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教授

王英


基本情况
姓名: 王英

63E6 

性别:
职称: 教授
最高学历: 研究生
最高学位: 博士
Email: wangying2010@jlu.edu.cn
详细情况
所在学科专业: 计算机软件与理论/计算机应用
所研究方向:

【研究方向】人工智能、机器学习、数据挖掘、自然语言处理、社会计算、信息检索

【硕士生招生专业】

计算机科学与技术学院,081200计算机科学与技术(学术学位)

计算机科学与技术学院,085400电子信息、085404计算机技术(专业学位)

软件学院,083500软件工程(学术学位)

软件学院,085400电子信息、085405软件工程(专业学位)

【博士生招生】

要求:具有机器学习基础,较强动手能力,较好英语听说读写能力,较好数学基础


欢迎有意保送和报考的硕士/博士研究生同学与我联系


讲授课程: 《操作系统》(课程链接
《图机器学习》
《操作系统实验》(课程链接
教育经历:

2024/12-2025/08  新加坡南洋理工大学 访问学者(合作导师:孙爱欣(Aixin Sun)教授)

2013/09-2014/09  美国亚利桑那州立大学 访问学者(合作导师:刘欢(Huan Liu)教授)
2010/12-2015/07  吉林大学 数学学院 博士后(合作导师:李辉来教授)
2007/09-2010/07  吉林大学 计算机科学与技术学院 博士
2004/09-2007/07  吉林大学 计算机科学与技术学院 硕士
2000/09-2004/07  黑龙江大学 计算机科学与技术学院 本科

工作经历:

2025/01-至今  吉林大学 “唐敖庆学者”英才教授

2020/09-至今  吉林大学计算机科学与技术学院 教授

2023/11-2024/11  吉林大学科研院国内合作处 副处长
2015/09-2020/08  吉林大学计算机科学与技术学院 副教授
2010/07-2015/08  吉林大学计算机科学与技术学院 讲师

科研项目:

主持项目:   

1)国家自然科学基金面上项目, 大规模复杂动态网络可扩展与可泛化表征学习研究, 62272191,2023/01-2026/12, 54万,主持;

2)国家自然科学基金面上项目,大规模异质信息网络摘要和摘要可解释性研究,618721612019/01-2022/12,63万,主持;

3)国家自然科学青年基金项目,异质社会网络信息可信度评估与建模研究,613001402014/01-2016/1225万,主持;

4)苏州市科技攻关项目,面向工矿行业的多模态超融合认知大模型关键技术研发,SYG20250962026/01-2027/12, 25万,主持;

5)先进技术类项目, 2023X014J00150, 2023/12-2025/03,100, 主持;

6)吉林省科技厅国际科技合作项目,分布外数据场景下可泛化图表示学习研究,20240402067GH, 2024/01-2026/12,15万,主持;

7)吉林省科技厅重点研发项目,大规模医疗数据因果推理及应用,20220201153GX2022/07-2025/0650万,主持;

8)吉林省发改委项目,大数据下网络摘要和查询研究及应用,2019C053-82019/01-2020/1220万,主持;

9)吉林省科技发展计划项目,“互联网+政府政务新媒体”大数据下的信息传播和效能评估研究,20180101328JC2018/01-2020/1212万,主持;

10)吉林省科技计划青年科研基金项目,在线社会网络中可信任信息评估软件的研制,20130522112JH2013/01-2015/123万,主持;

11)中国博士后基金项目,基于朴素贝叶斯信任推理的微博虚假话题检测模型研究,2012M5108792012/09-2013/095万,主持;

12)工业和信息化部电子第五研究所重点实验室开放课题“多噪声场景下的异质信息网络漏洞检测研究”, HK2023035282024/01-2024/125, 主持;

(13) 中共长春市委政法委项目,以智慧城市建设推进我市市域社会治理能力现代化,3D42130134212021/05-2021/122万,主持;

14)吉林大学青年学者交叉项目,大规模医疗知识图谱构建和因果推理研究,JLUXKJC20202072021/05-2021/1220, 主持;

