Designing data innovations that drive new discoveries
In all areas of science, health and society, the unparalleled growth in the volume, velocity and variety of data offers opportunities to transform approaches to research, make new discoveries and deliver new insights.
These opportunities can only be realised if there is a commensurate development of new data science methods – able to draw together this data to enable a new understanding of complex and integrative physical, life and social systems.
About us
DataX Research Centre is developing new methods in data science and enabling new research in a range of challenging application domains. They include:
- areas where new data science methods can drive a profound transformation in research, understanding and decision-making
- areas such as business forecasting and sustainable investment, predictive and personal health, archaeology, law and more.
Our research themes
Models and Algorithms in Data Science and Artificial Intelligence
Develop data-driven learning models to enable various forms of intelligence such as mental, perceptual, neural-symbolic, conservation-oriented, nature-inspired, interactive, and behavioral. Advance frontier theories and algorithms for a deep understanding of and managing data complexities, aiming to build trustworthy artificial intelligence.
People: Data scientists in mathematics, statistics, computing, and other schools.
Data for Science and Engineering Innovation
Pursue data-driven discovery across natural, physical, astronomical, biological, biomedical, and engineering fields; foster collaborations to unlock insights from complex scientific datasets. Research could encompass areas like climate change modelling, drug discovery, genetics research, and the visualization of scientific concepts through art.
People: Researchers in natural sciences, astronomy, engineering, medical sciences, psychological sciences, and Cochlear.
Health and Medical Analytics
Explore how data-driven approaches can enhance patient care, treatment outcomes, and healthcare operations. Collaborate with health professionals, implementation scientists, economists, and medical administrators to develop new insights into personalized medicine, predictive disease modelling, telemedicine effectiveness, and healthcare policy.
People: Researchers in Macquarie Business School, Australian Institute of Health Innovation (FMHHS), Clinical Trials, Department of Health Professions (FMHHS), and Macquarie Medical School.
Smart and Digital Business and Enterprise Innovation
Develop transdisciplinary techniques for smart business and digital enterprise innovation. Investigate how data analytics can drive business growth, improve decision-making, and foster innovation. Combine expertise from business experts, artists, and health professionals to explore market trends, customer behaviour, supply chain optimization, and sustainable business practices. Focus also on domain-oriented data science and AI for FinTech, disaster management, insurance products, pension policies, and enterprise transformation.
People: Researchers in business, engineering linguistics, media, communications, creative arts, language, and literature.
Technology Security, Regulation and Governance
Analyze the governance, regulatory, and ethical implications of data and technology, including AI and data systems, across all domains. Address issues such as designing technical systems to support regulatory compliance and governance frameworks to mitigate bias and ensure safety, privacy, security, and proper data ownership. Provide a cross-disciplinary analysis and diverse perspectives on the societal impacts of AI advancements.
People: Researchers in law, business; media, communications, creative arts; language and literature; ethics & agency.
People and Societies
Develop and apply new analytical approaches to gain insights into the human world. This research will examine data-related challenges in organisations and society, including data humanism, data justice, data sovereignty, data-driven & data-informed algorithmic decision making in society, and human communication in all its forms, from ancient writings to social media, to better understand how groups come together to share experiences, identities, and objectives. Topics will include unintended data harm and data justice, visual data exploration of human-related data, group dynamics and teamwork, recruitment and radicalization, trends, memes, and language.
People: Researchers in business, linguistics, performance & expertise, psychological sciences, security studies & criminology, media, communications, creative arts, language & literature, critical indigenous studies.
