毛文吉 - 中国科学院大学

个人简介

工作简历 1990-1993年，在陆汝钤院士的指导下，就读于中国科学院数学研究所。参与了国家重点攻关项目（天马）专家系统开发环境的研制。该项目获国家科技进步二等奖和中国科学院科技进步一等奖。 1993-1999年，在中国科学院研究生院计算机学部任职，1996年起任讲师。主持系统开发实验室工作并主讲人工智能相关课程，期间参与了多项国家课题的研究与开发。 1999-2001年，赴德国人工智能研究中心（DFKI）进行合作研究，2001年被聘为DFKI研究科学家。为欧盟四国联合项目SAID和DFKI研究项目Presence的主要研制人员。 2001-2006年，在美国南加州大学 Institute for Creative Technologies（USC/ICT）任研究助理，是美国军方两项重大研究计划MRE和SASO-ST中社会模拟技术的第一研制人。博士工作提出第一个基于认知科学和心理学的社会推理计算模型。 2006年9月加入中国科学院自动化研究所，任副研究员。2008年任硕士生导师，2012年至今任研究员、博士生导师。主持多项国家自然科学基金项目、中科院知识创新工程重大项目课题以及与国家核心部门的合作项目。 2014年至今担任互联网大数据与安全信息学研究中心副主任，2015年10月起被聘为中国科学院大学岗位教授。专利与奖励中国自动化学会“科技进步一等奖”（排名第三）中国人工智能学会“吴文俊人工智能科技创新二等奖”（排名第一）美国南加州大学“Outstanding Academic Achievement Award”（2006）教学情况 1994-1999学年，中国科学院研究生院计算机学部，研究生课程“人工智能原理”（主讲教师） 2016-2017学年，中国科学院大学计算机与控制学院，研究生课程“人工智能理论与实践”（主讲教师之一） 2018-2020学年，中国科学院大学人工智能学院，研究生课程“社会智能”（首席教授） 2019-2020学年，中国科学院大学人工智能学院，研究生课程“文献阅读”（主讲教师）

研究领域

人工智能，网络大数据分析挖掘，社会计算，情报安全信息学

近期论文

查看导师新发文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

[1] Z. Zeng, N. Xu and W. Mao. Event-Driven Network for Cross-Modal Retrieval. Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM'20), accepted for publication. [2] P. Wei, J. Zhao and W. Mao.Effective Inter-Clause Modeling for End-to-End Emotion-Cause Pair Extraction. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL'20), pp.3171-3181. ACL Press, 2020. [3] N. Xu, Z. Zeng and W. Mao. Reasoning with Multimodal Sarcastic Tweets via Modeling Cross-Modality Contrast and Semantic Association. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL'20), pp.3777-3786. ACL Press, 2020. [4] P. Wei, N. Xu and W. Mao. Modeling Conversation Structure and Temporal Dynamics for Jointly Predicting Rumor Stance and Veracity. Proceedings of the 2019 International Conference on Empirical Methods in Natural Language Processing (EMNLP'19), pp.4789-4800. ACL Press, 2019. [5] N. Xu, W. Mao and G. Chen. Multi-Interactive Memory Network for Aspect Based Multimodal Sentiment Analysis. Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI'19), pp.371-378. AAAI Press, 2019. [6]P. Wei, W. Mao and G. Chen. A Topic-Aware Reinforced Model for Weakly Supervised Stance Detection. Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI'19), pp.7249-7256. AAAI Press, 2019. [7] P. Wei and W. Mao. Modeling Transferable Topics for Cross-Target Stance Detection. Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'19), pp.1173-1176. ACM Press, 2019. [8] N. Xu, W. Mao and G. Chen. A Co-Memory Network for Multimodal Sentiment Analysis. Proceedings of the 41st InternationalACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'18), pp.929-932. ACM Press, 2018. [9] P. Wei, J. Lin and W. Mao. Multi-Target Stance Detection via a Dynamic Memory-Augmented Network. Proceedings of the 41st International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'18), pp.1229-1232. ACM Press, 2018. [10] G. Chen,N. Xu and W. Mao. An Encoder-Memory-Decoder Framework for Sub-Event Detection in Social Media. Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM'18), pp.1575-1578. ACM Press, 2018. [11] J. Lin, W. Mao and Y. Zhang. AnEnhanced Topic Modeling Approach to Multiple Stance Identification. Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM'17), pp.2167-2170. ACM Press, 2017. [12]N. Xu and W. Mao. MultiSentiNet: A Deep Semantic Network for MultimodalSentiment Analysis. Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM'17), pp.2399-2402. ACM Press, 2017. [13] Y. Zhang, W. Mao and D. Zeng. A Non-Parametric Topic Model for Short Texts Incorporating Word Coherence Knowledge. Proceedings of the 25th ACM International Conference on Information and Knowledge Management (CIKM'16), pp. 2017-2020. ACM Press, 2016. [14] W. Mao and J. Gratch. Modeling Social Causality and Responsibility Judgment in Multi-Agent Interactions: Extended Abstract. Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence (IJCAI'13), pp.3166-3170, 2013. [15] J. Gratch, S. Marsella and W. Mao. Towards a Validated Model of Emotional Intelligence. Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI'06), pp.1613-1616. AAAI Press, 2006. [16] W. Mao and J. Gratch. Evaluating a Computational Model of Social Causality and Responsibility. Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS'06),pp.985-992. ACM Press, 2006. [17] B. Martinovski, W. Mao, J. Gratch, et al. Mitigation Theory: An Integrated Approach. Proceedings of the Twenty-Seventh AnnualConference of the Cognitive Science Society (CogSci'05), pp.1407-1412. Lawrence Erlbaum Associates, 2005. [18] W. Mao and J. Gratch. Social Judgment in Multiagent Interactions. Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS'04), pp.210-217. IEEE Press, 2004. [19] N. Xu, W. Mao, P. Wei, et al. MDA: Multimodal Data Augmentation Framework for Boosting Performance on Sentiment/Emotion Classification Tasks. IEEE Intelligent Systems, in press. [20] Q. Kong, W. Mao, G. Chen, et al. Exploring Trends and Patterns of Popularity Stage Evolution in Social Media. IEEE Transactions on Systems, Man and Cybernetics: Systems, 50(10):3817-3827, 2020. [21] J. Lin, Q. Kong, W. Mao, et al. A Topic Enhanced Approach to Detecting Multiple Standpoints in Web Texts. Information Sciences, 501:483-494, 2019. [22] G. Chen, Q. Kong, N. Xu and W. Mao. NPP: A Neural Popularity Prediction Model for Social Media Content. Neurocomputing, 333:221-230, 2019. [23] J. Lin, W. Mao and D. Zeng. Personality-based Refinement for Sentiment Classification in Microblog. Knowledge-Based Systems, 132:204-214, 2017. [24] L. Zhou, L. Kaati, W. Mao, et al (Eds.). Intelligence and Security Informatics. IEEE Press, 2015. [25] D. Zeng and W. Mao. Supporting Global Collective Intelligence via Artificial Intelligence. IEEE Intelligent Systems, 29(2):2-4, March/April, 2014. [26] P. Su, W. Mao and D. Zeng. An Empirical Study of Cost-Sensitive Learning in Cultural Modeling. Information Systems and e-Business Management, 11(3):437-455, 2013. [27] C. Yang, W. Mao, X. Zheng, et al (Eds.). Intelligent Systems for Security Informatics. Elsevier, February, 2013. [28] W. Mao and F. Wang. Advances in Intelligence and Security Informatics. Academic Press, April, 2012. [29] W. Mao and J. Gratch. Modeling Social Causality and Responsibility Judgment in Multi-Agent Interactions. Journal of Artificial Intelligence Research, 44:223-273, May, 2012. [30] W. Mao, J. Gratch and X. Li. Probabilistic Plan Inference for Group Behavior Prediction. IEEE Intelligent Systems, 27(4):27-36, July/August, 