王鑫

职称:副教授、博士生导师

毕业院校:吉林大学

email:xinwang@jlu.edu.cn/xinwangjlu@gmail.com

个人主页:https://xinwangjlu.github.io/

研究方向:机器学习、数据挖掘、社会计算、图深度学习、知识图谱、推荐系统

个人简介

中国计算机学会杰出会员,中国计算机学会计算机应用专委会执行委员、大数据专委委员、人工智能与模式识别专委委员,中文信息学会社会媒体处理专委会委员。主要研究兴趣包括可信图神经网络、图数据分布外泛化、大语言模型知识编辑和公平性等。作为负责人主持国家级项目多项,包括国家自然科学基金面上基金项目1项、国家自然科学基金青年基金项目1项等。作为骨干成员参与科技部“文化科技与现代服务业”重点专项项目1项,科技部科技创新2030-“新一代人工智能”重大项目1项。以第一作者或通讯作者在人工智能领域著名国际期刊和会议上发表CCF A、B类和中科院1区论文20余篇,包括ICML,ICLR,KDD,CVPR,ACL,AAAI,EMNLP,WWW,CIKM,TKDD,JCST等。担任国际人工智能领域会议的Area Chair(ACL),Senior Program Member(AAAI)及Program Member(ICLR、Neurip、KDD、WWW、WSDM等)。


招生:欢迎202509月入学硕士研究生(推免)与我联系,要求:具有自驱力强,较强动手能力,较好英语能力,较好数学基础。



工作经历

2023.01 —— 至今       吉林大学人工智能学院    研究员/副教授

2020.11 —— 2023.01    吉林大学人工智能学院    副研究员/助理教授

2008.04 —— 2020.09    长春工程学院计算机技术与工程学院    副教授

2019.10 —— 2020.01    美国密西根州立大学计算机科学与工程系    访问学者

2018.10 —— 2019.10    美国德州农工大学计算机科学与工程系    访问学者

2016.05 —— 2016.08    加拿大渥太华大学计算机系    访问学者

教育经历

2011.09 —— 2015.06   吉林大学计算机科学与技术学院   计算机应用技术专业   博士

2005.09 —— 2008.03   哈尔滨工程大学计算机科学与技术学院   计算机应用技术专业   硕士

科研项目

  1. 2024-2027    国家自然科学基金委,面上基金项目,分布外数据场景下图表示学习可泛化性和可解释性研究,62372211,主持人

  2. 2023-2025    吉林省科技厅,国际科技合作项目,可信任图神经网络关键问题研究,20230402076GH,主持人

  3. 2017-2019    国家自然科学基金委,青年基金项目,融合多维度异质资源的推荐解释自动⽣成研究,61602057,主持人

  4. 2017-2019    中国博士后科学基金,面上项目,基于统计视角的可解释机器学习模型研究,2017M611301,主持人

  5. 2020-2021    吉林省科技厅,自然科学基金学科布局项目,大规模复杂信息网络的表示学习及表示融合研究,20200201297JC,主持人

  6. 2017-2018    吉林省科技厅,优秀青年基金项目,面向文本评论的可解释推荐系统的研究,20170520059JH,主持人

  7. 2019-2022    国家自然科学基金委,面上项目,基于条件生成对抗网络和全卷积架构深度神经网的高分辨率遥感影像分类方法研究,41871236,第二参与人

  8. 2016-2018    国家自然科学基金委,青年基金项目,面向构建过程的范畴学习模型及其适应性机制研究,61503044,第一参与人

论文选

  1. Yiwei Dai, Hengrui Gu, Ying Wang, Xin Wang*. Mitigate Extrinsic Social Bias in Pre-trained Language Models via Continuous Prompts Adjustment. EMNLP Main Conference, 2024. (清华A类,通讯作者)

  2. Hengrui Gu, Kaixiong Zhou, Yili Wang, Ruobing Wang, Xin Wang*. Pioneering Reliable Assessment in Text-to-Image Knowledge Editing: Leveraging a Fine-Grained Dataset and an Innovative Criterion. EMNLP Findings, 2024. (清华A类,通讯作者)

  3. Xin Juan, Xiao Liang, Haotian Xue, Xin Wang*. Multi-Strategy Adaptive Data Augmentation for Graph Neural Networks. Expert Systems with Applications, 2024. (中科院1区,通讯作者)

  4. Ruobing Wang, Xin He, Hengrui Gu, Xin Wang*. LGCRS: LLM-Guided Representation-Enhancing for Conversational Recommender System. ICANN, 2024. (CCF-C类,通讯作者)

  5. Mingchen Sun, YingJi Li, Ying Wang, Xin Wang. Towards Domain-Aware Stable Meta Learning for Out-of-Distribution Generalization. ACM Transactions on Knowledge Discovery from Data, 2024. (CCF-B类)

  6. Yili Wang, Haotian Xue, Xin Wang*. A two-stage co-adversarial perturbation to mitigate out-of-distribution generalization of large-scale graph. Expert Systems with Applications, 2024. (中科院1区, 通讯作者)

