Dr Alan Woodley

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PhD (Queensland University of Technology)

Dr. Alan Woodley is the leader of the Spatial Informatics Laboratory and a Senior Lecturer in the School of Computer Science. He has a background in data and computer science with a Bachelor of Information Technology and a Ph.D. from QUT.

Research

His research has focussed on applying efficient ‘big data’ solutions covering data analytics, computational modeling, and visualisation. His work has been applied to the mining and environmental domains and has developed research frameworks and tools to improve industrial sustainability and to bridge the social-technical divide. He has obtained research funding of over 4 million dollars and published over 70 articles.

Education

  • Massachusetts Institute of Technology, Certificate in New Ventures Leadership, MIT Innovation and Entrepreneurship Bootcamp, 2018
  • Queensland University of Technology, Doctor of Philosophy, 2008
  • Queensland University of Technology, Bachelor of Information Technology (Hons),  2003
  • Queensland University of Technology, Bachelor of Information Technology,  2003

Experience

  • Senior Lecturer, Queensland University of Technology, 2018 - Current
  • Vice Chancellor’s Research Fellow, Queensland University of Technology, 2018 - 2019
  • Lecturer, Queensland University of Technology, 2017
  • Research Fellow, Queensland University of Technology, 2014 - 2016
  • Postdoctoral Research Fellow, Sustainable Minerals Institute, The University of Queensland, 2008 - 2014

Current Roles

  • Senior Lecturer, School of Computer Science, Faculty of Science
  • Associate Investigator, Centre for Agriculture and the Bioeconomy
  • Associate Investigator, Australian Data Science Centre
  • Associate Investigator, ARC Centre of Excellence for Mathematical & Statistical Frontiers

Additional information

Experience

Dr. Woodley has spent over the past decade working with industry, Some of his success stories include working with:

  • The Yarrabilba community, Lendlease and Food Agility CRC to produce a community compost application.
  • Working with the Bonneville Power Association, a subsidiary of the US Department of Energy,  to produce a salmon monitoring tool.
  • The Queensland government and Frontier-SI to produce a high-dimensional  land change application.
  • Represents of Queensland, New South Wales, Victoria and Western Australia to work with data analytics of remote sensing algorithms.
  • Working with representatives of resource industry to help with their water issues.

Awards

Type
Funding Award
Reference year
2021
Details
Awarded $584 from the Food Agility CRC for the development of a Circular Food Economy Digital Framework. Our goal was to implement a food waste and composting system in the Yarrabilba State Secondary College. My focus was to manage the implementation of a Mobile App aimed at students in years 7 and 8. The project helped to establish a relationship between the school and social enterprise SubStation 33. Their relationship continued after the project with SubStation 33 donating computers to the school (https://www.abc.net.au/news/2022-01-30/qld-laptop-stress-yarrabilba-state-high-school/100781648).
Type
Funding Award
Reference year
2021
Details
Funding of $149K from the Bonneville Power Administration (a subsidiary of the US Department of Energy) for the project "Analysis of Spatial Stream Networks for Salmonids: Phase 2".This project required us to develop an open source version of our system.
Type
Fellowships
Reference year
2018
Details
Awarded a prestigious 3-year Vice Chancellor's Research Fellowship in Digitial Agriculture. The Fellowship will join together farm sensors, computational models, and visualizations. The Fellowship will explore how uncertainty is passed from sensors to models and how models can better deal with streaming data.
Type
Funding Award
Reference year
2017
Details
Funding of $200K from the CRC for Spatial Information (Category 4: Australian Competitive Grant) for the project "Change Detection System from High-Resolution Satellite Images (CDS)". The project uses high resolution (