Mr. Glen Charlton1, Dr. Jiaxin Fan1, Mrs. Marium Khan1, Dr. Paul Meek2, Associate Professor Guy Ballard3, Dr. Anastasios Papaioannou1, Dr. Jonathan Athur1
1Advanced Analytics and AI Platform, Intersect Australia, Australia, 2Vertebrate Pest Research Unit, NSW Department of Primary Industries, Australia, 3School of Environmental and Rural Science, University of New England, Australia
Biography:
Glen holds a BSc in Engineering Science and MSc in Science. He has over 10 years experience in applying Data Science and Electronics Engineering to commercial and research projects in the fields of Sport Science, Environmental Management and Animal Science. Glen established a research track record demonstrating the application of data science within projects at the University of New England and more recently within the 3AI team at Intersect. Glen has a number of published articles and involvement in conference submissions in the application of Data Science in multiple disciplines. Glen’s professional interests are in applying Data Science and other technology (in particular sensor and time-series data) to improve the efficiency and increase the capability of research projects to conduct novel and practically relevant research. Specifically for this project, Glen has extensive experience working within research projects involving time-series sensor data, real-time data pipelines, and deep-learning with image data. As Intersect’s Senior Research Data Scientist, Glen undertakes the Data Science services provided by Intersect’s Advanced Analytics & AI (3AI) Platform and the Data Science Team.
Abstract:
Introduction: The complex nature of data-intensive research requires domain experts (e.g. ecologists) alongside skills and expertise in data science and Artificial Intelligence (AI). Intersect’s Advanced Analytics and AI Platform (3AI) works closely with researchers across Australia providing hands-on support to advance research and bridge the knowledge gap to data science and AI. An example of this is a collaborative partnership as part of the Practical Ecology, Science and Technology Research Group (PEST) (NSW Department of Primary Industries, University of New England, Intersect) to develop research tools, apply for funding, and publish valuable research outputs.
Methods: 3AI leverages Intersect's existing research infrastructure and provides access to a dedicated team of research-focused data scientists and AI experts via flexible full-time, part-time, and project-based arrangements. Intersect has been collaborating on a part-time basis with PEST for more than 12 months providing access to the expertise of multiple members of the 3AI team.
Results: The ongoing partnership with PEST involves working collaboratively in: (1) developing cost-effective research-ready tools, (2) applying for research funding, (3) researching practical uses of AI, and (4) automating the collection and processing of data. This enables stable, sustainable, and scalable research in vertebrate pest management along with the translation to practical and impactful outcomes for the research community and society.
Conclusion: Intersect has developed a platform (3AI) to bridge the gap between the knowledge of domain experts and research-relevant expertise in data science and AI to sustainably advanced research and increase the capacity and capabilities of research groups (e.g., PEST).