Zhen (Zohn) Wang

I am honored to hold a Ph.D. degree at School of Computer Science, the University of Sydney, supervised by Professor Dacheng Tao. My academic journey commenced with a Data Science M.Sc. degree from Tsinghua University, supervised by Associate Professor Bo Yuan. Furthermore, I gained invaluable experience as a research assistant and visiting academic at the University of Melbourne, supervised by Professor Rui Zhang. I have proudly contributed to the academic community with over 30 top-tier AI research papers. In 2023, I received the Outstanding PhD Graduation Award from the University of Sydney and the Global Outstanding PhD Student Award from the China Scholarship Council.

My research spectrum encompasses diverse AI domains, including streaming label learning, continual learning, few-shot learning, meta-learning, reinforcement learning, and stock price prediction. My work is motivated by and can be applied to various real-world applications such as Stock Market, Streaming Media, Social Network, Recommendation System, and Quant Price Prediction.

I actively serve as a reviewer for prestigious journals and conferences such as NeurIPS, ICML, ICLR, CVPR, ICCV, ACM MM, AAAI, IJCAI, ECCV, IEEE Transcantions, and ACM Transcantions. For a more in-depth view of my research endeavors and achievements, please visit my Google Scholar.

News

• Two papers were accepted to NeurIPS 2023
• One paper on "Quantifying the impact of COVID-19" was accepted to TRB 2023, Washington, D.C.
• One paper on continual learning was accepted to IJCV

Publications

1. Zhen Wang, Liu Liu, Y. Kong, J. Guo, and Dacheng Tao. "Online Continual Learning with Contrastive Vision Transformer", European Conference on Computer Vision (ECCV 2022). (CORE Rank A*, CCF B)
2. Zhen Wang, Liu Liu, Y. Duan, Y. Kong, and Dacheng Tao. "Continual Learning with Lifelong Vision Transformer", Conference on Computer Vision and Pattern Recognition (CVPR 2022). (CORE Rank A*, CCF A)
3. Zhen Wang, Liu Liu, Y. Duan, and Dacheng Tao. "Continual Learning Through Retrieval and Imagination", The 36th AAAI Conference on Artificial Intelligence (AAAI), 2022. (CORE Rank A*, CCF A)
4. Zhen Wang, Liu Liu, Yiqun Duan, and Dacheng Tao, "SIN: Semantic Inference Network for Few-shot Streaming Label Learning", IEEE Transactions on Neural Networks and Learning Systems, 2022. (SCI Q1, SJR Q1)
5. Zhen Wang, Liu Liu, Y. Duan, and Dacheng Tao. "Continual Learning with Embeddings: Algorithm and Analysis", ICML 2021 Workshop on Theory and Foundation of Continual Learning.
6. Zhen Wang, Y. Duan, Liu Liu, and Dacheng Tao. "Multi-label Few-shot Learning with Semantic Inference", The 35th AAAI Conference on Artificial Intelligence (AAAI), 2021. (CORE Rank A*, CCF A)
7. Zhen Wang, Liu Liu, and Dacheng Tao. "Deep Streaming Label Learning", The 37th International Conference on Machine Learning (ICML), 2020. (CORE Rank A*, CCFA)
8. Zhen Wang, Rui Zhang, Jianzhong Qi, Bo Yuan. "DBSVEC: Density-Based Clustering Using Support Vector Expansion", The 35th IEEE International Conference on Data Engineering (ICDE), 2019. (CORE Rank A*, CCF A)
9. Y. Yu, Zhen Wang, Bo Yuan. "An Input-aware Factorization Machine for Sparse Prediction", The 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019. (CORE Rank A*, CCFA)
10. W. Lu, Y. Yu, Y. Chang, Zhen Wang, C. Li, Bo Yuan. "A Dual Input-aware Factorization Machine for CTR Prediction", The 29th International Joint Conference on Artificial Intelligence (IJCAI), 2020. (CORE Rank A*, CCFA)
11. Y. Kong, Liu Liu, M. Qiao, Zhen Wang, and Dacheng Tao. "Trust-Region Frequency Adaptation Online Continual Learning without Task Boundary", International Journal of Computer Vision (IJCV). (SJR Q1, SCI Q1)
12. Y. Kong, Liu Liu, Zhen Wang, and Dacheng Tao. "Continual Learning through Shared Low-Rank Null Space", European Conference on Computer Vision (ECCV 2022). (CORE Rank A*, CCF B)
13. Y. Duan, J. Zhou, Zhen Wang, YK Wang, and CT Lin. "DeWave: Discrete Encoding of EEG Waves for EEG to Text Translationn", Conference on Neural Information Processing Systems (NeurIPS), 2023 (CORE Rank A*, CCF A)
14. Y. Duan, Zhen Wang, and J. Wang. "Position-Aware Transformer for Image Captioning with Spatial Relation Representation", Neurocomputing, 2022. (SJR Q1, SCI Q2)
15. Y. Duan, Zhen Wang, Y. Li, J. Tang, Y. Wang, and CT Lin. "Cross Task Neural Architecture Search for EEG Signal Classifications", Neurocomputing, 2023. (SJR Q1, SCI Q2)
16. Y. Duan, Zhen Wang, Y. Li, and J. Wang. "Cross-Domain Multi-Style Merge for Image Captioning", Computer Vision and Image Understanding, 2023. (SJR Q1)
17. Si Chen, L. Wang*, Zhen Wang, and et al. "Learning Meta-Adversarial Features via Multi-Stage Adaptation Network for Robust Visual Object Tracking", Neurocomputing, 2022. (SJR Q1, SCI Q2)
18. H. Xi, L. He, Y. Zhang, Zhen Wang. "Bounding the Efficiency Gain of Differentiable Road Pricing for EVs and GVs to Manage Congestion and Emissions", PLoS ONE, 2020. (SJR Q1)
19. H. Xi, L. He, Y. Zhang, Zhen Wang. "Differentiable road pricing for environment-oriented electric vehicle and gasoline vehicle users in the bi-objective transportation network", Transportation Letters, 2021. (SJR Q2)
20. H. Xi, Zhen Wang, Q. Li, David A. Hensher, John D. Nelson, Chinh Ho. "Quantifying the impact of COVID-19 on the travel behavior of people in different socio-economic segments", Transportation Research Board (TRB), 2023.
21. X. Li; Zhen Wang; X. Wu; Bo Yuan; X. Wang. "A Dual Adaptive Factorization Network for CTR Prediction", IEEE International Conferences on High Performance Computing and Communications (IEEE HPCC 2021), 2021.
22. X. Li; Zhen Wang; X. Wu; Bo Yuan; X. Wang. "Input Enhanced Logarithmic Factorization Network for CTR Prediction", Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2022.
23. L. Wang; Si Chen; Zhen Wang; DH Wang; S. Zhu. "Graph Attention Transformer Network for Robust Visual Tracking", International Conference on Neural Information Processing (ICONIP), 2022.
24. G. Ma, L.Zhang, H.Wang, L. Li, Zi. Wang, Zhen Wang, L.Shen, X. Wang, and Dacheng Tao. "Learning Better with Less: Effective Augmentation for Sample-Efficient Visual Reinforcement Learning,", Conference on Neural Information Processing Systems (NeurIPS), 2023.
25. G. Ma, Zhen Wang, Z. Yuan, X. Wang, Bo Yuan, and Dacheng Tao. "A Comprehensive Survey of Data Augmentation in Visual Reinforcement Learning", Submitted to Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.

Under Review

1. TPAMI;
2. ICLR;
3. ICML;
4. AAAI;