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Grant Award View - GA141132-V2
Causal Discovery from Unstructured Data
GA ID:
GA141132-V2
Agency:
Australian Research Council
Approval Date:
1-Dec-2020
Variation Publish Date:
14-Oct-2021
Variation Date:
12-Oct-2021
Category:
Science, Technology, Engineering and Mathematics (STEM) Research
Grant Term:
1-Jan-2021 to 31-Dec-2023
Value (AUD):
$410,775.00
(GST inclusive where applicable)
Varies:
GA141132
- Causal Discovery from Unstructured Data
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:
Causal Discovery from Unstructured Data
Purpose:
This Project aims to enable machines to discover causal relations from various kinds of unstructured data, such as images, text files, and sensor data. The project expects to promote causal revolution of data-centric intelligence and science – construct machines that can communicate in the language of cause and effect and answer ‘why’ questions by inferring from unstructured data. Expected outcomes of this project include theoretical foundations for causal discovery from unstructured data and practical algorithms that drive intelligent machines to make rational decisions in real-world scenarios. This should benefit society and the economy nationally and internationally through the applications of artificial intelligence and data science.
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 Melbourne
Recipient ABN:
84 002 705 224
Grant Recipient Location
Suburb:
UNIVERSITY OF MELBOURNE
Town/City:
UNIVERSITY OF MELBOURNE
Postcode:
3010
State/Territory:
VIC
Country:
AUSTRALIA
Grant Delivery Location
State/Territory:
VIC
Postcode:
3010
Country:
AUSTRALIA