2012. [31] P. Su, W. Mao, D. Zeng, et al. Mining Actionable Behavioral Rules. Decision Support Systems, 54(1):142-152, December, 2012. [32] X. Li, W. Mao and D. Zeng. Forecasting Complex Group Behavior via Multiple Plan Recognition. Frontiers of Computer Science, 6(1):102-110, 2012. [33] Y. Wang, W. Mao, D. Zeng, et al. Listwise Approaches Based on Feature's Ranking Discovery. Frontiers of Computer Science, 6(6):647-659, 2012. [34] D. Zhang, W. Mao, J. Zhan, et al. Special Issue on Social Computing and E-business. Information Systems and E-Business Management, 10(2):161-163, 2012. [35] W. Mao, A. Ge and X. Li. From Causal Scenario to Social Causality: An Attributional Approach. IEEE Intelligent Systems, 26(6):48-57, November/December, 2011. [36] W. Mao, A. Tuzhilin and J. Gratch. Social and Economic Computing. IEEE Intelligent Systems, 26(6):19-21, November/December, 2011. [37] Q. Yang, Z. Zhou, W. Mao, et al. Social Learning. IEEE Intelligent Systems, 25(4):9-11, July/August, 2010. [38] W. Mao and J. Gratch. Modeling Social Inference in Agent Society. AI & Society, 24(1):5-11, 2009. [39] X. Li, W. Mao, D. Zeng, et al. Performance Evaluation ofMachine Learning Methods in Cultural Modeling. Journal of Computer Science and Technology, 24(6):1010-1017, November, 2009. [40] B. Martinovski and W. Mao. Emotion as an Argumentation Engine: Modeling the Role of Emotion in Negotiation. Group Decision and Negotiation, 18(3):235-259, 2009. [41] F. Wang, N. Sun, W. Mao, et al. Special Section on International Partnership Program. Journal of Computer Science and Technology, 24(6):997-999, November, 2009. [42] F. Wang, D. Zeng, K. Carley and W. Mao. Social Computing: From Social Informatics to Social Intelligence. IEEE Intelligent Systems, 22(2):79-83, March/April, 2007. [43] J. Gratch, W. Mao and S. Marsella. Modeling Social Emotions and Social Attributions. In: R. Sun (Ed.), Cognition and Multi-Agent Interaction: Extending Cognitive Modeling to Social Simulation, pp.219-251. Cambridge University Press, January, 2006. [44] R. Lu, C. Cao, Y. Chen, W. Mao, et al. A PNLU Approachto Automatic Generation of ICAI Systems. 中国科学 (A辑), 38(suppl.):1-11, 1995. [45] 林俊杰, 王磊, 毛文吉. 面向社会事件的半监督自训练多方立场分析. 模式识别与人工智能, 31(12):1074−1084, 2018. [46] 皇甫璐雯, 毛文吉. 一种基于OCC模型的文本情感挖掘方法. 智能系统学报, 12(5):645-652, 2017 [47] 孔庆超, 毛文吉. 基于动态演化的讨论帖流行度预测. 软件学报, 25(12):2767−2776, 2014. [48] 毛文吉, 曾大军. 基于认知和社会心理学的行为评估与情感建模. 社会物理学: 社会治理, pp.24-37. 科学出版社, 2014. [49] 王飞跃, 李晓晨, 毛文吉等. 社会计算的基本方法与应用. 浙江大学出版社, 2012. [50] 毛文吉, 曾大军, 王飞跃. 社会计算的研究现状与未来. 中国计算机学会通讯, 7(12):8-11, 2011. [51] 毛文吉. 多智能体交互环境下的社会推理计算模型. 模式识别与人工智能, 21(6):713-720, 2008. [52] 毛文吉. 基于MASIM的社会推理与计算系统. 系统科学与数学, 28(11):1432-1440, 2008. [53] X. Xiao, P. Wei, W. Mao, et al. Context-Aware Multi-View Attention Networks for Emotion Cause Extraction. Proceedings of the 2019 IEEE International Conference on Intelligence and Security Informatics (IEEE ISI'19), pp.128-133. IEEE Press, 2019. [54] N. Xu, G. Chen and W. Mao. MNRD: A Merged Neural Model for Rumor Detection in Social Media. Proceedings of the 2018 International Joint Conference on Neural Networks (IJCNN'18), pp.885-891, 2018. [55] P. Wei, W. Mao and D. Zeng. A Target-Guided Neural Memory Model forStance Detection