I am a first-year Ph.D. student at the University of Tokyo, supervised by Prof. Masashi Sugiyama. I am also a Junior Research Associate at the Imperfect Information Learning Team, RIKEN Center for Advanced Intelligence Project. 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. During my research journey, I also had wonderful time at MBZUAI, Ant Group and CAS.

My primary research focus is on trustworthy weakly supervised learning and data-efficient learning, . Here’s my CV. If you are interested in discussing with me, welcome and feel free to contact me.

Email: dongdongwu1230 [at] gmail.com OR wudd [at] g.ecc.u-tokyo.ac.jp OR dongdong.wu [at] riken.jp

🎈 Maintained GitHub Repositories

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

📝 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 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%)

👨‍💻 Academic Experience

• 2025.04 - 2026.03 (Expected), Junior Research Associate, RIKEN, Japan. [Advised by Masashi Sugiyama]
• 2025.04 - 2026.03 (Expected), Research Assistant, Beyond AI, Japan. [Advised by Masashi Sugiyama]
• 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), NeurIPS (2025), CVPR (2024, 2025), ICCV(2025), IJCAI (2024, 2025), KDD (2024), ECML-PKDD (2023), ADMA(2025), ECAI(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)