I am currently a Research Assistant in MBZUAI, advised by Assistant Professor Zhiqiang Shen. Before that, I received my M.Eng. degree from Southeast University under the supervision of Prof. Min-Ling Zhang. I received my B.Eng. degree from Chongqing University.

My primary research focus is on trustworthy weakly supervised learning and data-efficient learning, . Here’s my CV.

In April, I will begin my Ph.D. studies at the University of Tokyo under the supervision of Prof. Masashi Sugiyama. If you are interested in discussing with me, welcome and feel free to contact me.

Email: dongdongwu1230 [at] gmail.com OR dongdong.wu [at] mbzuai.ac.ae.

📝 Publications

• Submitted M-Attack: A Simple Baseline Achieving Over 90% Success Rate Against the Strong Black-box Models of GPT-4.5/4o/o1
  Zhaoyi Li, Xiaohan Zhao, Dong-Dong Wu, Jiacheng Cui, Zhiqiang Shen
  PDF Code Website
• Submitted Unleashing Potential of Mix Augmentation for Partial Label Learning
  Dong-Dong Wu, Zhaoyi Li, Xiang Li, Zhiqiang Shen
  
• Submitted Dissimilarity-Driven Contrastive Learning for Robust Hashing in Partial Label Image Retrieval
  Zhiqiang Kou, Yucheng Xie, Dong-Dong Wu, Jing Wang, Yuheng Jia, Min-Ling Zhang, Xin Geng
• ICLR 2025 PLENCH: Realistic Evaluation of Deep Partial-Label Learning Algorithms
  Wei Wang, Dong-Dong Wu, Jindong Wang, Gang Niu, Min-Ling Zhang, Masashi Sugiyama
  Proceedings of the 13th International Conference on Learning Representations (ICLR), 2025
  PDF Code Spotlight
• CVPR 2024 Efficient Model Stealing Defense with Noise Transition Matrix
  Dong-Dong Wu, Chilin Fu, Weichang Wu, Wenwen Xia, Xiaolu Zhang, Jun Zhou, Min-Ling Zhang
  Proceedings of the 35th IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024
  PDF Code Appendix
• arXiv 2024 Robust Representation Learning for Unreliable Partial Label Learning
  Yu Shi*, Dong-Dong Wu*, Xin Geng, Min-Ling Zhang
  PDF Code
• AAAI 2024 Distilling Reliable Knowledge for Instance-dependent Partial Label Learning
  Dong-Dong Wu*, Deng-Bao Wang*, Min-Ling Zhang
  Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI), 2023
  PDF Code Appendix
• ICML 2022 Revisiting consistency regularization for deep partial label learning
  Dong-Dong Wu*, Deng-Bao Wang*, Min-Ling Zhang
  Proceedings of the 39th International Conference on Machine Learning (ICML), 2022
  PDF Code
• EAAI A new classification method based on the negation of a basic probability assignment in the evidence theory
  Dongdong Wu, Zijing Liu, Yongchuan Tang
  Engineering Applications of Artificial Intelligence (EAAI). 2020, 96: 103985. https://doi.org/10.1016/j.engappai.2020.103985
  PDF
• PAA A new approach for generation of generalized basic probability assignment in the evidence theory
  Yongchuan Tang, Dongdong Wu, Zijing Liu
  Pattern Analysis and Applications (PAA). 2021, 24(3): 1007-1023. https://doi.org/10.1007/s10044-021-00966-0
  PDF ESI Highly Cited Paper (top1%)
• QRE An improved failure mode and effects analysis method based on uncertainty measure in the evidence theory
  Dongdong Wu, Yongchuan Tang
  Quality and Reliability Engineering International (QRE). 2020; 36(5): 1786‐1807. https://doi.org/10.1002/qre.2660
  PDF Certificate ESI Highly Cited Paper (top1%)

🎈 Maintained GitHub Repositories

• [Advances-in-Partial-and-Complementary-Label-Learning]
  • A curated list of most recent papers & codes in Learning with Partial/Complementary Labels.

👨‍💻 Academic Experience

• 2024.09 - 2025.03, Research Assistant, MBZUAI, UAE. [Advised by Zhiqiang Shen]

• 2023.06 - 2023.10, Research Intern, Ant Group, China. [Collaborated with Chilin Fu, Weichang Wu, Xiaolu Zhang, and Jun Zhou]

• 2020.06 - 2021.09, Research Intern, Institute of Automation, Chinese Academy of Science, China.

🌞 Academic Services

• Reviewer / PC Member: ICML (2022, 2025), ECML-PKDD (2023), CVPR (2024, 2025), ICCV(2025), IJCAI (2024, 2025), KDD (2024), ADMA(2025).
• Teaching Assistant: Machine Learning at Southeast University, spring 2022.

👻 Invited Talks

• “ATEC2023 Competition Review and Sharing”, Meituan, 2024

🏅 Awards

• Competitions
  • Team Champion (Rank 1/1901), ATEC2023 - LLM Application and Security, 2024. [Report]

  • Rank 6, ATEC2023 - AI-Generated News Detection Track, 2024.

  • Rank 6, CCF BDCI - Conversational RAG Track, 2024. [Code]

  • Rank 7, 1st Learning and Mining with Noisy Labels (LMNL) Challenge of IJCAI-ECAI2022 - Image Classification Task, 2022.
  • Rank 4, 1st LMNL Challenge of IJCAI-ECAI2022 - Label Noise Detection Task, 2022. [Certificate], [Code]
  • First Prize, National CCF Green Computing Contest, 2021.
  • Third Prize, National WeChat Mini Program Development Contest, 2020.
  • Outstanding Winner (Top 1%), International Interdisciplinary Contest in Modeling (ICM), 2019. [Report]
• Honors
  • Outstanding Graduate in Southeast University, 2024.
  • Excellent Master Student Model in Southeast University, 2023.
  • Outstanding Undergraduate in Chongqing University, 2021.
• Scholarships
  • Huawei Scholarship (2024), Lenovo Research Institute Scholarship (2023), Huawei Scholarship (2021)