琚玮
谷歌学术：https://scholar.google.com/citations?user=GX05vA4AAAAJ&hl=en
个人主页：https://juweipku.github.io/
主要研究方向
图表示学习、图神经网络、推荐系统、AI4Science、知识图谱
教育经历
博士 计算机学院 北京大学 2019-2022 导师：张铭
硕士 数学科学学院 北京大学 2017-2019 导师：周铁
学士 数学学院 四川大学 2012-2017
工作经历
副教授 计算机学院 四川大学 2024-至今
博士后 计算机学院 北京大学 2022-2024 合作导师：张铭
个人介绍
琚玮，四川大学计算机学院副教授。于2022年在北京大学计算机学院获博士学位，长期从事人工智能、机器学习、数据挖掘等方面的研究。研究兴趣主要集中图表示学习、推荐系统、时空数据分析以及交叉学科应用（AI4Science）等。主持国家自然科学基金青年科学基金项目和中国博士后科学基金面上项目，作为项目骨干参与多项国家重点研发计划和企业横向基金课题。近5年来共发表国际顶级学术论文40余篇，其中以第一作者/共同一作/通讯作者身份发表论文30余篇，相关研究成果发表在Nature Machine Intelligence (Nature 子刊)、ICML、AAAI、IJCAI、TKDE、TOIS、TNNLS等机器学习和数据挖掘的国际顶级会议和期刊上，并荣获2022年国际顶级会议ICDM的最佳论文提名奖和2023年度ACM SIGCSE中国“优博奖”。并在多个国际顶级会议和期刊如 ICLR、ICML、NeurIPS、KDD、WWW、AAAI、IJCAI、TKDE、TOIS、TNNLS等担任程序委员会成员和审稿人。此外，长期担任由中国科协和教育部联合组织的中学生科技创新后备人才培养计划（“英才计划”）的辅导老师，指导优秀中学生进行科研探索和科技创新。IEEE会员，ACM会员。
主要论文
Wei Ju, Zhengyang Mao, Siyu Yi, Yifang Qin, Yiyang Gu, Zhiping Xiao, Yifan Wang, Xiao Luo, Ming Zhang. Hypergraph-enhanced Dual Semi-supervised Graph Classification. ICML 2024. To appear. CCF-A
Wei Ju, Yiyang Gu, Binqi Chen, Gongbo Sun, Yifang Qin, Xingyuming Liu, Xiao Luo, Ming Zhang. GLCC: A General Framework for Graph-level Clustering. AAAI 2023: 4391-4399. CCF-A
Wei Ju, Xiao Luo, Meng Qu, Yifan Wang, Chong Chen, Minghua Deng, Xian-Sheng Hua, Ming Zhang. TGNN: A Joint Semi-supervised Framework for Graph-level Classification. IJCAI 2022: 2122-2128. CCF-A
Wei Ju, Siyu Yi, Yifan Wang, Qingqing Long, Junyu Luo, Zhiping Xiao, Ming Zhang. A Survey of Data-Efficient Graph Learning. IJCAI 2024. To appear. CCF-A
Wei Ju, Yiyang Gu, Zhengyang Mao, Ziyue Qiao, Yifang Qin, Xiao Luo, Hui Xiong, Ming Zhang. GPS: Graph Contrastive Learning via Multi-scale Augmented Views from Adversarial Pooling. SCIENCE CHINA Information Sciences 2024. To appear. CCF-A
Wei Ju, Yusheng Zhao, Yifang Qin, Siyu Yi, Jingyang Yuan, Zhiping Xiao, Xiao Luo, Xiting Yan, Ming Zhang. COOL: A Conjoint Perspective on Spatio-Temporal Graph Neural Network for Traffic Forecasting. Information Fusion 2024 107: 102341
Wei Ju, Yifang Qin, Ziyue Qiao, Xiao Luo, Yifan Wang, Yanjie Fu, Ming Zhang. Kernel-based Substructure Exploration for Next POI Recommendation. ICDM 2022: 221-230. CCF-B, 最佳论文提名
Wei Ju, Junwei Yang, Meng Qu, Weiping Song, Jianhao Shen, Ming Zhang. KGNN: Harnessing Kernel-based Networks for Semi-supervised Graph Classification. WSDM 2022: 421-429. CCF-B
Wei Ju, Zhengyang Mao, Ziyue Qiao, Yifang Qin, Siyu Yi, Zhiping Xiao, Xiao Luo, Yanjie Fu, Ming Zhang. Focus on Informative Graphs! Semi-supervised Active Learning for Graph-level Classification. Pattern Recognition 2024 153: 110567. CCF-B
Wei Ju, Zheng Fang, Yiyang Gu, Zequn Liu, Qingqing Long, Ziyue Qiao, Yifang Qin, Jianhao Shen, Fang Sun, Yifan Wang, Zhiping Xiao, Junwei Yang, Jingyang Yuan, Yusheng Zhao, Yifan Wang, Xiao Luo, Ming Zhang. A Comprehensive Survey on Deep Graph Representation Learning. Neural Networks 2024 173: 106207. CCF-B
Wei Ju, Zequn Liu, Yifang Qin, Bin Feng, Chen Wang, Zhihui Guo, Xiao Luo, Ming Zhang. Few-shot Molecular Property Prediction via Hierarchically Structured Learning on Relation Graphs. Neural Networks 2023 163:122-131. CCF-B
Wei Ju, Yiyang Gu, Xiao Luo, Yifan Wang, Haochen Yuan, Huasong Zhong, Ming Zhang. Unsupervised Graph Representation Learning with Hierarchical Contrasts. Neural Networks 2023 158:359-368. CCF-B
Wei Ju, Xiao Luo, Zequ Ma, Junwei Yang, Minghua Deng, Ming Zhang. GHNN: Graph Harmonic Neural Networks for Semi-supervised Graph-level Classification. Neural Networks 2022 151:70-79. CCF-B
Wei Ju, Yifang Qin, Siyu Yi, Zhengyang Mao, Kangjie Zheng, Luchen Liu, Xiao Luo, Ming Zhang. Zero-shot Node Classification with Graph Contrastive Embedding Network. Transactions on Machine Learning Research 2023