Dr. Jiangang Ma
Senior Lecturer, Information Technology
Campus
Biography
Dr. Jiangang (Mike) Ma is currently a senior lecturer (equivalent to associate professor in North America) in information technology. Before joining Federation University, he worked as a lecturer of data science and statistics with James Cook University. Before that, he was a postdoctoral research fellow with the University of Adelaide and then worked as a research fellow at Centre for Applied Informatics with Victoria University, where he worked on ARC funded research projects.
Mike earned a PhD degree in computer science from Victoria University and a master's degree in information technology from Queensland University of Technology. After that, he worked as a professional software engineer in industry for several years.
Mike's research interests include data science, artificial intelligence, and health informatics. He has worked on a broad range of topics including big data analytics, data visualization, anomaly detection, graph-based learning and health informatics, etc. His current projects focus on applying deep learning (DL), large language models (LLMs), image/video processing and natural language processing (NLP) techniques to develop AI-powered solutions for practical applications, such as predicting anomalies for healthcare applications and detecting disease from media data, etc. He is actively looking for highly motivated students who are interested in joining his team to do excellent research.
More about Mike
Qualifications
- Doctor of Philosophy (Computer Science), Victoria University
- Master (Information Technology), Queensland University of Technology
- Graduate Certificate in Education (Tertiary Education), Federation University
Areas of interest
- Data science
- Artificial intelligence
- Image and video processing
- Internet-of-Things (IoT)
- Health informatics
Areas of expertise
Deep learning, AI, large language models, graph-based learning
He has a broad interest in deep learning, AI, large language models and graph-based learning, and develops AI solutions that translate from research into real-world applications. His expertise includes graph-based learning, graph neural networks, and multimodal representation learning, with applications in healthcare, decision support and intelligent systems.
Anomaly Detection
He specializes in anomaly detection using deep learning and graph-based learning, developing methods to identify rare and unexpected patterns in complex, high-dimensional and heterogeneous data. His research work spans time series, media data, graph-structured data, etc., with applications in fraud, healthcare (e.g., brain disease detection & classification, depression detection, etc.), and intelligent monitoring systems.
Big data analytics, management
In area of big data analytics and management, he specializes in developing scalable methods to process and extract insights from big datasets. His research work combines machine learning with cloud computing, with applications in IoT (e.g., real-time identifying and tracking moving objects), and real-time decision support, etc.
Current
- PhD student, Federation University, ‘Explainable Graph Learning for Brain Disorder Detection’, principal supervisor.
- PhD student, Federation University, ‘Context-Aware Large Language Models for Depression Severity Prediction and Suicidal Expression Detection from Social Media’, co-supervisor.
Past
- PhD student, Federation University, ‘Reliable Graph Neural Networks for Anomaly Detection’, principal supervisor.
- PhD student, Federation University, ‘An efficient framework for mining outlying aspect’, principal supervisor.
- PhD student, Federation University, ‘Enhancing Video Coding Efficiency through Deep Learning-Based Forward Referencing Framework’, co-supervisor.
- PhD student, Victoria University, ‘Data Stream Mining in Medical Sensor-Cloud’, co-supervisor.
- Business analytics and decision support
- User experience
- IT problem solving
- Data mining
- Machine learning
- Data visualization
- Big data analytics
Dr. Ma has published over 50 research papers on international journals and conferences, including the papers published on top international journals and conferences, such as IEEE International Conference on Data Engineering (ICDE) and IEEE International Conference on Data Mining (ICDM), etc.
He is actively looking for highly motivated students who are interested in joining his team to do excellent research. If you are interested in joining his team to do research, please contact him and briefly introduce:
- your education background
- your research experience and strengths
- explain why you want to do the research projects.
Centre for Smart Analytics (CSA)
Health Innovation and Transformation Centre
- Publications
Structure Matters: Brain Graph Augmentation via Learnable Edge Masking for Data-Efficient Psychiatric Diagnosis
- Conference Proceedings
- DOI reference: 10.1007/978-981-95-4972-6_28
SIGNL: A label-efficient audio deepfake detection system via spectral-temporal graph non-contrastive learning
- Journals
- DOI reference: 10.1016/j.eswa.2025.131056