Dong-Dong Wu (吴东冬) is currently a third-year master student in School of computer science and engineering at Southeast University. He is a member of Pattern Learning and Mining Lab (PALM) supervised by Prof. Min-Ling Zhang. Dong-Dong Wu received his B.Eng. degree in School of Big Data & Software Engineering at Chongqing University in Jun 2021. In the same year, he was admitted to study for an M.Eng. degree in Southeast University without entrance examination.

My primary research interest lies in the field of trustworthy weakly supervised learning, . Specially now I am focusing on partial label learning, dataset condensation, long-tailed learning, knowledge distillation, and uncertainty calibration, model defense. Here is my CV.

If you are interested in discussing with me, feel free to drop me an email (dongdongwu@seu.edu.cn, dongdongwu1230@gmail.com) or add my wechat (kaefer1999).

Note: I am seeking a research assistant (RA) position opportunities from June 2023 through March 2024. Please feel free to contact me if you have any potential openings.

🎈 Github

• [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%.

👨‍💻 Internships

• 2023.06 - 2023.10, Machine Intelligence Department, Ant Group, China.
• 2020.06 - 2021.09, Institute of Automation, Chinese Academy of Science, China, [Admission] [Certificate].

🌞 Professional Services

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

🏅 Honors and Awards

• 6th place@final list and 1th place@defense session (track: AI generated news detection) in the ATEC2023, 2024.
• Outstanding Graduate Student Model in Southeast University, 2023.
• Lenovo Research Institute Scholarship, 2023.
• Outstanding Graduate Student in Southeast University, 2022.
• 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.
• Graduate Academic Scholarship of Southeast University (3-time), 2021-2022.
• Advanced Individual in Chongqing city, 2021.
• Outstanding Graduates in Chongqing University, 2020.
• First Prize (top 3%), National CCF Green Computing Contest, 2021.
• Third Prize (top 5%), National WeChat Mini Program Development Contest, 2020.
• Outstanding Winner (top 0.1%), International Interdisciplinary Contest in Modeling (ICM), 2019.
• Individual Scholarship (4-time), including Huawei Scholarship, Seasky Land Scholarship, Texcel Scholarship, Qianrong Wang Scholarship).
• National Inspirational Scholarship of Chongqing University (3-time).
• Comprehensive Scholarship of Chongqing University (6-time).

👨‍🎓Educations

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