in Twitter. Proceedings of the 2018 International Joint Conference on Neural Networks (IJCNN'18), pp.2068-2075, 2018. [56] G. Chen, Q. Kong, W. Mao, et al. A Partition and Interaction Combined Model for Social Event Popularity Prediction. Proceedings of the 2018 IEEE International Conference on Intelligence and Security Informatics (IEEE ISI'18), pp.214-219. IEEE Press, 2018. [57] G. Chen, W. Mao, Q. Kong, et al. Event Detection for Social Media by Joint Learning with Keyword Extraction. Proceedings of the 2018 IEEE International Conference on Intelligence and Security Informatics (IEEE ISI'18), pp.232-237. IEEE Press, 2018. [58] Y. Zhang, W. Mao and D. Zeng. Topic Evolution Modeling in Social Media Short Texts based on Recurrent Semantic Dependent CRP. Proceedings of the 2017 IEEE International Conference on Intelligence and Security Informatics (IEEE ISI'17), pp.119-124. IEEE Press, 2017. [59] J. Lin, W. Mao and D. Zeng. Topic and User based Refinement for Competitive Perspective Identification. Proceedings of the 2017 IEEE International Conference on Intelligence and Security Informatics (IEEE ISI'17). IEEE Press, 2017. [60] X. Kong and W. Mao. Ranking Events based on User Relevant Query. Proceedings of the 2017 IEEE International Conference on Intelligence and Security Informatics (IEEE ISI'17). IEEE Press, 2017. [61] G. Chen, Q. Kong and W. Mao. An Attention-based Neural Popularity Prediction Model for Social Media Events. Proceedings of the 2017 IEEE International Conference on Intelligence and Security Informatics (IEEE ISI'17). IEEE Press, 2017. [62] G. Chen, Q. Kong and W. Mao. Online Event Detection and Tracking in Social Media based on Neural Similarity Metric Learning. Proceedings of the 2017 IEEE International Conference on Intelligence and Security Informatics (IEEE ISI'17). IEEE Press, 2017. [63] Y. Zhang, W. Mao and J. Lin. Dynamic Topic Modeling in Short Texts. Proceedings of the 8th IEEE International Conference on Big Knowledge (IEEE ICBK'17), pp.315-319. IEEE Press, 2017. [64] C. Cui, W. Mao, X. Zheng, et al. Mining User Intents in Online Interactions: Applying to Discussions about Medical Event on Sina Weibo Platform. Proceedings of the 2017 International Conference for Smart Health (ICSH'17), pp.177-183. Springer, 2017. [65] N. Xu and W. Mao. A Residual Merged Neutral Network for Multimodal Sentiment Analysis. Proceedings of the 2017 IEEE International Conference on Big Data Analysis (IEEE ICBDA'17). IEEE Press, 2017. [66] J. Lin, W. Mao and D. Zeng. Competitive Perspective Identification via Topic based Refinement for Online Documents. Proceedings of the 2016 IEEE International Conference on Intelligence and Security Informatics (IEEE ISI'16). IEEE Press, 2016. [67] Q. Kong, W. Mao and C. Liu. Popularity Prediction Based on Interactions of Online Contents. Proceedings of the 4th IEEE International Conference on Cloud Computing and Intelligence Systems (IEEE CCIS'16), pp.1-5. IEEE Press, 2016. [68] J. Lin and W. Mao. Personality based Public Sentiment Classification in Microblog. Proceedings of the 2015 IEEE International Conference on Intelligence and Security Informatics (IEEE ISI'15). IEEE Press, 2015. [69] Y. Zhang, X. Li and W. Mao. A Bottom-up Method