Project Overview
The project investigates methods for building trustworthy and explainable AI frameworks for policing applications. It focuses on designing data-driven models that integrate interpretability, fairness, and operational reliability into machine-learning workflows for real-world decision support.
Aim
To develop machine learning frameworks that enable ethical, explainable, and reliable AI applications in policing and public safety.
Objectives
- To design scalable models for extracting structured intelligence from unstructured law enforcement data.
- To develop explainability techniques tailored for operational decision contexts.
- To evaluate fairness and robustness of AI systems under real-world data constraints.
- To collaborate with law enforcement partners to ensure translational impact and adoption.
Significance
The project will advance responsible AI adoption in critical domains by addressing technical and ethical challenges in real-world policing applications. It aligns with Australia’s National AI Strategy and contributes to the safe and transparent adoption of emerging technologies in public safety and justice.
Ideal candidate
This project is open to domestic applicants only.
Applicants must meet the entry requirements for a Higher degree by research program.
The ideal candidates should have a relevant bachelor’s degree in science and engineering, and be interested in law enforcement.
Internship
The successful candidate will be provided with an internship opportunity, to support the research project.
Scholarship
This scholarship is funded by the CSIRO Next Generation Graduates Program (NGGP) in partnership with the NSW Police Force. The program supports Master of Philosophy (MPhil) students undertaking research that advances responsible AI.
Scholarship Value
$43,333.00 (full-time enrolment) per year, for a maximum of two years. Additional allowances are available to support training, travel, and thesis preparation.
Applications closing date: 31st December 2025
Enquiries
To apply, contact Dr. Yanda Shao via the Expression of Interest.
For enquiries, please email Dr. Yanda Shao at Yanda.Shao@curtin.edu.au