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DECRAs

The Discovery Early Career Researcher Award (DECRA) scheme provides research support for outstanding early career researchers.
  • Adaptive value-flow analysis to improve code reliability and security (DE170101081) –  Yulei Sui
    (1 Jan 2017 - 29 Feb 2020)

  • Intelligent bibliometrics for tracking and predicting technological change (DE190100994)  –  Yi Zhang
    (1 Jan 2019 - 20 Nov 2022)

  • Towards extreme object detection (DE190101315) –  Yunchao Wei 
    (10 May 2019 - 18 August 2021)

  • Bayesian nonparametric learning for practical sequential decision making (DE200100245) –  Junyu Xuan
    (1 May 2020 - 30 April 2024)

  • Dimension-reduced Reinforcement Learning for Large-scale Fleet Management (DE200101310) –  Wei Bian
    (4 June 2021 - 3 June 2027)

  • Fuzzy transfer learning for real-time decision making under uncertainty (DE220101075) –  Hua Zuo
    (1 Jan 2022 – 31 Dec 2024)

  • Towards Transferable Visual Understanding in the Real World (DE220101379) –  Guoliang Kang
    (1 Jan 2022 – 31 Dec 2024)

  • Towards Human-like Machine Perception for Embodied AI (DE220101390) –  Wenguan Wang
    (15 Aug 2022 – 2 March 2023)

  • Structured Federated Learning for Personalised Intelligence on Devices (DE230100495) –  Jing Jiang
    (1 Jan 2023 – 31 Dec 2025)

  • Advancing Human Perception: Countering Evolving Malicious Fake Visual Data (DE230100477) –  Xin Yu
    (1 June 2023 – 31 May 2026)

  • Transfer learning for reliable data detection in Open-set environments (DE250100363) - Zhen Fang 

Future Fellowships (FT)

The Future Fellowships Scheme provides four year fellowships to outstanding Australian mid-career researchers to undertake high quality research in areas of national and international benefit.
  • Effective, efficient and scalable processing of big geo-textual streams (FT170100128) –  Ying Zhang
    (6 Dec 2017 – 5 Dec 2021)

  • Taming Large-Volume Dynamic Graphs in the Cloud (FT200100787) –  Lu Qin
    (30 June 2021 – 29 June 2025)

  • Learning Software Security Analysers with Imperfect Data (FT220100391) – Yulei Sui
    (30 June 2023 – 29 June 2027)

  • Situated Anomaly Detection in an Open Environment (FT230100121) – Ling Chen
    (30 June 2024 – 29 June 2028)

Discovery Projects (DP)

The Discovery Project Scheme (DP) funds individual researchers or research teams to undertake research which promises to expand knowledge base and research capacity in Australia, with economic, commercial, environmental, social and/or cultural benefits.
  • Cross-domain knowledge transfer for data-driven decision making (DP170101632) –  
    Jie Lu; Guangquan Zhang; Witold Pedrycz
    (1 Jan 2017 – 31 May 2020)

  • A neural fuzzy engine for human-machine autonomous systems (DP180100670) –  
    CT Lin; Nikhil Ranjan Pal
    (1 Jan 2018 – 31 Dec 2020)

  • Towards interpretable deep learning with limited examples (DP180100106) –  
    Ivor Tsang; Yi Yang; Alexander Hauptmann
    (1 Jan 2018 – 31 Dec 2021)

  • Cognitive Intelligent Information Processing and Presentation in Navigation (DP180100656) –  
    CT Lin; Tzyy-Ping Jung; Klaus Gramann
    (1 Jan 2018 – 31 Dec 2021)

  • Large-scale spatio temporal data hashing for efficient data analytics (DP180100966) –  
    Chengqi Zhang; Ling Chen; Phillip Yu
    (1 Jan 2018 – 31 Dec 2022)

  • Characterisation of amorphous metal materials (DP180100470) –  
    Youguang Guo; Junwei Lu; HaiYan (Helen) Yu
    (1 Jan 2018 – 31 Dec 2023)

  • Drift learning for decision-making in dynamic multi-stream environments (DP190101733) –  
    Jie Lu; Guangquan Zhang; Junyu Xuan; Witold Pedrycz
    (19 June 2019 – 30 Sep 2022)

  • Adversarial Learning of Hybrid Representation (DP200101328) –  
    Ivor Tsang; Yulei Sui; Yang Liu; Klaus-Robert Mueller
    (1 Jan 2020 – 31 Dec 2023)

  • Automatic Machine Learning with Imperfect Data for Video Analysis (DP200100938) –  
    Yi Yang; Yunchao Wei; Thomas Huang
    (1 May 2020 – 31 March 2024) 

  • Sequential decision-making in dynamic and uncertain environments (DP200100700) –  
    Jie Lu; Guangquan Zhang; Zheng Yan; Jun Wang; Witold Pedrycz 
    (1 June 2020 – 31 Dec 2023)

