Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Monash University
- University of Sydney
- The University of Queensland
- University of Adelaide
- Curtin University
- University of Southern Queensland
- Australian National University
- La Trobe University
- Queensland University of Technology
- UNIVERSITY OF WESTERN AUSTRALIA
- University of New South Wales
- AUSTRALIAN NATIONAL UNIVERSITY (ANU)
- BOND UNIVERSITY
- Macquarie University
- Murdoch University
- The University of Western Australia
- UNIVERSITY OF ADELAIDE
- UNIVERSITY OF SYDNEY
- 8 more »
- « less
-
Field
-
challenging problem due to the limitations of classical algorithms. These methods often struggle with the complexity and scale of accurately predicting mRNA secondary structures. This pilot research project
-
Optimisation methods, such as mixed integer linear programming, have been very successful at decision-making for more than 50 years. Optimisation algorithms support basically every industry behind
-
Mixed-Integer Programming (MIP) solvers are very powerful tools to solve combinatorial problems that arise in many industries. Modern MIP solvers usually run a sequence of algorithms to solve
-
Automated Program Repair (APR) is the grand challenge in software engineering research. Many APR methods have shown promising results in fixing bugs with minimal, or even no human intervention. Despite many studies introducing various APR techniques, much remains to be learned, however, about...
-
This project aims to employ advanced machine learning techniques to analyse text, audio, images, and videos for signs of harmful behaviour. Natural language processing algorithms are utilized
-
package should be prioritised are surprisingly difficult computational tasks. State-of-the-art high-performance algorithms are used to calculate routes for the vehicles in order to minimise costs and
-
guarantees of FL. In this project, we aim at an ambitious goal - designing secure and privacy-enhancing algorithms and framework for FL and applying our designs into real-world applications. To achieve
-
formative assessment and personalised feedback while ensuring fairness, accountability, and transparency. The research will explore a combination of algorithmic design, human–AI interaction, and empirical
-
algorithm that allows accurate simulation of fluid transport processes in porous media coupled with chemical reactions (e.g. dissolution and precipitation). The algorithm will be validated firstly against
-
development of NeurAID repository perform sural nerve biopsy assessment as required for training of AI algorithms collaborate with other clinicians and AI engineers to facilitate the development of algorithms