北京大学计算机学院,教授,博导,2003年获取北京大学信息学院博士学位。研究方向为AI和数据管理结合、图数据管理和深度分析等,近期承担了国家科技重大专项、国家自然科学基金、深圳基础研究课题等一批国家级和省部级科研项目,以及与阿里、华为、中兴、电信等企业在内的一批产学合作研究项目。在数据管理领域会议和期刊上发表论文60余篇,获阿里巴巴高校合作优秀奖,CCF科技进步杰出奖,开发了ICS-GNN、LOGER、APrompt4EM等模型和方法,发表VLDB、ICDE、AAAI、IJCAI、WWW、KDD等研究论文,2024研究组囊括KDD CRAG比赛全部三个赛道第一名。相关技术在阿里巴巴公司大规模图数据上实际应用。 
 
  - 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