(15)符号计算与知识工程教育部重点实验室开发基金,大规模异构网络的深度表示学习,202101222, 2021/01-2022/125万,主持;

16)中央高校基本科研业务费专项资金,吉林大学基本科研业务费科学前沿与交叉项目“面向语义网的人物社会关系搜索研究”,2011031292011/01-2012/125万,主持;
17)吉林大学优秀青年科学基金后备人选培育计划项目,2015/07-2017/0618万,主持;
18)吉林大学青年教师创新项目,实时搜索关键技术研究,2011/05-2013/053万,主持;

19)科技部2030新一代人工智能重大项目,复杂动态系统智能理论与方法研究,2021ZD01125002021/12-2025/122022-2025496万,子课题负责人,个人可支配经费60.


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主持教研项目:

1.吉林大学2015年度本科教学改革研究项目“教学更新制导的操作系统课程建设(2015XYB074)”(2015.06-2016.05).


学术论文:

代表性论文:

[1]Xiaosong Yuan, Ying Wang(王英,通讯作者). SeaRAG: Reducing Hallucination in Retrieval-Augmented Generation via Statement-Entity Adaptive Ranking[C]. In Proceedings of the ACM Web Conference (WWW), 2026. (CCF A)

[2]Xiaosong Yuan, Chen Shen, Shaotian Yan, Kaiyuan Liu, Xiaofeng Zhang, Liang Xie, WenxiaoWang, Renchu Guan, Ying Wang(王英,通讯作者), Jieping Ye. Differential Fine-Tuning Large Language Models Towards Better Diverse Reasoning Ailities[C]. In Proceedings of the International Conference on Learning Representations (ICLR), 2026. (清华A)

[3]Yiyang Liu, Mingchen Sun, Yutong Zhang, Ying Wang(王英,通讯作者). Information Bottleneck based Graph Structural Learning for OOD Generalization[J]. Information Processing & Management (IPM), 2026, 63(5): 1-13.(中科院一区,IF6.9)

[4]Fuyuan Ma, Yuhan Wang, Shixuan Ma, Yongzhen Li, Xin Wang, Ying Wang(王英,通讯作者). DyFiLM: A Framework to Handle the Distribution Shifts on Dynamic Graphs with Hypernetworks[J]. Neural Networks, 2026, 193(108006): 1-14. (CCF B, IF: 9.0)

[5]Xianglin Zuo, Baohang Wei, Hao Yuan, Ying Wang(王英,通讯作者). Graph Causal Representation Learning for Out-of-Distribution Generalization[J]. Neural Networks, 2026, 195(108208): 1-14. (CCF B, IF:9.0)

[6]Xiaosong Yuan, Chen Shen, Renchu Guan, Ying Wang(王英, 通讯作者), Xuhang Chen. LSFusion: Ladder-Side Attribute Composition for Multi-Aspect Controllable Text Generation[J]. IEEE Transactions on Consumer Electronics, 2026.(中科院二区,IF10.9)

[7]Mingchen Sun, Jiahui Hou, Yutong Zhang, Yingji Li, Ying Wang(王英, 通讯作者). Generalizable Graph Prompt Learning Framework with Model-level Prompt Injection and Two-Stage Prompt Tuning[C]. In Proceedings of the 31st Conference on Knowledge Discovery and Data Mining(KDD), 2025, pp2747-2755. (CCF A类)

[8]Yunxia Zhang, Mingchen Sun, Yutong Zhang, Funing Yang, Ying Wang(王英, 通讯作者). Graph OOD Detection via Plug-and-Play Energy-based Evaluation[C]. In Proceedings of the 34th International Joint Conference on Artificial Intelligence(IJCAI), 2025, pp7065-7073. (CCF A类)

[9]Yingji Li, Mengnan Du, Rui Song, Mu Liu, Ying Wang(王英,通讯作者). BATED: Learning fair representation for Pre-trained Language Models via biased teacher-guided disentanglement[J]. Artificial Intelligence, 2025, 348(104401): 1-23. (CCF A, IF14.05)

