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Grant Award View - GA2353

Vector network system identification

Contact Details

ARC NCGP General Enquiries

Phone:
02 6281 6600

Email Address:

GA ID:
GA2353
Agency:
Australian Research Council
Approval Date:
10-Nov-2017
Publish Date:
20-Feb-2018
Category:
Science, Technology, Engineering and Mathematics (STEM) Research
Grant Term:
1-Jan-2018 to 31-Dec-2020
Value (AUD):
$352,616.00 (GST inclusive where applicable)

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

PBS Program Name:
ARC 17/18 Discovery
Grant Program:
Discovery Projects
Grant Activity:
Vector network system identification
Purpose:
This machine learning project aims to provide more reliable ways to identify the structure and function of dynamic networks from both continuous and discrete network data. The project will use all the data and create principled new metrics. This could enable early diagnosis of network faults across a range of applications for example in power systems or diseased human brains. It could also enable discovery of critical functional subnetworks affecting reliable operation in large complex human systems (such as financial systems) or natural systems (such as gene regulatory networks).

Internal Reference ID:
DP18 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

Phone:
02 6281 6600

Email Address: