Rate My Professor Jian Yang

Yang's research interests focus on graph mining, trust and fake news detection, recommendation in social media, fraud detection, data fusion, data-driven process analytics, service-oriented computing, smart cities, and aging and aged care. She has earned prestigious recognitions, including Stanford/Elsevier Top 2% of Scientists worldwide since 2019, Faculty Excellence in HDR Supervision (2019), Most Influential IJCAI 2020 Paper Award for “Deep learning for community detection: Progress, challenges and opportunities,” ICPR 2024 Best Student Paper Award, and Best Student Paper Award for “FRAUDRE: Fraud Detection Dual-Resistant to Graph Inconsistency and Imbalance” (2021). As a founding member and steering committee chair of the International Conference on Service Oriented Computing (ICSOC), she has also served as general chair and program committee chair for ICSOC and BPM conferences. Notable publications include “A bidirectional feedback actor–critic approach for collaborative target search in heterogeneous intelligent agent systems” (IEEE Systems Journal, 2026), “A survey of progress in LLM alignment from the perspective of reward design” (IEEE Transactions on Artificial Intelligence, 2026), “Community-structure enhanced brain graph mining” (IEEE Transactions on Artificial Intelligence, 2026), “Extract and refine brain subgraph for disorder analysis via cross-domain learning” (IEEE Transactions on Big Data, 2026), and “Learning from graph-graph relationship: a new perspective on graph-level anomaly detection” (IEEE Transactions on Knowledge and Data Engineering, 2026). She leads major projects such as MQRC Consilience Macquarie University Data Research Centre, Transformation of Data to Data products for a Trusted Data-Driven Economy, and initiatives on trust and spam detection in social media, fraud detection in finance, and smart cities.