[10]Yili Wang, Yaohua Liu, Ninghao Liu, Rui Miao, Ying Wang(王英), Xin Wang. AdaGCL+: An Adaptive Subgraph Contrastive Learning Towards Tackling Topological Bias[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence (TAPMI), 2025, 47(9): 8073-8087. (CCF A)

[11]Yili Wang, Yixin Liu, Xu Shen, Chenyu Li, Rui Miao, Kaize Ding, Ying Wang(王英), Shirui Pan, Xin Wang. Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark[C]. In Proceedings of the International Conference on Learning Representations (ICLR), 2025, pp1-27. (清华A)

[12]Ruobing Wang, Qiaoyu Tan, Yili Wang, Ying Wang(王英), Xin Wang. CrystalICL: Enabling In-Context Learning for Crystal Generation[C]. In Proceedings of the International Conference on Empirical Methods in Natural Language Processing (EMNLP), 2025, pp18440-18455. (清华A)

[13]Funing Yang, Haihui Du, Xingliang Zhang, Yongjian Yang, Ying Wang(王英,通讯作者). Self-supervised Category-Enhanced Graph Neural Networks for Recommendation[J]. Knowledge Based System, 2025, 311(113109), 1-11. (中科院一区,IF:7.6)

[14]Ying Wang(王英), Xianglin Zuo, Xinglin Liu, Junhe Zhang, Bo Yang. Event Prediction Model Combining Ordinary Differential Equation and Hypernetworks[J]. Neural Networks, 2025, 191(107731): 1-12. (CCF B, IF: 9.0)

[15]Ying Wang(王英), Fuyuan Ma, Zhaoqi Yang, Yaodi Zhu, Bo Yang, Pengfei Shen, Lei Yun. Rumor Detection with Adaptive Data Augmentation and Adversarial Training[J]. Journal of Artificial Intelligence Research (JAIR), 2025, 82: 1175-1204. (CCF B,IF:8.8)

[16]Xianglin Zuo, Xin He, Tianhao Jia, Ying Wang(王英,通讯作者). Graph Collaborative Filtering Model Combing Time Factor and Attention Mechanism[J]. Journal of Artificial Intelligence Research (JAIR), 2025, 8: 1-15.(CCF B,IF:2.9)

[17]Xin He, Wenqi Fan, Ruobing Wang, Ying Wang(王英), Yili Wang, Shirui Pan, Xin Wang. Balancing User Preferences by Social Networks: A Condition-Guided Social Recommendation Model for Mitigating Popularity Bias[J]. Neural Networks, 2025, 187(107317): 1-11. (CCF B,IF:9.0)

[18]Chenyu Li, Ying Wang(王英,通讯作者), Zihao Chen. DynTSM:A Dynamic Graph Contrastive Representation Learning Method Based on Temporal and Structural Perturbations[C]. In Proceedings of the International Conference on Systems, Man, and Cybernetics, 2025, pp1-6. (CCF C)

[19]Fuyuan Ma, Yuhan Wang, Shixuan Ma, Yongzhen Li, Ying Wang(王英,通讯作者). Multi-Scale Control Model for Network Group Behavior[C]. In Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2025, pp259-270. (CCF C)

[20]Fuyuan Ma, Yuhan Wang, Junhe Zhang, and Ying Wang(王英,通讯作者). Source Identification Model Based on Label Propagation and Graph Ordinary Differential Equation[C]. In Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2025, pp128-140. (CCF C)

[21]Xinglin Liu, Yutong Zhang, Youhan Qi, Xin Wang, Ying Wang(王英,通讯作者). Hypergraph Structure Recommendation Model with Counterfactual Learning[C]. IEEE International Conference on Big Data(IEEE BigData), 2025. (CCF C)