for Constructing Topic Hierarchies from Political Media Data. Proceedings of the 2015 IEEE International Conference on Intelligence and Security Informatics (IEEE ISI'15). IEEE Press, 2015. [70] Y. Zhang, W. Mao and D. Zeng. Constructing Topic Hierarchies from Social Media Data. Proceedings of the ICDM Workshops 2015 (ISI-ICDM'15), pp. 1015-1018. IEEE Press, 2015. [71] Q. Kong, W. Mao, D. Zeng, et al. Predicting Popularity of Forum Threads for Public Events Security. Proceedings of the 2014 IEEE Joint Intelligence and Security Informatics Conference (JISIC'14), pp.99-106. IEEE Press, 2014. [72] Y. Zhang, W. Mao, D. Zeng, et al. Exploring Opinion Dynamics in Security-Related Microblog Data. Proceedings of the 2014 IEEE Joint Intelligence and Security Informatics Conference (JISIC'14), pp.284-287. IEEE Press, 2014. [73] L. Huangfu, W. Mao, D. Zeng, et al. OCC Model-Based Emotion Extraction from Online Reviews. Proceedings of the 2013 IEEE International Conference on Intelligence and Security Informatics, pp.116-121. IEEE Press, 2013. [74] Q. Kong, W. Mao and D. Zeng. Predicting User Participation in Social Networking Sites. Proceedings of the 2013 IEEE International Conference on Intelligence and Security Informatics. IEEE Press, 2013. [75] A. Ge, W. Mao, D. Zeng, et al. Action Knowledge Extraction from Web Text. Proceedings of the 2013 IEEE International Conference on Intelligence and Security Informatics. IEEE Press, 2013. [76] Z. Tan, W. Mao, D. Zeng, et al. Acquiring Netizen Group's Opinions for Modeling Food Safety Events. Proceedings of the 2012 IEEE International Conference on Intelligence and Security Informatics, pp.114-119. IEEE Press, 2012. [77] A. Ge, W. Mao, D. Zeng, et al. Extracting Action Knowledge in Security Informatics. Proceedings of the 2012 IEEE International Conference on Intelligence and Security Informatics. IEEE Press, 2012. [78] Y. Li, W. Mao, D. Zeng, et al. Extracting Opinion Explanations from Chinese Online Reviews. Proceedings of the 2012 IEEE International Conference on Intelligence and Security Informatics. IEEE Press, 2012. [79] P. Su, W. Mao, D. Zeng, et al. Mining Actionable Behavioral Rules from Group Data. Proceedings of the 2011 IEEE International Conference on Intelligence and Security Informatics. IEEE Press, 2011. [80] X. Li, W. Mao, D. Zeng, et al. Forecasting Group Behavior via Multiple Plan Recognition. Proceedings of the 2011 IEEE International Conference on Intelligence and Security Informatics. IEEE Press, 2011. [81] Y. Wang, W. Mao, D. Zeng, et al. Boosting Rank with Predictable Training Error. Proceedings of the 2011 IEEE International Conference on Intelligence and Security Informatics. IEEE Press, 2011. [82] Z. Tan, X. Li and W. Mao. Agent-Based Modeling of Netizen Groups in Chinese Internet Events. Proceedings of the Pacific Asia Workshop on Intelligence and Security Informatics (PAISI'11), pp.43-53. Springer, 2011. [83] X. Li, W. Mao, D. Zeng, et al. Automatic Construction of Domain Theory for Attack Planning. Proceedings of the 2010 IEEE International Conference on Intelligence and Security Informatics (IEEE ISI'10), pp.65-70. IEEE Press, 2010. [84] P. Su, W. Mao, D. Zeng, et al. Employing Cost-Sensitive Learning in Cultural