Rate My Professor Can Wang

Dr. Wang's research specializations include data analytics, artificial intelligence, machine learning, and big data. Her key publications encompass journal articles such as "Truth Finding by Reliability Estimation on Inconsistent Entities for Heterogeneous Data Sets" in Knowledge-Based Systems (2020), "Three-hop Velocity Attenuation Propagation Model for Influence Maximization in Social Networks" in World Wide Web (2019), "Coupled Clustering Ensemble by Exploring Data Interdependence" in ACM Transactions on Knowledge Discovery from Data (2018), and "Coupled Attribute Similarity Learning on Categorical Data" in IEEE Transactions on Neural Networks and Learning Systems (2015). Significant conference contributions include "DAMTRNN: A Delta Attention-Based Multi-task RNN for Intention Recognition" and "Top-N Hashtag Prediction via Coupling Social Influence and Homophily" at ADMA 2019, the former earning the Best Student Paper Award, and "Coupled Interdependent Attribute Analysis on Mixed Data" at AAAI 2015. With over 4,246 citations on Google Scholar, her work has notable impact in the field. At Griffith University, Dr. Wang convenes courses like Applied Data Mining (3031ICT) and Data Mining (3804ICT), and contributes to the Master of Data Science program while supervising PhD students.