[22]Xiaosong Yuan, Chen Shen, Shaotian Yan, Xiaofeng Zhang, Liang Xie, WenxiaoWang, Renchu Guan, Ying Wang(王英,通讯作者), Jieping Ye. Instance-adaptive Zero-shot Chain-of-Thought Prompting[C]. In Proceedings of the International Conference on Neural Information Processing Systems (NeurIPS), 2024, pp1-18. (CCF A)

[23]Yingji Li, Mengnan Du, Xin Wang, Mingchen Sun, Ying Wang(王英,通讯作者). Mitigating Social Biases of Pre-trained Language Models via Contrastive Self-Debiasing with Double Data Augmentation[J]. Artificial Intelligence, 2024, 332(104143): 1-17. (CCF A, IF14.05)

[24]Yili Wang, Kaixiong Zhou, Ninghao Liu, Ying Wang(王英), Xin Wang. Efficient Sharpness-Aware Minimization for Molecular Graph Transformer Models[C]. In Proceedings of the International Conference on Learning Representations (ICLR), 2024, pp1-23. (清华A)

[25]Yingji Li, Mengnan Du, Rui Song, Xin Wang, Ying Wang(王英,通讯作者). Data-Centric Explainable Debiasing for Improving Fairness in Pre-trained Language Models[C]. In Proceedings of the Annual Meeting of the Association for Computational Linguistics(ACL) Findings, 2024, pp3773-3786. (CCF A)

[26]Mingchen Sun, Yingji Li, Ying Wang(王英,通讯作者), Xin Wang. Towards Domain-Aware Stable Meta Learning for Out-of-Distribution Generalization[J]. ACM Transactions on Knowledge Discovery from Data, 2024, 18(8): 1-24. (CCF B, IF:4.0)

[27]Zihao Chen. Ying Wang(王英,通讯作者), Fuyuan Ma, Hao Yuan, Xin Wang. GPL-GNN: Graph Prompt Learning for Graph Neural Network[J]. Knowledge-Based Systems, 2024, 286(111391): 1-11.(中科院一区, IF:8.8)

[28]Ying Wang(王英), Yingji Li, Yue Wu, Xin Wang. Exploring Multiple Hypergraphs for Heterogeneous Graph Neural Networks[J]. Expert Systems With Applications, 2024, 236(121230): 1-10. (中科院一区, IF: 8.5)

[29]Rui Miao, Kaixiong Zhou, Yili Wang, Ninghao Liu, Ying Wang(王英), Xin Wang. Rethinking Independent Cross-Entropy Loss For Graph-Structured Data[C]. In Proceedings of International Conference on Machine Learning(ICML), 2024, pp1-20. (CCF-A)

[30]Yiwei Dai, Hengrui Gu, Ying Wang(王英), Xin Wang. Mitigate Extrinsic Social Bias in Pre-trained Language Models via Continuous Prompts Adjustment[C]. In Proceedings of the International Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024, pp11068-11083. (清华A)

[31]Yingji Li, Mengnan Du, Xin Wang, Ying Wang(王英,通讯作者). Prompt Tuning Pushes Farther, Contrastive Learning Pulls Closer: A Two-Stage Approach to Mitigate Social Biases[C]. In Proceedings of the Annual Meeting of the Association for Computational Linguistics(ACL), 2023, pp14254-14267. (CCF A)

[32]Xianglin Zuo, Wenqi Chen, Xianduo Song, Xin Wang, Ying Wang(王英,通讯作者). Generating Real-world Hypergraphs via Deep Generative Models[J]. Information Sciences, 2023, 647(119412): 1-15. (中科院一区,IF:8.1)

[33]Yingji Li, Yue Wu, Mingchen Sun, Bo Yang, Ying Wang(王英,通讯作者). Learning Continuous Dynamic Network Representation with Transformer-based Temporal Graph Neural Network[J]. Information Sciences, 2023, 649(119596): 1-15. (中科院一区, IF: 8.1)

[34]Mingchen Sun, Mengduo Yang, Yingji Li, Dongmei Mu, Xin Wang, Ying Wang(王英,通讯作者). Structural-aware Motif-based Prompt Tuning for Graph Clustering[J]. Information Sciences, 2023, 649(119643): 1-15. (中科院一区,IF:8.1)