  7. Xu Shen, Yili Wang, Kaixiong Zhou, Shirui Pan, Xin Wang*. Optimizing OOD Detection in Molecular Graphs: A Novel Approach with Diffusion Models. KDD, 2024. (CCF-A类,通讯作者)

  8. Hengrui Gu, Kaixiong Zhou, Xiaotian Han, Ninghao Liu, Ruobing Wang, Xin Wang*. PokeMQA: Programmable knowledge editingfor Multi-hop Question Answering. ACL Main Conference, 2024. (CCF-A类,通讯作者)

  9. Yingji Li, Mengnan Du, Rui Song, Xin Wang, Ying Wang. Data-Centric Explainable Debiasing for Improving Fairness in Pre-trained Language Models. ACL Findings, 2024. (CCF-A类)

  10. Rui Miao, Kaixiong Zhou, Yili Wang, Ninghao Liu, Ying Wang, Xin Wang*. Rethinking Independent Cross-Entropy Loss For Graph-Structured Data. ICML, 2024. (CCF-A类,通讯作者)

  11. Yingji Li, Mengnan Du, Rui Song, Xin Wang, Mingchen Sun, Ying Wang. Mitigating Social Biases of Pre-trained Language Models via Contrastive Self-Debiasing with Double Data Augmentation. Artificial Intellignece, 2024. (CCF-A类)

  12. Yiwei Dai, Mingchen Sun, Xin Wang*. Pre-Training Graph Neural Networks via Weighted Meta Learning. IJCNN, 2024. (CCF-C类,通讯作者)

  13. Xin Juan, Kaixiong Zhou, Ninghao Liu, Tianlong Chen, Xin Wang*. Molecular Data Programming: Towards Molecule Pseudo-labeling with Systematic Weak Supervision. CVPR, 2024. (CCF-A类,通讯作者)

  14. Yili Wang, Kaixiong Zhou, Ninghao Liu, Ying Wang, Xin Wang*. Efficient Sharpness-Aware Minimization for Molecular Graph Transformer Models. ICLR, 2024. (清华A类,通讯作者)

  15. Zihao Chen, Ying Wang,  Fuyuan Ma, Hao Yuanhao, Xin Wang. GPL-GNN: Graph Prompt Learning for Graph Neural Network. Knowledge-based Systems, 2024. (中科院一区)

  16. Mingchen Sun, Mengduo Yang, Yingji Li, Dongmei Mu, Xin Wang, Ying Wang. Structural-aware Motif-based Prompt Tuning for Graph Clustering. Information Sciences, 2023. (中科院一区)

  17. Ying Wang, Yingji Li, Yue Wu, Xin Wang*. Exploring Multiple Hypergraphs for Heterogeneous Graph Neural Networks. Expert Systems with Applications, 2023. (中科院一区,通讯作者)

  18. Xianglin Zuo, Wenqi Chen, Xianduo Song, Xin Wang, Ying Wang. Generating Real-world Hypergraphs via Deep Generative Models. Information Sciences, 2023. (中科院1区,CCF-B类)

  19. Hengrui Gu, Xin Wang*. LAGCL: Towards Stable and Automated Graph Contrastive Learning. ADMA, 2023. (CCF-C类,通讯作者)

  20. Yingji Li, Mengnan Du, Xin Wang*, Ying Wang*. Prompt Tuning Pushes Farther, Contrastive Learning Pulls Closer: A Two-Stage Approach to Mitigate Social Biases. ACL Main Conference, 2023. (CCF-A类,通讯作者)

  21. Xin Juan, Fengfeng Zhou, Wentao Wang, Wei Jin, Jiliang Tang, Xin Wang*. INS-GNN: Improving graph imbalance learning with self-supervision. Information Sciences, 2023. (中科院1区, CCF-B类, 通讯作者)

  22. Yili Wang, Kaixiong Zhou, Rui Miao, Ninghao Liu, Xin Wang*. AdaGCL: Adaptive Subgraph Contrastive Learning to Generalize Large-scale Graph Training. In Proceedings of the 31st ACM International Conference on Information and Knowledge Management (CIKM), 2022. (CCF-B类,通讯作者)

  23. Rui Miao, YintaoYang, Yao Ma, Xin Juan, Haotian Xue, Jiliang Tang, YingWang, Xin Wang*. Negative Samples Selecting Strategy for Graph Contrastive Learning. Information Sciences, 2022. (中科院1区, CCF-B类, 通讯作者)

  24. Mingchen Sun, Kaixiong Zhou, Xin He, Ying Wang, Xin Wang. GPPT: Graph Pre-training and Prompt Tuning to Generalize Graph Neural Networks. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022. (CCF-A类)

  25. Kai Guo, Kaixiong Zhou, Xia Hu, Yi Chang, Xin Wang*. Orthogonal Graph Neural Networks. In Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI), 2022. (CCF-A类, 通讯作者)

  26. Yintao Yang, Rui Miao, Yili Wang, Xin Wang*. Contrastive Graph Convolutional Networks with Adaptive Augmentation for Text Classification. Information Processing and Management, 59(4): 102946, 2022. (中科院1区, CCF-B类, 通讯作者)

