Rate My Professor Can Wang

Dr. Can Wang is a Senior Lecturer of Computer Science in the School of Information and Communication Technology, Griffith Sciences, at Griffith University, Australia, a position she assumed in January 2020. She previously held the role of Lecturer at Griffith University from May 2017 to December 2019 and served as a Postdoctoral Fellow at Data61, CSIRO, Australia, from 2014 to 2016. Dr. Wang earned her PhD in Computer Science from the University of Technology Sydney in 2013, a Master's degree from Wuhan University, China, in 2009, and a Bachelor's degree from Wuhan University in 2007. Throughout her academic career, she has received numerous honors, including Best Student Paper Awards at ADMA 2019 and PAKDD 2013, Outstanding Performance awards from CSIRO in 2014 and 2015, Full Scholarship from UTS for doctoral studies in 2009, Huawei Special Scholarship for Postgraduates in 2008, first scholarships for postgraduates in 2008 and 2007, and multiple prizes in mathematical modeling contests such as third prize in the US Mathematical Contest in Modeling (2007) and second prize in the National Mathematical Modeling Contest for Postgraduates (2007).

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.