江佳伟，博士，武汉大学计算机学院教授、博士生导师。从事机器学习算法、大数据处理与分析、图计算、联邦学习等方向的研究，发表CCF-A 类论文50余篇。主持国家自然科学基金优青项目(海外)， 国家重点研发计划课题，湖北省重点研发专项，CCF-蚂蚁科研基金等项目。

主要奖励：

1）CCF优秀博士学位论文奖（每年10名）

2）ACM China全国新星提名（每年5名）

3）ACM China SIGMOD优秀博士学位论文奖

学术服务：

长期担任VLDB、KDD、ICDE、WWW、AAAI、DASFAA等国际会议程序委员，IEEE TKDE、VLDB Journal等期刊审稿人。

指导学生竞赛：

1）中国研究生人工智能创新大赛，一等奖，2022年

2）全国大学生计算机系统能力大赛，特等奖(唯一)，2023年

3）全国大学生计算机系统能力大赛-智能系统创新设计赛(小米杯)，一等奖，2024年

4）花旗杯金融创新应用大赛，特等奖(唯一)，2024年

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欢迎报考本组硕士、博士。

本组长期与国内工业界、海外研究机构保持密切合作。

本组长期招聘博士后（重点资助），并协助申请武汉大学弘毅博士后（入选后年薪30万），详见：

https://www.whu.edu.cn/info/1118/174554.htm

https://cs.whu.edu.cn/info/1040/43021.htm

代表性论文：

- Jiawei Jiang, Shaoduo Gan, Bo Du, Gustavo Alonso, Ana Klimovic, Ankit Singla, Wentao Wu, Sheng Wang, Ce Zhang. A Systematic Evaluation of Machine Learning on Serverless Infrastructure. The VLDB Journal, 2024.

- Jiawei Jiang, Yi Wei, Yu Liu, Wentao Wu, Chuang Hu, Zhigao Zheng, Ziyi Zhang, Yingxia Shao, Ce Zhang. How good are machine learning clouds? Benchmarking two snapshots over 5 years. The VLDB Journal, 2024.

- Jiawei Jiang, Lukas Burkhalter, Fangcheng Fu, Bolin Ding, Bo Du, Anwar Hithnawi, Bo Li, Ce Zhang. VF-PS: How to Select Important Participants in Vertical Federated Learning, Efficiently and Securely? NeurIPS. 2022.

- Jiawei Jiang, Yusong Hu, Xiaosen Li, Wen Ouyang, Zhitao Wang, Fangcheng Fu, Bin Cui. Analyzing Online Transaction Networks with Network Motifs. SIGKDD. 2022.

- Jiawei Jiang, Shaoduo Gan, Yue Liu, Fanlin Wang, Gustavo Alonso, Ana Klimovic, Ankit Singla, Wentao Wu, Ce Zhang. Towards Demystifying Serverless Machine Learning Training. SIGMOD, 2021.

- Jiawei Jiang, Fangcheng Fu, Tong Yang, Yingxia Shao, Bin Cui. SKCompress: compressing sparse and nonuniform gradient in distributed machine learning. The VLDB Journal, 2020.

- Jiawei Jiang, Pin Xiao, Lele Yu, Xiaosen Li, Xupeng Miao, Zhipeng Zhang, Bin Cui. PSGraph: How Tencent trains large-scale graphs with Spark? ICDE, 2020.

- Jiawei Jiang, Bin Cui, Ce Zhang, Fangcheng Fu. DimBoost: Boosting Gradient Boosting Tree to Higher Dimensions. ACM SIGMOD, 2018.

- Jiawei Jiang, Fangcheng Fu, Tong Yang, Bin Cui. SketchML: Accelerating Distributed Machine Learning with Data Sketches. ACM SIGMOD, 2018. 

- Jiawei Jiang, Bin Cui, Ce Zhang, Lele Yu. Heterogeneity-aware Distributed Parameter Servers. ACM SIGMOD, 2017.

- Jiawei Jiang, Yunhai Tong, Hua Lu, Bin Cui, et al. GVoS: A General System for Near-Duplicate Video Related Applications on Storm. ACM TOIS, 2017.

- 江佳伟, 符芳诚, 邵蓥侠, 崔斌. 面向高维特征和多分类的分布式梯度提升树. 软件学报, 2019.

- Yuxiang Wang, Xiao Yan, Chuang Hu, Quanqing Xu, Chuanhui Yang, Fangcheng Fu, Wentao Zhang, Hao Wang, Bo Du, Jiawei Jiang*. Generative and Contrastive Paradigms Are Complementary for Graph Self-Supervised Learning. ICDE, 2024. (corresponding author)

- Qiang Huang, Xin Wang, Susie Xi Rao, Zhichao Han, Zitao Zhang, Yongjun He, Quanqing Xu, Yang Zhao, Zhigao Zheng, Jiawei Jiang*. BenchTemp: A General Benchmark for Evaluating Temporal Graph Neural Networks. ICDE, 2024. (corresponding author)

- Fangcheng Fu, Xuanyu Wang, Jiawei Jiang*, Huanran Xue, and Bui Cui. ProjPert: Projection-based Perturbation for Label Protection in Split Learning based Vertical Federated Learning. TKDE, 2024. (corresponding author)

- Shaoduo Gan, Jiawei Jiang*, Binhang Yuan, Ce Zhang, XiangruLian, RuiWang, and others. BAGUA: Scaling up Distributed Learning with System Relaxations. VLDB, 2022. (corresponding author)

- Yang Li, Yu Shen, Wentao Zhang, Jiawei Jiang*, Bolin Ding, Yaliang Li, Jingren Zhou, Zhi Yang, Wentao Wu, Ce Zhang, Bin Cui. VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition. VLDB, 2021. (corresponding author)

- Yang Li, Jiawei Jiang*, Jinyang Gao, Yingxia Shao, Ce Zhang, Bin Cui. Efficient Automatic CASH via Rising Bandits. AAAI, 2020. (corresponding author)

- Wentao Zhang, Jiawei Jiang*, Yingxia Shao, Bin Cui. Efficient Diversity-Driven Ensemble for Deep Neural Networks. ICDE, 2020. (corresponding author)

- Fangcheng Fu, Jiawei Jiang*, Yingxia Shao, Bin Cui. An experimental evaluation of large scale gbdt systems. VLDB, 2019. (corresponding author)

- Zhipeng Zhang, Jiawei Jiang*, Wentao Wu, Ce Zhang, Lele Yu, Bin Cui. Mllib*: Fast training of glms using spark mllib. ICDE, 2019. (corresponding author)