  27. Song Xianduoa#, Wang Xin#, Song Yuyuana, Zuo Xianglin, Wang Ying*. Hierarchical Recurrent Neural Networks for Graph Generation. Information Sciences, 589: 250-264, 2022. (中科院1区, CCF-B类, 共同一作)

  28. Xin Juan, Meixin Peng, Xin Wang*. Exploring Self-training for Imbalanced Node Classification. International Conference on Neural Information Processing (ICONIP), 2021: 28-36. (CCF-C类, 通讯作者)

  29. Ying Wang, Hongji Wang, Xinrui Huan, Xin Wang∗. Exploring Graph Capsual Network for Graph Classification. Information Sciences, 581: 932-950, 2021. (中科院1区, CCF-B类, 通讯作者)

  30. Siyuan Guo, Ying Wang, Hao Yuan, Zeyu Huang, Jianwei Chen, Xin Wang*. TAERT: Triple-Attentional Explainable Recommendation with Temporal Convolutional Network. Information Sciences, 567: 185-200, 2021. (中科院1区, CCF-B类, 通讯作者)

  31. Xin Wang, Ying Wang. Attention guide Walk Model in Heterogeneous Information Network for Multi-style Recommendation Explanation. In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI), 2020: 6275-6282. (CCF A类, 第一作者)

  32. Xiaoyang Wang, Yao Ma, Wei Jin, Xin Wang, Jiliang Tan, Jian Yu. Traffic Speed Prediction Based on Spatial Temporal Graph Neural Network. In Proceedings of the World Wide Web Conference (WWW), 2020: 1082-1092. (CCF-A类)

  33. Xin Wang, Ying Wang, Wanli Zuo, Yongguo, Cai. Exploring social context for topic identification in short and noisy text. In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI), 2015, 1868-1874. (CCF-A类, 第一作者)

  34. Ying Wang, Xin Wang, Jiliang Tang, WanliZuo. Modeling status theory in trust prediction. In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI), 2015, 1875-1881. (CCF-A类)

  35. Ying Wang, Xin Wang*, WanliZuo. Research on trust prediction from a sociological perspective. Journal of Computer Science and Technology (JCST), 2015, 30(4): 843-858. (CCF-B类, 通讯作者)

  36. Xin Wang, Ying Wang, Jianhua, Guo. Building trust networks in the absence of trust relations. Frontiers of Information Technology & Electronic Engineering (FITEE), 2017, 18 (10): 1591-1600. (CCF-C类, 第一作者)

  37. Yunzhi Ling, Ying Wang, Xin Wang, Yunhao Ling. Exploring Common and Label-Specific Features for Multi-Label Learning with Local Label Correlations. IEEE Access, 2020. (中科院2区)

  38. Xin Wang, Ying Wang, Hongbin Sun. Exploring the combination of dempster- shafer theory and neural network for predicting trust and distrust. Computational Intelligence and Neuroscience, 2016, 5403105: 1-12. (JCR1区, 第一作者)

  39. Xin Wang, Wanli Zuo, Ying Wang. A novel approach to word sense disambiguation based on topical and semantic association. The Scientific World Journal, 2013, 586327: 1-8. (JCR3区, 第一作者)

  40. 王鑫, 王英, 左万利. 基于交互意见和地位理论的符号网络链接预测模型研究. 计算机研究与发展, 2016(4): 764-775.  (CCF-A类中文, 第一作者)

  41. 吴越, 王英, 王鑫, 徐正祥, 李丽娜. 基于超图卷积的异质网络半监督节点分类. 计算机学报, 2021, 44 (11): 2248-2260. (CCF-A类中文)

  42. 王英, 王鑫, 左万利. 基于社会学理论的信任关系预测模型研究. 软件学报, 2014, 25(12): 2893-2904. (CCF-A类中文)

  43. 孙小婉, 王英, 王鑫, 孙玉东. 面向双注意力网络的特定方面情感分析模型. 计算机研究与发展, 2019, 56(11): 2384-2395. (CCF-A类中文)

  44. 王英, 左祥麟, 左万利, 王鑫. 基于本体的Deep Web查询接口集成. 计算机研究与发展, 2012, 49(11): 2383-2394. (CCF-A类中文)



获奖情况

  1. 2017,中国商业联合会,科技进步奖,社会化搜索技术与软件,二等奖

  2. 2016,吉林省科学技术奖励委员会,科技进步奖,计及风光储互补的区域电力经济调度研究及其风电消纳应用,二等奖

  3. 2015,中国商业联合会,科技进步奖,深度网搜索技术的研究与应用,三等奖

  4. 2012,吉林省科学技术奖励委员会,科学技术奖,基于主题爬行和本体的Deep Web搜索技术,三等奖

社会兼职

中国计算机学会杰出会员

中国计算机学会计算机应用专委会执行委员

中国计算机学会大数据专委委员

中国计算机学会人工智能与模式识别专委委员

中文信息学会社会媒体处理专委会委员

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