[35]Xianglin Zuo, Hao Yuan, Bo Yang, Hongji Wang, Ying Wang(王英,通讯作者). Exploring Graph Capsual Network and Graphormer for Graph Classification[J]. Information Sciences, 2023, 640: 1-17. (中科院一区,IF:8.1)

[36]Wajid Ali, Wanli Zuo, Wang Ying(王英), Rahman Ali, Gohar Rahman, Inam Ullah. Causality Extraction: A Comprehensive Survey and New Perspective[J]. Journal of King Saud University-Computer and Information Sciences, 2023, 35: 1-25. (中科院一区, IF: 6.9)

[37]Mingchen Sun, Kaixiong Zhou, Xin He, Ying Wang(王英,通讯作者), Xin Wang. GPPT: Graph Pre-training and Prompt Tuning to Generalize Graph Neural Networks[C]. In Proceedings of the 28th Conference on Knowledge Discovery and Data Mining (KDD), 2022, pp1717-1727. (CCF A)

[38]Xianduo Song, Xin Wang, Yuyuan Song, Xianglin Zuo, Ying Wang(王英,通讯作者). Hierarchical Recurrent Neural Networks for Graph Generation[J]. Information Sciences, 2022, 589: 250-264. (中科院一区, IF:8.1)

[39]Rui Miao, Yintao Yang, Yao Ma, Xin Juan, Haotian Xue, Jiliang Tang, Ying Wang(王英), Xin Wang. Negative Samples Selecting Strategy for Graph Contrastive Learning[J]. Information Sciences, 2022, 613: 667-681. (中科院一区,IF:8.1)

[40]Xianglin Zuo, Tianhao Jia, Xin He, Bo Yang, Ying Wang(王英,通讯作者). Exploiting Dual-Attention Networks for Explainable Recommendation in Heterogeneous Information Networks[J]. Entropy, 2022, 24(1718): 1-19. (中科院三区,IF:2.305)

[41]Ying Wang(王英), Mingchen Sun, Hongji Wang, Yudong Sun. Research on Knowledge Graph Completion Model Combining Temporal Convolutional Network and Monte Carlo Tree Search[J]. Mathematical Problems in Engineering, 2022, 2022(2290540): 1-13. (中科院三区,IF:1.145)

[42]Ying Wang(王英) , Xin He, Hongji Wang, Yudong Sun, Xin Wang. Fast Explainable Recommendation Model by Combining Fine grained Sentiment in Review Data[J]. Computational Intelligence and Neuroscience, 2022, 1-18.(中科院三区, IF: 3.12

[43]沈鹏飞, 徐臻, 闫论, 王英(通讯作者). 基于嵌套生成对抗学习的网络嵌入[J]. 电子学报, 2022, 50(9): 2155-2163. (CCF中文A)

[44]Bo Wang, Tao Shen, Guodong Long, Tianyi Zhou, Ying Wang(王英,通讯作者). Structure-Augmented Text Representation Learning for Efficient Knowledge Graph Completion[C]. In Proceedings of the International World Wide Web Conference (WWW), 2021, pp1737-1748. (CCF A)

[45]Ying Wang(王英), Hongji Wang, Hui Jin, Xinrui Huang, Xin Wang. Exploring Graph Capsual Network for Graph Classification[J]. Information Sciences, 2021, 581: 932-950. (中科院一区,IF:8.1)

[46]Siyuan Guo, Ying Wang(王英), Hao Yuan, Zeyu Huang, Jianwei Chen, Xin Wang. TAERT: Triple-Attentional Explainable Recommendation with Temporal Convolutional Network[J]. Information Sciences, 2021, 567: 185-200. (中科院一区,IF:8.1)

[47]吴越, 王英(通讯作者), 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[J]. 计算机学报, 2021, 44(11): 2248-2260. (CCF中文A)

