-
Intelligent Table Tennis Match Analysis: Automated Insights Extraction through Machine Learning and Computer Vision, AUD 62,500, funded by the Table Tennis Australia (TTA) [2023-2026].
-
Empowering Agents with Human Feedback: Integrating Implicit and Explicit Signals in Deep Reinforcement Learning, AUD 471,571, funded by the US Air Force Office of Scientific Research (AFOSR), Asian Office of Aerospace Research and Development (AOARD) [2023-2025] (led by Dr Bahareh Nakisa at the School of IT).
-
Design and delivery of a Graduate Certificate of Secondary Digital Technologies, AUD 1,112,571, funded by the Department of Education and Training, Victoria, Australia [2023-2026] (led by A/Prof Julianne Lynch at the School of Education).
-
Machine Learning in Heterogeneous Data from Multiple Sources, USD 225,000, funded by the US Air Force Office of Scientific Research (AFOSR), Asian Office of Aerospace Research and Development (AOARD) [2022-2025] (One of the only two projects funded outside of US in the recent AFOSR Director's Research Initiative).
-
Cold-start Contract Cheating Identification from Side Information Using Latent Linear Writing Style Representation, AUD 12,000, funded by the Deakin Science & Society Network [2022].
-
Application of Generic Actual Argument Model to represent complex decisions and generate narratives, AUD 30,000, funded by the Defence Science and Technology (DST) Group under the AI for Decision Making Initiative Round 3 Phase 1 [2022].
-
-
Utilizing Extractive-Abstractive Summarization for Understanding the Narrative of Social Media Users from Multimodal Data, AUD 20,000, funded by the Office of National Intelligence (ONI) Australia under the AI for Decision Making Initiative Round 2 Phase 1 [2021].
-
Conversational Interface for Context-aware Systems, AUD 7,500, funded by Deakin University, School of Information Technology under the SIT Industry Engagement and Demonstrators Grant (IEDG) [2021].
-
IoT-enabled Conversational System for Explainable Situational Awareness, AUD 15,000, funded by Deakin University, School of Information Technology under the SIT Research Program Initialisation Grant [2021].
-
-
Efficient outlying aspect mining in data with mixed attributes, AUD 10,000, funded by Deakin University, School of Information Technology under Early Career Researcher Small grant [2021].
-
Practical anomaly detection method for real-world problems, AUD 5,000, funded by Deakin University, Faculty of Science, Engineering and Built Environment under Peer-Reviewed ECR Support Scheme (PRESS) [2021].
-
A competency-aware multi-agent framework for human-machine teams in adversarial environments, AUD 373,199, funded jointly by Defence Science and Technology (DST) Group Australia and US Air Force Office of Scientific Research (AFOSR) under the AFOSR-DST Australia Autonomy Initiative [2021-2022].
-
Modeling Adversary Intent Using Multiobjective Reinforcement Learning, AUD 97,199, funded jointly by Defence Science and Technology (DST) Group Australia [2021].
-
Developing robust framework for practical data mining, USD 150,000, funded by US Air Force Office of Scientific Research (AFOSR), Asian Office of Aerospace Research and Development (AOARD) and Office of Naval Research (ONR) Global [2020-2023].
-
Ensembling Single-Class Classifiers, AUD 20,000, funded by the Office of National Intelligence (ONI) Australia under the AI for decision making initiative Round 1 Phase 1 [2020].
-
A new robust method to detect anomalies in cybersecurity datasets, AUD 5,000, funded by Deakin University, Faculty of Science, Engineering and Built Environment under Peer-Reviewed ECR Support Scheme (PRESS) [2020].
