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Grant Award View - GA141229

Graph Neural Networks for Efficient Decision-making towards Future Grids

Contact Details

ARC NCGP General Enquiries

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02 6287 6600

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GA ID:
GA141229
Agency:
Australian Research Council
Approval Date:
1-Dec-2020
Publish Date:
8-Dec-2020
Category:
Science, Technology, Engineering and Mathematics (STEM) Research
Grant Term:
22-Mar-2021 to 22-Feb-2024
Original: 1-Jan-2021 to 31-Dec-2023
Value (AUD):
$415,675.00 (GST inclusive where applicable)
Variations:

One-off/Ad hoc:
No
Aggregate Grant Award:
No

PBS Program Name:
ARC 20/21 Discovery
Grant Program:
Discovery Early Career Researcher Award
Grant Activity:
Graph Neural Networks for Efficient Decision-making towards Future Grids
Purpose:
This project aims to develop a breakthrough framework for decision-focused learning by integrating explainable graph neural networks and efficient computational methods. It expects to create new methodologies of graph representation learning for unlocking data insight with spatiotemporal knowledge while to build new accelerated optimisation theories for speeding up decision-focused learning model. The expected outcomes will advance big spatiotemporal data analytics and nonlinear optimisation theory for solving decision-making tasks towards a future energy system. This should promote the Australian power industry transition to a sustainable future grid based on a digitalisation approach to efficient energy management against climate changes.

GO ID:
GO Title:
Discovery Early Career Researcher Award for funding commencing in 2021
Internal Reference ID:
DE21 Round 1
Selection Process:
Targeted or Restricted Competitive

Confidentiality - Contract:
No
Confidentiality - Outputs:
No

Grant Recipient Details

Recipient Name:
The University of New South Wales
Recipient ABN:
57 195 873 179

Grant Recipient Location

Suburb:
KENSINGTON
Town/City:
KENSINGTON
Postcode:
2033
State/Territory:
NSW
Country:
AUSTRALIA

Grant Delivery Location

State/Territory:
NSW
Postcode:
2033
Country:
AUSTRALIA

Contact Details

ARC NCGP General Enquiries

:
02 6287 6600

: