This is Kunze Wang, and I am currently a machine learning engineer and applied scientist at Rokt, where I work on computational advertising and recommendation systems.

Before joining Rokt, I completed my PhD at The University of Sydney, supervised by Dr.Caren Han and Dr. Josiah Poon. During my time at USYD, I visited The University of Hong Kong and The University of Western Australia, and interned at Meituan Company.

Prior to that, I earned my Master of Information Technology and Information Technology Management at USYD. I completed my bachelor’s degree at Nanjing University and graduated with honors.

My research interests include graph neural networks for text classification, knowledge graphs, abusive language detection, and, like everyone else recently, large language models :)

Since I’ve graduated from USYD and may lose uni email account at any time, you may have to reach me through my personal email blakewkz[AT]gmail[DOT]com to reach me instead of my uni email.

Pulications

First/Co-first authored

1. Wang, K., Ding, Y., & Han, S. C. (2023). Graph neural networks for text classification: a survey. Accepted at Artificial Intelligence Review. Link
2. Wang, K.., Han, C., & Poon, J. (2023, December). Re-Temp: Relation-Aware Temporal Representation Learning for Temporal Knowledge Graph Completion. In Findings of the Association for Computational Linguistics: EMNLP 2023 (pp. 258-269). Link
3. Wang, K., Han, C. and Poon, J., 2022. InducT-GCN: Inductive Graph Convolutional Networks for Text Classification. In 26TH International Conference on Pattern Recognition. Link
4. Wang, K., Han, C., Long, S. and Poon, J., 2022. ME-GCN: Multi-dimensional Edge-Embedded Graph Convolutional Networks for Semi-supervised Text Classification. In ICLR 2022 Workshop on Deep Learning on Graphs for Natural Language Processing. Link
5. Wang, K., Lu, D., Han, C., Long, S. and Poon, J., 2020. Detect All Abuse! Toward Universal Abusive Language Detection Models. In Proceedings of the 28th International Conference on Computational Linguistics (pp. 6366-6376). Link

Co-authored

1. Yang, W., Xu, Y., Li, Y., Wang, K., Huang, B. and Chen, L., 2024. Continual Learning for Temporal-Sensitive Question Answering. Accepted at IJCNN 2024.
2. Han, C., Yuan, Z., Wang, K., Long, S. and Poon, J., 2022. Understanding Graph Convolutional Networks for Text Classification. In Deep Learning for Graphs at AAAI Conference on Artificial Intelligence 2022. Link
3. Weld, H., Huang, G., Lee, J., Zhang, T., Wang, K., Guo, X., Long, S., Poon, J. and Han, C., 2021. CONDA: a CONtextual Dual-Annotated dataset for in-game toxicity understanding and detection. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 (pp. 2406–2416). Link
4. Han, C., Long, S., Luo, S., Wang, K. and Poon, J., 2020. VICTR: Visual Information Captured Text Representation for Text-to-Vision Multimodal Tasks. In Proceedings of the 28th International Conference on Computational Linguistics (pp. 3107-3117). Link

Teaching

1. COMP5046 Natural Language Processing: Head TA - 2020s1, 2021s1
2. COMP5318 Machine Learning: Tutor - 2020s1, 2020s2
3. COMP5703 Information Technology Capstone Project: Tutor - 2020s1, 2020s2

Academic Service

1. Reviewers of AAAI, EMNLP, COLING
2. Leaderboard chair of Workshop on Toxic Language Detection

CV

cv.pdf