Track Co-Chairs
Aneesh Krishna, Curtin University
Madhushi Bandara, University of Technology Sydney
Yunfei Shi, University of New South Wales
Track Description
The goal of the Data Analytics and Artificial Intelligence track is to advance the knowledge of understanding data analytics and Artificial Intelligence (AI) technologies and using them for positive impacts of the society from both economic and humanistic perspectives.
The emphasis of this track is on how individual and organisational knowledge can be distilled from data and be incorporated into business and social contexts for effective decision-making, and their broader implications to organisations and communities. We welcome submissions that offer significant theoretical and practical contributions to these aspects.
This track accepts both conceptual and empirical manuscripts, and teaching cases in the areas of interest. This track is open to various research methods, and accepts completed research papers, as well as research-in-progress papers.
Areas of interest include:
- Design, development, and use of analytics and AI to support innovative data-driven decisions and strategies
- Human factor considerations in developing data-driven systems including advancement in methodologies
- Analytical tools and techniques, such as text analytics and sentiment analysis, and their applications in a relevant domain
- Advancement in visualisation of structured and unstructured data and knowledge
- Velocity and real-time analysis of big data that facilitates decision-making at the individual, organisational, and societal levels
- Integration of data analytics and AI for strategic decision-making leading to economic propensity and sustainable future
- Adoption and implementation of data analytics and AI tools at the workplace, and their implications for workforce development
- Governance of data analytics and AI technologies and their implications for policies
- Responsible data analytics and AI including fairness, trustworthiness, accountability, and human-centered design