Rate My Professor Teresa Wang

Dr. Teresa Weiqing Wang is a Senior Research Fellow in the Department of Data Science & AI and Senior Lecturer in data science at Monash University's Faculty of Information Technology. As Director of the Master of Data Science program, she teaches advanced units including FIT5201 Machine Learning and FIT9136 Algorithms and Programming Foundations in Python. Her academic journey began with a Bachelor of Software Engineering and a Master of Computer Science from Nanjing University in 2010 and 2013, respectively, followed by a PhD in Computer Science from the University of Queensland in 2017. Her doctoral thesis, "Point of Interests Recommendation in Location-Based Social Networks," earned the Dean’s Award for Outstanding Higher Degree by Research Theses.

Prior to her current roles, Wang served as a Lecturer at Monash University from 2018 to 2023 and as a Post-doctoral Research Fellow in the Data and Knowledge Engineering Group at the University of Queensland from 2017 to 2018. She is the recipient of the prestigious Australian Research Council (ARC) Discovery Early Career Researcher Award (DECRA) fellowship for 2025-2027, supporting her project "Knowledge Enriched Approach for Effective Personalization" as Primary Chief Investigator. Wang's research specializes in entity and user modelling, relational and structural machine learning, spatial and temporal analysis, graph and network construction, and recommender systems, with applications in social media, eCommerce, and health/medical data. She has contributed to significant projects such as the CSIRO Next Generation Graduates Program on AI in Mental Health, AI for Clean Energy and Sustainability, and Real-time EH&S Intervention to Improve Site Safety.

Her influential publications include "Spatial-aware hierarchical collaborative deep learning for POI recommendation" (IEEE Transactions on Knowledge and Data Engineering, 2017), "PME: projected metric embedding on heterogeneous networks for link prediction" (ACM SIGKDD, 2018), "An overview of clustering methods with guidelines for application in mental health research" (Psychiatry Research, 2023), "Joint modeling of user check-in behaviors for real-time point-of-interest recommendation" (ACM TOIS, 2016), and recent works like "Scalable and effective negative sample generation for hyperedge prediction" (Neural Networks, 2026). Wang actively supervises PhD students and maintains an active presence in machine learning and data science research.