  • Brain Robot Interface for Physical Human Robot Collaboration (DP210101093) –  
    CT Lin; Dikai Liu; Klaus Gramann
    (1 Jan 2021 – 31 Dec 2023)

  • Targeted Graph Embedding for Anomaly Detection in Large-Scale Networks (DP210101347) –  
    Ling Chen; Lu Qin; Huan Liu
    (1 Jan 2021 – 31 Dec 2023)

  • Efficient and Scalable Similarity Query Processing on Big Streaming Graphs (DP210101393) –  
    Ying Zhang; Wenjie Zhang 
    (1 Jan 21 – 31 Dec 23 )

  • Learning to Pinpoint Emerging Software Vulnerabilities (DP210101348) –  
    Yulei Sui; Ling Chen
    (1 Jan 21 – 31 Dec 24 )

  • Taming Large-Volume Dynamic Graphs in the Cloud (DP240101322) –  
    Lu Qin
    (30 June 2021 - 29 June 2025)

  • Robust Federated Learning for Imperfect Decentralised Data (DP220100768)  –  
    Chengqi Zhang; Guodong Long; Jing Jiang
    (1 Jan 2022 – 31 Dec 2024)

  • AI-Human Empowered Team Decision-Making (DP220100803) –  
    CT Lin; Nikhil Ranjan Pal; Tzzy-Ping Jung
    (1 Jan 2022 – 31 Dec 2024)

  • Interpretable Behaviour Analyssi with External Structured Knowledge (DP220100769) –  
    Michael Blumenstein; Guodong Long
    (1 Jan 2022 – 31 Dec 2024)

  • Robust meta learning for risk-aware recommender systems (DP220102635) –  
    Guangquan Zhang; Junyu Xuan; Qian Zhang; Witold Pedrycz 
    (3 Oct 22 – 2 Oct 2025)

  • Advanced Machine Learning with Bilevel Optimization (DP230101540)  –  
    Guangquan Zhang; Feng Liu; Hua Zuo
    (1 June 2023 – 31 May 2026)

  • Toward Human-guided Safe Reinforcement Learning in the Real World (DP240102349) –  
    Ling Chen; Lina Yao
    (Pending establishment)

  • Next-Generation Distributed Graph Engine for Big Graphs (DP240101322) –  
    Lu Qin; Ying Zhang; Xiaoyang Wang
    (Pending establishment)

  • Mitigating the Influence of Social Bots in Heterogeneous Social Networks (DP240100181) –  
    Xiaojun Chang; Wenguan Wang; Lina Yao
    (Pending establishment)

Linkage Projects (LP)

The ARC Linkage Program promotes national and international research partnerships between researchers and business, industry, community organisations and other publicly funded research agencies.
  • Dialogue-to-Action: Towards A Self-Evolving Enterprise Intelligent Assistant (LP180100654) –  
    Chengqi Zhang; Guodong Long; Xianzhi Wang; Jing Jiang; 
    (1 Dec 2019 – 31 Dec 2023)

  • Transfer Learning for Genome Analysis and Personalised Recommendation (LP210100414) –  
    Jie Lu; Guangquan Zhang; Yi Zhang; Qian Zhang; Hua Lin 
    (1 Jul 2021 – 30 Jun 2024)

  • Effective, efficient and scalable processing of the graph of graphs (LP210301046) –  
    Ying Zhang; Lu Qin; Christy Jie Liang; Yiguang Lin
    (2 Oct 2023 – 1 Oct 2026)

Australian Laureate Fellowships (FL)

The ARC’s prestigious Australian Laureate Fellowships scheme promotes excellence in research by supporting world-class Australian and international researchers to conduct research in Australia and to build Australia’s research capacity, undertake innovative research programs and mentor early career researchers.

Learn more: Autonomous Learning - ARC Laureate project by Jie Lu

Autonomous learning for decision making in complex situations (FL190100149)
Jie Lu
(1 Jan 2020 – 31 Dec 2024)

 

ARC Grants (non UTS-led)

Griffith University led: Developing a Truly Intelligent Water Meter through Advanced Data Analytics (LP160100215) – Rodney Stuart, Michael Blumenstein, Hong Zhang, Damian Giurco, Kumbesan Sandrasegaran, Dragan Savic, Christopher Jones

Griffith University led: Economically Efficient Green Logistics through Cyber Physical Systems (LP160100080) – Elizabeth Chang, Omar Hussein, Farookh Khadeer Hussain, Naeem Junjua, Clifford Woodward, Tim Jensen 

UNSW led: Efficient Processing of Large Scale Multidimensional Graphs (DP180103096) – Xuemin Lin, Wenjie Zhang, Ying Zhang 

ANU Led: Two-way Auslan: Automatic Machine Translation of Australian Sign Language (DP220100800) – Hongdong Li; Xin Yu

 

Acknowledgement of Country

UTS acknowledges the Gadigal People of the Eora Nation and the Boorooberongal People of the Dharug Nation upon whose ancestral lands our campuses now stand. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands. 

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