Dr Jia Wu
No more applications being accepted
Funded PhD Project (Students Worldwide)
About the Project
This project aims to develop an early prediction system to predict possible outbreaks of malicious messages in time-variant information networks. The research will primarily leverage deep representations of time-variant subsequence and substructure patterns in large-scale social networks to signal malicious and malevolent messages before it has a chance to propagate. This project will lay the theoretical foundations of this emerging field to strengthen Australia’s world leadership role in data science. Practically, the novel theories and data analytics technologies developed will help to safeguard Australian business, industry, and society from cyberfraud, online rumour-mongering, and financial loss.
Research Topics
• social networks
• graph mining
• social anomaly detection
• subgraph mining
• dynamic graph mining
• dynamic social networks
• graph neural networks
• graph embedding
• others related to social networks and graph mining
Funding Notes
Scholarship Components
Successful candidates will receive
• Tuition fee offset for 3 years maximum
• Stipend (tax exempt, indexed annually, 2020 rate AUD$28,092pa)
Requirements
• Candidates must hold or will get a Master’s degree soon in Computer Science or a relevant subject area.
• English Minimum Requirements:
IELTS (academic): overall score of 6.5 with 6 in each component
TOEFL: overall score of 92, with 17 in reading, 18 in listening, 22 in writing and 23 in speaking
• Candidates are expected to have high-quality publications in data mining, machine learning or AI areas.
References
Dr Jia Wu, ARC DECRA Fellow (Australia Discovery Early Career Researcher Award), assistant professor and Deputy Director of HDR in the Department of Computing at Macquarie University in Australia, focuses on research fields of data mining and AI. He has published 100+ papers, most of which have been published in reputed journals and top international conferences including IEEE TPAMI, IEEE TKDE, ACM SIGKDD, IJCAI, AAAI, IEEE TNNLS, IEEE TII, IEEE TCYB and ACM TKDD. He currently serves as an associate editor for reputed journals ACM TKDD and Neural Networks. His research group has won the Best Paper Award in Data Science Track (SDM 2018) and the Best Student Paper Award (IJCNN 2017).
Find more details on the homepage: http://web.science.mq.edu.au/~jiawu/
How to Apply
Please send your material including CV, transcript of Master and English Test Report to jia.wu@mq.edu.au
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