optical reporting tool and chirality of resveratrol, the red wine molecule.
Speakers: Paul Baird and Adam Kowalczyk
​Title:
Big data in the genomics world
​Abstract: Data driven enterprises arising through genomic studies are rapidly increasing. Firstly, through the onset of genome wide association studies (GWAS) to whole -exome and -genome sequencing (WES and WGS) to genome wide interaction search (GWIS). In the blinding disease age related macular degeneration (AMD) we have used all these techniques with the aim of identifying genetic variants associated with different aspects of disease. In this regard, GWAS and WES have been used to identify variants contributing to pharmacogenetic response in AMD. In another aspect, we have taken the analysis of genetic variants to the next level using the world’s largest AMD study of 40,000 people from multiple cohorts along with the development of the novel statistical tool (GWIS) - a high throughput computational model. This allows us to look at all genes in our genome and identify gene regions that interact with each other in the 2 main types of AMD. These analyses will provide important information regarding insight into disease biology and towards delivering precision medicine to better treat disease.
Speaker:Jarrod Hurley
​Title: Supercomputing
​Abstract: This talk will provide an overview of the Swinburne supercomputing program from the beginning as a beowulf PC cluster within the Centre for Astrophysics & Supercomputing to a petascale national facility, highlighting the focus on GPU programming, data delivery and future plans for integration with cloud computing.
Speaker: Colin Jacobs
Title: Classifying Astronomical Images using Artificial Neural Networks
Abstract: Einstein's General Theory of Relativity predicts that massive objects such as galaxies will bend light around them, creating so-called "gravitational lenses". These have been discovered, and can teach us much about the cosmos, but they are a rare phenomenon. Finding a few thousand of these objects amongst hundreds of millions of galaxies is a challenge worthy of the latest techniques in computer vision and data mining. I will describe convolutional neural networks, a very successful computer vision algorithm, and their application to finding these lenses in a database of scientific images.
 

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We acknowledge and pay respects to the Elders and Traditional Owners of the land on which our six Australian nodes stand

​© 2022   The ARC Centre of Excellence for Gravitational  Wave Discovery (OzGrav)
Banner images: An artist's impression of gravitational waves generated by binary neutron stars.  Credits: R. Hurt/Caltech-JPL
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