Lecturer, University of Technology Sydney
Honorary Lecturer, Macquarie University
Email: shoujin.wang@uts.edu.au

Biograph:

Shoujin Wang is a Lecturer in Data Science at the Data Science Institute, University of Technology Sydney. 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 60 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.

Selected Honors and Awards:

[1]. IEEE DSAA 2024 Best Paper Award (PSTDA Track), 2024.
[2]. NSW iAwards & NSW iAwards Merit Award (as a team), 2024.
[3]. UTS Distilling Research Impact Award (as a team), 2024.
[4]. Listed in the Selected 200 Young Researchers in Mathematics and Computer Science by 11th Heidelberg Laureate Forum, 2024.
[5]. UTS nominee of the NSW Premier's Award for Science & Engineering (NSW Early Career Researcher), 2023.
[6]. 2023 Royal Society of New South Wales Bicentennial Early Career Research and Service Citation, 2023.
[7]. Listed in the globally top 2% scientists (single year) by Stanford University, 2023.
[8]. One paper selected as most influential IJCAI paper (IJCAI 2021), 2023.
[9]. DSAA 2022 Next-Generation Data Scientist Award, 2022.
[10]. DSAA Special Session Best Student Paper Award, 2022.
[11]. IEEE UIS/ATC 2022 Best Paper Award, 2022.
[12]. DAAD UNICORE Scholarship, 2022.
[13]. Club Melbourne Fellowship Award, 2022.
[14]. DAAD AINET Fellowship, 2021.

In the Media:

[1]. "MCEC announces Annual Club Melbourne Fellowship" on Melbourne Convention and Exhibition Centre (MCEC) website, 2022.
[2]. "New system uses AI to beat fake news" in The Lighthouse, MIRAGE news, The National Tribune, 2022.
[3]. "AI could be key to preventing the spread of fake news" in LifeWire, viknews, 2022.
[4]. "AI helps to prevent the spreading of fake news" in SBS Chinese Channel, SBS Radio, 2022.
[5]. Interviewed by SBS Chinese Channel to talk about the daily life of researchers, SBS Chinese Channel and SBS Radio, 2022.
[6]. "Quality research as a team in data science" in UTS Research Insider, 2018.

Call For Students and Collaborations:

• Shoujin is always seeking highly self-motivated students for PhD, Master by Research (MRes), or dual-doctorate degree candidates. He also warmly welcomes visiting students and visiting scholars in the areas of data science and AI.
• UTS competitive scholarship for PhD and MRes (including international and domestic applicants): link
• UTS-CSC joint scholarship for PhD, joint-PhD (dual-doctor degree) students: link
• CSC or other funding sponsored PhD students, visiting PhD students, postdocs and scholars.
• UTS PhD and MRes application procedure and website: link
• Shoujin is open to any kinds of collaborations on research, industry projects, data science applications, etc.

Call For Papers:

1. Special issue "Recommender Systems and Their Advanced Application" with Applied Science (IF = 2.84, citescore = 3.7, JCR Q2). Submission deadline January 31, 2023.
2. Special issue "Advanced Semantic Technologies and Sensors" with Sensors (IF = 3.847, JCR Q2). Submission deadline December 20, 2023.
3. Special issue "Deep Reinforcement Learning for Recommender Systems (DRL4RS)" with ACM Transactions on Recommender Systems. Submissions deadline: August 30th, 2023.
4. Special issue "Deep Learning for Recommender Systems" with Frontiers in Big Data.(open for submission now).
5. Topical issue "Advanced Theories and Algorithms for Next-Generation Recommender Systems" with SN Computer Science. (open for submission now).

News!

[10/2024] I am invited to serve as the Journal Track Co-Chair of ADMA 2024 and the Local Arrangement Co-Chair of PAKDD 2025, both conferences will be held in Sydney.
[10/2024] Named in the Sandford's List of World Top 2% Scientists (single year) again for the year 2024.
[09/2024] One paper titled "NeuroClips: Towards High-fidelity and Smooth fMRI-to-Video Reconstruction" accepted by NeurIPS 2024.
[08/2024] One paper titled "Fuzzy Federated Learning for Privacy-Preserving Detection of Adolescent Idiopathic Scoliosis" accepted by IEEE Transactions on Fuzzy Systems.
[05/2024] Our paper titled "A Hierarchical and Disentangling Interest Learning Framework for Unbiased and True News Recommendation" has been accepted by the very prestigious data science conference, SIGKDD 2024!
[05/2024] One paper titled "Time-Series Representation Learning via Dual Reference Contrasting" and another paper titled "Structural Representation Learning and Disentanglement for Evidential Chinese Patent Approval Prediction" accepted by CIKM 2024.
[02/2024] Our new survey paper on "casual learning for trustworthy recommender systems" released, link.
[01/2024] Two papers accepted by the ACM Web Conference 2024, one paper on fake news detection and another on sequential recommendation. Congratulations to Qi and Peilin!
[10/2023] Two papers on Related Work Generation and Clickbait Detection accepted by EMNLP 2023. Congratulations to Qi!
[10/2023] Listed in the Globally Top 2% scientists (single year) by Stanford University in October 2023, link for the list: link.
[10/2023] One paper "Trustworthy Recommender Systems" accepted by ACM Transactions on Intelligent Systems and Technology (TIST).
[10/2023] One paper "Learning Informative Representation for Fairness-aware Multivariate Time-series Forecasting: A Group-based Perspective" accepted by IEEE Transactions on Knowledge and Data Engineering (TKDE). Congratulations to Hui and Qi!