Shoujin Wang is a real-world application driven data science researcher. He obtained his PhD in Data Science from the University of Technology Sydney in 2019. Shoujin's main research interests include Data Mining, Machine Learning, Recommender Systems and Fake News Mitigation. He has published more than 40 high-quality research papers in these areas, most of which were published at premier data science and AI conferences or journals, like The ACM Web Conference, AAAI, IJCAI and ACM Computing Surveys (CSUR). He has delivered four research tutorials on recommender systems at AAAI, IJCAI, SIGIR and ICDM.

Shoujin has generally served as a (senior) PC member at over 10 premier international conferences including KDD, AAAI, IJCAI and a reviewer for more than 10 prestigious journals including Machine Learning, IEEE Transactions on Knowledge and Data Engineering (TKDE), ACM Transactions on Information Systems (TOIS), etc. Shoujin has been invited to serve as a guest editor of three primer journals including IEEE Intelligent Systems and has organized two workshops at ICDM. Shoujin has some practical data science application experience by being involved into two industry projects. He is also one of the two recipients of the prestigious 2022 Club Melbourne Fellowships.