Modeling. Proceedings of the 2010 IEEE International Conference on Service Operations and Logistics and Informatics (IEEE SOLI'10). IEEE Press, 2010. [85] A. Ge, W. Mao and D. Zeng. Story Extraction from the Web: A Case Study in Security Informatics. Proceedings of the 2010 IEEE International Conference on Service Operations and Logistics and Informatics (IEEE SOLI'10). IEEE Press, 2010. [86] Y. Wang and W. Mao. FeatureRank: A Non-linear Listwise Approach with Clustering and Boosting. Proceedings of the Second IEEE Youth Conference on Information, Computing and Telecommunications (IEEE YC-ICT'10). IEEE Press, 2010. [87] P. Su, W. Mao, D. Zeng, et al. Handling Class ImbalanceProblem in Cultural Modeling, Proceedings of the 2009 IEEE International Conference on Intelligence and Security Informatics, pp.251-256. IEEE Press, 2009. [88] X. Li, W. Mao, D. Zeng, et al. Performance Evaluation of Classification Methods in Cultural Modeling, Proceedings of the 2009 IEEE International Conference on Intelligence and Security Informatics, pp.248-250. IEEE Press, 2009. [89] X. Li, W. Mao, D. Zeng, et al. Agent-Based Social Simulation and Modeling in Social Computing. Proceedings of the First InternationalWorkshop on Social Computing (SOCO'08), pp.401-412. Springer, 2008. [90] X. Li, D. Zeng, W. Mao, et al. Online Communities: A Social Computing Perspective. Proceedings of the First International Workshop on Social Computing (SOCO'08), pp.355-365. Springer, 2008 [91] W. Mao and J. Gratch. Modeling Social Inference in Virtual Agents. Proceedings of the Sixth International Workshop on Social Intelligence Design (SID'07), pp.81-94, 2007. [92] W. Mao, D. Zeng, L. Zhang, et al. Social Modeling and Reasoning for Security Informatics. Proceedings of the Pacific Asia Workshop on Intelligence and Security Informatics (PAISI'07). Springer, 2007. [93] W. Mao and J. Gratch. Social Causality and Responsibility: Modelingand Evaluation. Proceedings of the Fifth International Conference on Intelligent Virtual Agents (IVA'05), pp.191-204. Springer, 2005. [94] W. Mao and J. Gratch. A Utility-Based Approach to Intention Recognition. AAMAS 2004 Workshop on Agent Tracking: Modeling Other Agents from Observations (MOO'04), 2004. [95] W. Mao and J. Gratch. The Social Credit Assignment Problem. Proceedings of the Fourth International Conference on Intelligent Virtual Agents (IVA'03), pp.39-47. Springer, 2003.

学术兼职

担任《ACM Computing Surveys》、《IEEE Intelligent Systems》期刊编委，《软件学报》责任编委，多次应邀主编SCI/SSCI学术期刊专刊和组织本领域国际学术研讨会，任会议主席10余次及100多个国际会议的程序委员会委员或Session主席。曾任ACM北京分会主席、中国人工智能学会理事，现任中国计算机学会大数据专家委、服务计算专委会委员，IEEE SMC 学会Homeland Security专委会委员等职。担任国际期刊审稿人：ACM Computing Surveys、ACM Transactions on Intelligent Systems and Technology、Computational and Mathematical Organization Theory、IEEE Computational Intelligence、IEEE Intelligent Systems、IEEE Transactions on Big Data、IEEE Transactions on Knowledge and Data Engineering、IEEE Transactions on Neural Networks and Learning Systems、Journal of Autonomous Agents and Multi-Agent Systems、Social Network Analysis and Mining Journal等担任学术会议程序委员会委员（或Session主席）：AAAI、AAMAS、Agent、AMT、CCAI、CCDM、CCFBigdata、CCIS、EUROMEDIA、FOSINT-SI、GAMEON、GAMEON-NA、IEEE ISI、IJCAI、IVA、NCSC、PAAMS、PAISI、PRIMA、SID、SMP、WI等