[48]Xin Wang, Ying Wang(王英,通讯作者), Yunzhi Ling. Attention Guide Walk Model in Heterogeneous Information Network for Multi-style Recommendation Explanation[C]. In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI), 2020, pp6275-6282. (CCF A )

[49]Yunzhi Ling, Ying Wang(王英, 通讯作者), Xin Wang, Yunhao Ling. Exploring Common and Label-Specific Features for Multi-Label Learning with Local Label Correlations[J]. IEEE Access, 2020, 8: 50969-50982. (中科院二区, IF: 3.9)

[50]Yu Li, Ying Wang(王英,通讯作者), Tingting Zhang, Jiawei Zhang, Yi Chang. Learning Network Embedding with Community Structural Information[C]. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2019, pp2937-2943.  (CCF A)

[51]Fuyuan Ma, Wenqi Chen, Minhao Xiao, Xin Wang, Ying Wang(王英, 通讯作者). Explanation Chains Model Based on the Fine-Grained Data[C]. NLPCC 2019. (CCF C)

[52]孙小婉, 王英(通讯作者), 王鑫, 孙玉东. 面向双注意力网络的特定方面情感分析模型[J]. 计算机研究与发展, 2019, pp2384-2395. (CCF中文A)

[53]Xin Wang, Ying Wang(王英, 通讯作者), Jianhua Guo. Building Trust Networks in the Absence of Trust Relations[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(10): 1591-1600. (中科院三区, IF: 0.622)

[54]Xin Wang, Ying Wang(王英, 通讯作者), Hongbin Sun. Exploring the Combination of Dempster-Shafer Theory and Neural Network for Predicting Trust and Distrust[J]. Computational Intelligence and Neuroscience, 2016, 5403105: 1-12. (中科院三区, IF:0.596)

[55] Mengmeng Wang, Wanli Zuo, Xin Wang, Ying Wang(王英, 通讯作者). An Improved Density Peaks-based Clustering Method for Social Circle Discovery in Social Networks[J]. Neurocomputing, 2016, 179: 219-227. (中科院二区, CCF C, IF: 2.083)

[56]王鑫, 王英(通讯作者), 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[J]. 计算机研究与发展, 2016(4): 764-775. (CCF中文A)

[57]王萌萌,左万利, 王英(通讯作者). 基于加权非负矩阵分解的链接预测算法[J]. 电子学报,2016. (CCF中文A)
[58]
萌萌,左万利, 王英(通讯作者). 一种基于加权非负矩阵分解的多维用户人格特质识别算法[J], 计算机学报, 2016. (CCF中文A)

[59]Ying Wang(王英), Xin Wang, Jiliang Tang, WanliZuo. Modeling Status Theory in Trust Prediction[C]. In Proceedings of the 29th AAAI Conference on Artificial Intelligence(AAAI), 2015, pp1875-1881. (CCF A)

[60]Xin Wang, Ying Wang(王英, 并列一作), Wanli Zuo. Exploring Social Context for Topic Identification in Short and Noisy Text[C]. In Proceedings of the 29th AAAI Conference on Artificial Intelligence(AAAI), 2015, pp1868-1874, 2015.1.25-1.29. (CCF A)

[61]Ying Wang(王英), Xin Wang, Wanli Zuo. Research on Trust Prediction from a Sociological Perspective[J]. Journal of Computer Science and Technology(JCST), 2015, 30(4): 843-858. (中科院三区,CCF B, IF: 0.672)

[62]Mengmeng Wang, Wanli Zuo, Ying Wang(王英, 通讯作者). A Multidimensional Nonnegative Matrix Factorization Model for Retweeting Behavior Prediction[J]. Mathematical Problems in Engineering, 2015, 936397: 1-10. (中科院四区, IF:1.082)

[63]Mengmeng Wang, Wanli Zuo, Ying Wang(王英, 通讯作者). A Novel Adaptive Conditional Probability-based Predicting Model for User’s Personality Traits[J]. Mathematical Problems in Engineering, 2015, 472917: 1-14. (中科院四区, IF: 1.082)

