E-Mail：liandefu@ustc.tsg211.com
个人主页：http://staff.ustc.tsg211.com/~liandefu
主要研究方向：可信人工智能、高维向量检索、机器学习理论
连德富，国家优青，图书馆VIP特任教授，博士生导师，现任计算机科学与技术学院副院长。曾任电子科技大学副教授、悉尼科技大学访问学者，曾入选微软亚洲研究院铸星计划。主要研究方向包括大规模分类、深度学习、因果机器学习等，研发了RecStudio开源推荐系统和FuxiTS时序预测和检测系统，主持了国家自然科学基金优秀青年科学基金、面上项目，科技部科技创新2030重大项目课题，国防科技173重点项目等。他在KDD、NeurIPS、TPAMI、TKDE等CCF-A类会议和期刊发表论文90余篇。曾获得教育部自然科学一等奖、CCF自然科学一等奖、安徽省教学成果一等奖、四川省教学成果二等奖、APWeb 2016最佳学生论文、WWW 2021最佳论文候选、WISE 2022最佳论文奖等。
获奖情况：
2023 CCF科技成果奖自然科学一等奖（排名第二）
2023 KDD Cup Next Product Recommendation/Generation 两个赛道分获季军和亚军（全球高校冠军）
2023 RecSys Challenge 第三名
2022 NeurIPS Traffic4Cast 比赛双赛道冠军
2022 中科大招生先进个人
2022 NeurIPS Top Reviewers
2022 WISE Best Paper Award
2021 杨元庆教育基金
2021 中科大招生先进个人
2021 安徽省教学成果奖一等奖（排名第7）
2020 中科大优秀班主任
2019 计算机学院“新创学者”
2018 计算机学院“新创学者”
2018 教育部高等学校科学研究优秀成果奖自然科学一等奖（排名第4）
2018 四川省教学成果奖二等奖（排名第5）
2016 APWeb best student paper runner up
代表性论著：
1. Zepu Lu, Jin Chen, Defu Lian*, Zaixi Zhang, Yong Ge and Enhong Chen. Knowledge Distillation for High Dimensional Search Index. The 37th Annual Conference on Neural Information Processing Systems (NeurIPS 2023), Dec. 2023.
2. Wuchao Li, Chao Feng, Defu Lian*, Yuxin Xie, Haifeng Liu, Yong Ge, and Enhong Chen. Learning Balanced Tree Indexes for Large-Scale Vector Retrieval. The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023), pp. 1353-1362, Aug. 2023
3. Chenwang Wu, Xiting Wang, Defu Lian*, Xing Xie, and Enhong Chen. A Causality Inspired Framework for Model Interpretation. The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023), pp. 2731-2741, Aug. 2023
4. Chenwang Wu, Defu Lian*, Yong Ge, Zhihao Zhu, and Enhong Chen. Influence-Driven Data Poisoning for Robust Recommender Systems. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 45(10), 2023
5. Zhaoyi Li, Ying Wei and Defu Lian*. Learning to Substitute Spans towards Improving Compositional Generalization. The 61st Annual Meeting of the Association for Computational Linguistics (ACL 2023), pp. 2791-2811, July 2023.
6. Xu Huang, Defu Lian*, Jin Chen, Liu Zheng, Xing Xie and Enhong Chen. Cooperative Retriever and Ranker in Deep Recommenders. The 32nd Web Conference (WWW 2023), pp. 1150-1161, Apr. 2023.
7. Chao Feng, Wuchao Li, Defu Lian*, Zheng Liu and Enhong Chen. Recommender Forest for Efficient Retrieval. The 36th Annual Conference on Neural Information Processing Systems (NeurIPS 2022), pp. 38912-38924, Dec. 2022
8. Leyan Deng, Defu Lian*, Chenwang Wu and Enhong Chen. Graph Convolution Network based Recommender Systems: Learning Guarantee and Item Mixture Powered Strategy. The 36th Annual Conference on Neural Information Processing Systems (NeurIPS 2022), pp. 3900-3912, Dec. 2022
9. Jin Chen, Defu Lian*, Yucheng Li, Baoyun Wang, Kai Zheng and Enhong Chen. Cache-Augmented Inbatch Importance Resampling for Training Recommender Retriever. The 36th Annual Conference on Neural Information Processing Systems (NeurIPS 2022), pp. 34817-34830, Dec. 2022
10. Defu Lian, Xing Xie, Enhong Chen and Hui Xiong. Product Quantized Collaborative Filtering. IEEE Transaction on Knowledge and Data Engineering (IEEE TKDE), 33(9), 2021
11. Qi Liu, Jin Zhang, Defu Lian*, Yong Ge, Jianhui Ma and Enhong Chen. Online Additive Quantization. The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2021), pp. 1098-1108, Aug. 2021.
12. Yongji Wu, Defu Lian*, Neil Gong, Lu Yin, Mingyang Yin, Jingren Zhou and Hongxia Yang. Linear-Time Self Attention with Codeword Histogram for Efficient Recommendation. The 30th Web Conference (WWW 2021), pp. 1262-1273, virtual, Apr. 2021
13. Defu Lian, Yongji Wu, Yong Ge, Xing Xie and Enhong Chen. Geography-Aware Sequential Location Recommendation. The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2020), pp. 2009–2019, Aug. 2020.
14. Defu Lian, Haoyu Wang, Zheng Liu, Jianxun Lian, Enhong Chen and Xing Xie. LightRec: a Memory and Search-Efficient Recommender System. The 29th Web Conference (WWW 2020), pp. 695–705, Apr. 2020
15. Defu Lian, Qi Liu and Enhong Chen. Personalized Ranking with Importance Sampling. The 29th Web Conference (WWW 2020), pp. 1093–1103, Apr. 2020
