I am currently a Research Assistant in Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), supervised 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 interest lies in the field of trustworthy weakly supervised learning, . Currently, I am particularly interested in areas such as partial label learning, dataset condensation, long-tailed learning, knowledge distillation, uncertainty calibration, and model defense. Here is my CV.

Next year (2025 April), I will begin my Ph.D. studies at the University of Tokyo under the supervision of Masashi Sugiyama. If you are interested in discussing with me, welcome and feel free to email me at DongDong.Wu@mbzuai.ac.ae or dongdongwu1230@gmail.com, or reach out via WeChat (ID: kaefer1999).

🎈 GitHub Repositories

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

📝 Publications

• Efficient Model Stealing Defense with Noise Transition Matrix. [Appendix] [Code]
  • 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’24), accepted, 2024.
• Robust Representation Learning for Unreliable Partial Label Learning.
  • Yu Shi$\dagger$, Dong-Dong Wu$\dagger$, Xin Geng*, Min-Ling Zhang*
• Distilling Reliable Knowledge for Instance-dependent Partial Label Learning. [Appendix] [Code]
  • Dong-Dong Wu, Deng-Bao Wang, Min-Ling Zhang*.
  • Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI’24), accepted, 2023.
• Revisiting consistency regularization for deep partial label learning. [Code]
  • Dong-Dong Wu$\dagger$, Deng-Bao Wang$\dagger$, Min-Ling Zhang*.
  • Proceedings of the 39th International Conference on Machine Learning (ICML’22), accepted, 2022.
• 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.
• 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.
  • ESI Highly Cited Paper, top1%.
• 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.
  • ESI Highly Cited Paper [Certificate], top1%.

👨‍💻 Academic Experience

• 2024.09 - now, Research Assistant, MBZUAI, UAE. [Advised by Zhiqiang SHEN]
• 2023.06 - 2023.10, Machine Intelligence Department, Ant Group, China. [Collaborated with Chilin FU, Xiaolu ZHANG, and Jun ZHOU]
• 2020.06 - 2021.09, Institute of Automation, Chinese Academy of Science, China.

🌞 Academic Services

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

👨‍🎓 Educations

• 2021.09 - 2024.06, Master, Southeast University (87.93/100), Nanjing.
• 2017.09 - 2021.06, Undergraduate, Chongqing University (86.88/100), Chongqing.

👻 Invited Talk

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

🏅 Awards

• (Competition)
• 1st place team (Top 1/1901) in the ATEC2023 - LLM application and security [Report], 2024.
• 7th place@Task 1-1(Image Classification) and 4th place@Task 1-2(Label Noise Detection) in the 1st Learning and Mining with Noisy Labels (LMNL) challenge of IJCAI-ECAI2022 [Certificate], [Code], 2022.
• First Prize, National CCF Green Computing Contest, 2021.
• Third Prize, National WeChat Mini Program Development Contest, 2020.
• Outstanding Winner (Top 0.1%), International Interdisciplinary Contest in Modeling (ICM), 2019.
• (Honors)
• Outstanding Graduate in Southeast University, 2024.
• Excellent Master Student Model in Southeast University, 2023.
• Excellent Master Student in Southeast University, 2022.
• Outstanding Graduate in Chongqing University, 2021.
• Advanced Individual in Chongqing city, 2021.
• (Scholarship)
• Individual Scholarship (2-time), including Lenovo Research Institute Scholarship (2023), Huawei Scholarship (2024).
• Graduate Academic Scholarship of Southeast University (3-time), 2021-2023.
• Individual Scholarship (4-time), including Huawei Scholarship (2021), Seasky Land Scholarship (2017), Texcel Scholarship (2019), Qianrong Wang Scholarship (2019).
• National Inspirational Scholarship of Chongqing University (3-time), 2017-2020.
• Comprehensive Scholarship of Chongqing University (6-time), 2017-2021.