[64]Mengmeng Wang, Wanli Zuo, Ying Wang(王英, 通讯作者). A Multi-layer Naive Bayes Model for Analyzing User’s Retweeting Sentiment Tendency[J]. Computational Intelligence and Neuroscience, 2015, 510281: 1-11. (中科院四区, IF:0.596)

[65]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[J]. 软件学报, 2014, 25(12): 2893-2904.CCF 中文A类)

[66]赵秋月,左万利,田中生,王英(通讯作者). 一种基于改进D-S证据理论的信任关系强度评估方法研究[J]. 计算机学报, 2014.04, 37(4): 873-883. (CCF中文A)

[67]王英, 左祥麟, 左万利, 王鑫. 基于本体的Deep Web查询接口集成[J]. 计算机研究与发展, 2012.11, 49(11): 2383-2394. (CCF中文A)

[68]Ying Wang(王英), Huilai Li, Wanli Zuo, Fengling He, Xin Wang, Kerui Chen. Research on Discovering Deep Web Entries. Computer Science and Information Systems, 2011.06, 8(3): 779-799. (中科院三区, IF :0.642)



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教研论文:
[1]王英,王鑫,左万利. 操作系统课程改革的启发和思考,计算机教育,2017.

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专利:

1王英,杨兆琪,王鑫,杨博,朱曜迪,马涪元,张钧贺. 基于自适应数据增强和对抗性训练的谣言检测框架. 专利号: ZL 2023 1 0798909.5, 授权公告日: 2026.3.2.

2王英,张钧贺,王鑫,杨博,马涪元,朱曜迪,杨兆琪. 基于常微分方程和超网络的事件预测方法. 专利号: ZL 2023 1 0792186.8, 授权公告日: 2025.12.30.

3王英,李莹姬,吴越. 一种基于时序图Transformer的连续动态网络表征学习方法. 专利号: ZL 2021 1 1434187.2, 授权公告日: 2024.5.1 0.

4)王英, 杨孟铎, 周昊, 孙明辰, 赵文龙. 一种基于模体结构增强的图聚类方法. 专利号: ZL 202111434145.9, 授权公告日: 2024.7.17.

5王英, 孙小婉, 王鑫, 孙玉东, 于尤婧, 凌云志, 马涪元. 基于混合注意力网络的细粒度情感极性预测方法. 专利号: ZL 2019 1 0333298.0, 授权公告日: 2023.6.9.

  (6) 王英, 杨伟英, 王鑫, 左万利, 贾天浩, 郝琳琳. 基于超图卷积的超边链接预测方法. 专利号:ZL 2020 1 1276695.8,授权公告日:2022.7.1.

(7) 王英, 贾天浩, 王鑫, 左万利, 杨伟英, 左祥麟. 一种融合异质信息网络的可解释推荐方法. 专利号:ZL 2020 1 1276253.3, 授权公告日:2022.9.16.

8王英,孙玉东,王鑫,李畅,于尢婧,孙小婉,凌云志,马涪元. 面向细粒度情感的可解释推荐模型. 专利号:ZL 2019 1 0333302.3,授权公告日:2021.11.19.

9王英,马涪元,王鑫,孙玉东,陈文祺,肖旻昊. 基于细粒度数据的可解释商品推荐方法. 专利号:ZL 201910333300.4,授权公告日:2021.9.24.

10王英,左万利,王萌萌,王鑫, 彭涛. 基于最低阈值的用户个人品性多标记预测方法. 专利号:ZL 2014 1 0081840.5, 授权公告日: 2019.4.16.

11王英,左万利,田中生,王鑫,彭涛,王萌萌,赵秋月. 基于前馈神经网络的可信与不可信用户识别方法,专利号:ZL 2013 1 0547349.2,授权公告日:2016.10.5.

12)左祥麟,杨博, 范利云, 左万利, 王俊华, 王英, 王泊, 郑慧中. 基于证据理论的网络质量评价方法.专利号:ZL 2016 1 0280055.1, 授权公告日:2018.5.15.

