4 Research Park Drive
Macquarie University NSW 2109
Competitive research and collaboration
Our cutting-edge and impactful research is funded by ARC and other competitive grants alongside industry collaborations.
Learn more about the artificial intelligence (AI) projects our researchers are currently involved in.
An intelligent modelling assistant for combinatorial optimisation
Funding: Australian Research Council Discovery Project
This project aims to discover key fundamental technologies for automating assistance to non-expert users in the formulation of mathematical models.
Through automating the modelling of combinatorial optimisation problems, this research will generate new knowledge to address the fundamental challenges of automatic mathematical modelling. This intelligent assistant will enable synthesis of new mathematical models through the utilisation of:
- natural language processing components
- novel custom-made machine-readable knowledge bases.
The outcome of this research will broaden access to high-quality models by non-expert workforce and alleviate the shortage of expert mathematicians, bringing significant social and economic benefits.
- Vicky Mak
- Diego Molla-Aliod
- Bahadorreza Ofoghi
- John Yearwood
- Joyce Zhang
Trust-oriented data analytics in online social networks
Funding: Australian Research Council Discovery Project
Trust-oriented data analytics is essential in online social networks for reducing deceitful interactions and enhancing trust between users. This project aims to systematically devise innovative solutions by considering rich social contextual information as an important source of trust.
The expected outcomes of this project include innovative solutions from a fundamental perspective to the challenges of:
- context-aware trust propagation
- trust network searching/matching
- trustworthy/malicious user prediction in online social networks.
This project is significant as it will advance the knowledge base for enabling a trustworthy social networking environment, benefiting billions of Australian and worldwide online social network users.
- Guanfeng Liu
- Mehmet Orgun
- Kian-Lee Tan
- Yan Wang
Data complexity and uncertainty-resilient deep variational learning
Funding: Australian Research Council Discovery Project
Enterprise data present increasingly significant characteristics and complexities, such as:
- multi-aspect, heterogeneous and hierarchical features and interactions
- evolving dependencies and multi-distributions.
These complexities continue to significantly challenge the state-of-the-art probabilistic and neural learning systems with limited to insufficient capabilities and capacity.
This research aims to develop a theory of flexible deep variational learning transforming new deep probabilistic models with flexible variational neural mechanisms for analytically explainable, complexity-resilient analytics of real-life data. The outcomes are expected to fill important knowledge gaps and lift critical innovation competencies in wide domains.
- Longbing Cao
- Joao Gama
Federated omniverse facilities for smart digital futures
Funding: Australian Research Council Linkage Infrastructure, Equipment and Facilities scheme
A world-first trans-disciplinary, -domain, and -institutional smart 3D omniverse R&D ecosystem, AuVerse, will be built in New South Wales, affiliated with Queensland, and accessible to academia and industry. AuVerse will support digital design, development, training and society that is:
- cloud-based
- reality-virtuality-fused
- immersive
- interactive
- secure
- future-oriented.
In the new era of digital innovation and paradigm shift, AuVerse will substantially boost Australia’s pivotal research leadership and business competitiveness in nurturing new-generation, collaborative and transformative digital R&D and talent pipeline. It will enable large-scale strategic business innovation and transformation including smart manufacturing and Industry 4.0.
- Amin Beheshti
- Longbing Cao
- Patricia Davidson
- Sankalp Khanna
- Jinman Kim
- Quang Vinh Nguyen
- Vijay Varadharajan
- Ping Yu
Ethical enterprise representations for personalised sustainable finance
Funding: Australian Research Council Linkage Project
The rapidly evolving field of sustainable finance requires responsible services that satisfy environmental, social and governance (ESG) criteria. This requires disruptive FinTech innovations – ethical enterprise learning from whole-of-business financial data. However, the corresponding valid theories and industrial solutions are unavailable.
We aim to develop forward-looking ESG-integrated enterprise learning theories and tools to represent and analyse entire businesses and data, and develop novel ESG ratings and ESG-efficient investment solutions. These will:
- advance knowledge and capabilities in enterprise AI and sustainable finance
- transform financial services
- enhance Australia’s leadership in FinTech research and innovation.
- Di Bu
- Longbing Cao
- Xuhui Fan
- Yin Liao
- Vito Mollica
- Alberto Rossi
- Jing Sun
Early sleep interventions to improve outcomes in children with neurodisability
Funding: National Health and Medical Research Council
Sleep disorders affect up to 80 per cent of children with neurodisability (ND), can occur at any age, and are more severe and pervasive in children with ND than in typically developing (TD) children. Poor sleep exacerbates existing learning and behaviour difficulties, impacting the health and well-being of the entire family.
A tailored approach to sleep problems is required in children with ND, but there is limited evidence in this field. The objective of this research is to improve the diagnosis and aspects of management of sleep difficulties in children with ND, aiming to improve quality of life and outcomes for them and their families.
Findings will be translated into clinical guidelines and develop national standards of care for this population.
- Jasneek Chawla
- Maree Milross
- Natalia Pride
- Deborah Richards
- Moya Vandeleur
- Karen Waters