beat365官方网站，教授，博導，2003年獲取beat365信息學院博士學位。研究方向為AI和數據管理結合、圖數據管理和深度分析等，近期承擔了國家科技重大專項、國家自然科學基金、深圳基礎研究課題等一批國家級和省部級科研項目，以及與阿裡、華為、中興、電信等企業在内的一批産學合作研究項目。在數據管理領域會議和期刊上發表論文60餘篇，獲阿裡巴巴高校合作優秀獎，CCF科技進步傑出獎，開發了ICS-GNN、LOGER、APrompt4EM等模型和方法，發表VLDB、ICDE、AAAI、IJCAI、WWW、KDD等研究論文，2024研究組囊括KDD CRAG比賽全部三個賽道第一名。相關技術在阿裡巴巴公司大規模圖數據上實際應用。
Hao Miao, Zida Liu, Jun Gao: BSG4Bot:Efficient Bot Detection based on Biased Heterogeneous Subgraphs. ICDE 2025
Jiazun Chen, Yikuan Xia, Jun Gao, Zhao Li, Hongyang Chen. CommunityDF: A Guided Denoising Diffusion Approach for Community Search. ICDE 2025
Chenhao Xu, Chunyu Chen, Jinlin Peng, Jiannan Wang, Jun Gao: BQSched: A Non-intrusive Scheduler for Batch Concurrent Queries via Reinforcement Learning, ICDE 2025
Suchen Liu, Jun Gao, Yinjun Han, Yanglin. MoEPlan: A Lazy Learned Query-Selection Optimizer via Mixture of Optimizer Experts. DASFAA 2025
Xiaoru Qu, Yifan Wang, Zhao Li, Jun Gao: Graph-Enhanced Prompt Learning for Personalized Review Generation. Data Sci. Eng. 9(3): 309-324 (2024)
Tianyi Chen, Jun Gao, Yaofeng Tu, Mo Xu: GLO: Towards Generalized Learned Query Optimization. ICDE 2024: 4843-4855
Yikuan Xia, Jiazun Chen, Jun Gao: Winning Solution For Meta KDD Cup' 24. CoRR abs/2410.00005 (2024)
Tianyi Chen, Jun Gao, Hedui Chen, Yaofen Tu. LOGER: A Learned Optimizer towards Generating Efficient and Robust Query Execution Plans. In Proc of VLDB 2023
Jianzun Chen, Yikuan Xia, Jun Gao. CommunityAF: An Example-based Community Search Method via Autoregressive Flow. In Proc of VLDB 2023
Jialin Wang, Xiaoru Qu, Jinze Bai, Zhao Li, Ji Zhang, Jun Gao: SAGES: Scalable Attributed Graph Embedding With Sampling for Unsupervised Learning. IEEE Trans. Knowl. Data Eng. 35(5): 5216-5229 (2023)
Hao Miao, Jiazun Chen, Yang Lin, Mo Xu, Yinjun Han, Jun Gao: JG2Time: A Learned Time Estimator for Join Operators Based on Heterogeneous Join-Graphs. DASFAA (1) 2023: 132-147
Jiazun Chen, Jun Gao, Bin Cui: ICS-GNN+: lightweight interactive community search via graph neural network. VLDB J. 32(2): 447-467 (2023)
Li Zheng, Zhao Li, Jun Gao, Zhenpeng Li, Jia Wu, Chuan Zhou: Domain Adaptation for Anomaly Detection on Heterogeneous Graphs in E-Commerce. ECIR (2) 2023: 304-318
Zhao Li, Junshuai Song, Zehong Hu, Zhen Wang, Jun Gao: Constrained Dual-Level Bandit for Personalized Impression Regulation in Online Ranking Systems. ACM Trans. Knowl. Discov. Data 16(2): 23:1-23:23 (2022)
Wentao Zhang, Zeang Sheng, Ziqi Yin, Yuezihan Jiang, Yikuan Xia, Jun Gao, Zhi Yang, Bin Cui: Model Degradation Hinders Deep Graph Neural Networks. KDD 2022: 2493-2503
Jiazun Chen, Jun Gao: VICS-GNN: A Visual Interactive System for Community Search via Graph Neural Network. ICDE 2022: 3150-3153
Junshuai Song, Xiaoru Qu, Zehong Hu, Zhao Li, Jun Gao, Ji Zhang: A subgraph-based knowledge reasoning method for collective fraud detection in E-commerce. Neurocomputing 461: 587-597 (2021)
Jun Gao, Jiazun Chen, Zhao Li, and Ji Zhang. ICS-GNN: Lightweight Interactive Community Search via Graph Neural Network. PVLDB, 14(6):1006 - 1018, 2021.
Yikuan Xia, Jun Gao, Bin Cui: iMap: Incremental Node Mapping between Large Graphs Using GNN. CIKM 2021: 2191-2200
Li Zheng, Jun Gao, Zhao Li, Ji Zhang: AdaBoosting Clusters on Graph Neural Networks. ICDM 2021: 1523-1528
Jinze Bai, Jialin Wang, Zhao Li, Donghui Ding, Ji Zhang, Jun Gao. ATJ-Net: Auto-Table-Join Network for Automatic Learning on Relational Databases. In Proc. of WWW 2021
Xiaoru Qu, Zhao Li, Jialin Wang, Zhipeng Zhang, Pengcheng Zou, Junxiao Jiang, Jiaming Huang, Rong Xiao, Ji Zhang, Jun Gao*: Category-aware Graph Neural Networks for Improving E-commerce Review Helpfulness Prediction. In Proc. of CIKM, 2020, Pages 2693-2700.
Jinze Bai, Jialin Wang, Zhao Li, Donghui Ding, Jiaming Huang, Pengrui Hui, Jun Gao, Ji Zhang, and Zujie Ren. Recommendation on Heterogeneous Information Network with Type-sensitive Sampling. In Proc. of DASFAA, 2020, Pages 673-684. CCF B
Junshuai Song, Zhao Li, Zehong Hu, Yucheng Wu, Zhenpeng Li, Jian Li and Jun Gao. PoisonRec: An Adaptive Data Poisoning Framework for Attacking Black-box Recommender Systems. In Proc of ICDE 2020