13)尚靖博,左祥麟,左万利,王英. 利用模糊理论对欺诈网页识别的方法,专利号:ZL 201611046454.8,授权公告日: 2018.9.5.

14)左万利,赫枫龄,王俊华,王鑫,凤丽洲,王英,彭涛,万海旭,苏雪阳,高宁宁,闫昭,张雪松. 基于本体的情境搜索方法,专利号:ZL 2012 1 0575284.8,授权公告日:2016.1.6.


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软件著作权:

1)基于深度学习的细粒度医学知识图谱可视化软件V1.0, 2025

2)基于深度学习的细粒度医学知识图谱可视化软件V1.0, 2025

3)基于机器学习的数据诊断系统V1.0, 2021

4)大规模异质信息网络摘要可解释性研究平台V1.0, 2020

5)政府政务新媒体校内评估可视化显示平台V1.0, 2020

6深度网搜索软件V1.0, 2013

著作教材:


1.左万利, 王英. 计算机操作系统教程(第4版),高等教育出版社, 2019.

2.左万利, 王英, 彭涛. 操作系统习题与实验指导(第二版), 高等教育出版社, 2013.03.


获奖情况:

科研获奖:

[1] 王英,王鑫,左祥麟,李玉, 孙明辰. 复杂网络表征学习与泛化理论研究. 吉林省自然科学二等奖, 2025.

[2] 王英,王鑫,左祥麟,左万利,李丽娜,李莹姬,马涪元,王俊华,异质社会网络分析与应用研究,中国商业联合会科技进步三等奖,2021.

[3] 左万利,王英,彭涛,赫枫龄,社会化搜索技术与软件,中国商业联合会科技进步二等奖,2017.
[4]
左万利,王英,彭涛,赫枫龄,陈珂锐,王鑫,王萌萌,岳琳. 基于主题爬行和本体的Deep Web搜索, 吉林省人民政府, 吉林省科技进步奖, 三等奖, 2015.
[5]
左万利, 彭涛, 王英, 赫枫龄, 陈珂锐, 张邦佐, 罗娜, 王俊华, 王鑫, 凤丽洲, 岳琳, 深度网搜索技术的研究与应用, 中国商业联合会, 中国商业联合会科学技术三等奖, 省部级, 2013.
[6]
房至一, 曲冠南, 赵辉, 轩景泉, 张云春, 张剑飞, 王英, 戴志明, 王瑞娟. 基于Linux集群的汽车零部件产业协同服务平台的研究与应用, 中国商业联合会, 中国商业联合会科学技术奖全国商业科技进步三等奖, 2011.
[7]
房至一, 轩景泉, 赵辉, 张云春, 王英, 曲冠南, 张剑飞, 戴志明, 王瑞娟, 焦雪, 丛士佺, 张丹, 张美文. 汽车零部件协同设计与制造相关技术研究与应用,吉林省科学技术进步二等奖, 2009.


教学获奖:

[1] 左万利, 王英,闫昭,赵东范,张雪松,董立岩,刘兆军. 《操作系统》课程新形态改革与建设,吉林大学教学成果二等奖,2023.06.

[2] 左万利, 赵东范, 闫昭, 董立岩, 刘兆军, 彭涛, 王英. 《操作系统》课程持续性教学改革与建设, 吉林省教学成果三等奖, 2014.02.
[3]
左万利, 赵东范, 闫昭, 董立岩, 刘兆军, 彭涛, 王英. 《操作系统》课程持续性教学改革与建设, 吉林大学教学成果一等奖, 2013.07.


社会兼职:


中国计算机学会杰出会员

中文信息学会社会媒体处理专委会执行委员

中国计算机学会计算机应用专委会执行委员

中国计算机学会计算机教育专委会执行委员

中国计算机学会自然语言处理会专委会执行委员
中国计算机学会模式识别和人工智能专委会委员


治学格言: 一分耕耘,一分收获。

 

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