Discovery Early Career Researcher Award - Grant ID: DE230101281
Funder
Australian Research Council
Funding Amount
$329,278.00
Summary
An Efficient Computational Solver for Complex Engineering Problems. This project aims to address significant gaps in the existing knowledge about solving complex engineering problems that involve conflicting objectives and unquantifiable features. In these problems, the decision-maker is interested in knowing high-quality and dissimilar solutions that determine the trade-off between the problem objectives. The intended outcomes of this project include a novel robust computational solver that can ....An Efficient Computational Solver for Complex Engineering Problems. This project aims to address significant gaps in the existing knowledge about solving complex engineering problems that involve conflicting objectives and unquantifiable features. In these problems, the decision-maker is interested in knowing high-quality and dissimilar solutions that determine the trade-off between the problem objectives. The intended outcomes of this project include a novel robust computational solver that can automatically find such solutions. The decision-makers can then choose the final solution based on their expertise and preferences. This expects to offer significant benefits to diverse engineering disciplines by finding superior and more practical solutions to their complex multidisciplinary problems.Read moreRead less
Towards Generalisable and Unbiased Dynamic Recommender Systems. This project aims to develop the foundations, including models, methodology, and algorithms for building generalisable and unbiased dynamic recommender systems to facilitate intelligent decision-making, prompt contextualised and personalised strategic plans, and support context-aware action recourse. To ensure that fundamental principles, such as fairness and transparency, are respected, a set of algorithms and techniques are propos ....Towards Generalisable and Unbiased Dynamic Recommender Systems. This project aims to develop the foundations, including models, methodology, and algorithms for building generalisable and unbiased dynamic recommender systems to facilitate intelligent decision-making, prompt contextualised and personalised strategic plans, and support context-aware action recourse. To ensure that fundamental principles, such as fairness and transparency, are respected, a set of algorithms and techniques are proposed to develop recommender systems in a more responsible manner. The result of this project will not only maintain Australia's leadership in this frontier research area, but also serve as an excellent vehicle for the education and training of Australia's next generation of scholars and engineers.Read moreRead less