基本信息

毛文吉  研究员、博士生导师  中国科学院自动化研究所
电子邮件: wenji.mao@ia.ac.cn
联系电话: 010-82544789
通信地址: 北京中关村东路95号
邮政编码: 100190

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

招生信息

1. [学科专业]:模式识别与智能系统,[研究方向]:人工智能理论与方法
2. [学科专业]:社会计算,[研究方向]:互联网大数据解析

教育背景

2001-09--2006-08   美国南加州大学计算机科学系   获博士学位
1990-09--1993-07   中国科学院数学研究所   获硕士学位
1986-09--1990-07   吉林大学计算机科学与技术系   获学士学位

工作经历

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因果推理计算模型。

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、中科院项目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。

社会任职:

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、Patterns、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、ACL、AMT、CCAI、CCDM、CCFBigdata、CCIS、EUROMEDIA、FOSINT-SI、GAMEON、GAMEON-NA、IEEE ISI、IJCAI、IVA、NCSC、PAAMS、PAISI、PRIMA、SID、SMP、WI等

专利与奖励

中国自动化学会“科学技术进步奖",一等奖(排名第三)

中国人工智能学会“吴文俊人工智能科学技术创新奖",二等奖(排名第一)

美国南加州大学“杰出学术成就奖",校级(2006)

出版信息

领域顶级会议论文:

[1] Z. Zeng, Y. Sun and W. Mao. Multimodal Coordinated Clustering Network for Large-Scale Cross-Modal Retrieval. Proceedings of the ACM Multimedia 2021 Conference (MM'21), accepted for publication.

[2] S. Wang and W. Mao. Modeling Inter-Cliam Interactions for Verifying Multiple Claims.  Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM'21), accepted for publication.

[3] Z. Zeng, S. Wang, N. Xu and W. Mao. PAN: Prototype-based Adaptive Network for Robust Cross-Modal Retrieval. The 44nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'21), pp.1125-1134. ACM Press, 2021.

[4] J. Zhao, P. Wei and W. Mao. Robust Neural Text Classification and Entailment via Mixup Regularized Adversarial Training. The 44nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'21), pp.1778-1782. ACM Press, 2021.

[5] 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.

[6] 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.

[7] 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), pp.2297-2300. ACM Press, 2020.

[8] 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.

[9] 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.

[10] 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.

[11] 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.

[12] 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.

[13] N. Xu, W. Mao and G. Chen. A Co-Memory Network for Multimodal Sentiment Analysis. Proceedings of the 41st International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'18), pp.929-932. ACM Press, 2018.

[14] 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.

[15] N. Xu and W. Mao. MultiSentiNet: A Deep Semantic Network for Multimodal Sentiment Analysis. Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM'17), pp.2399-2402. ACM Press, 2017.

[16] J. Lin, W. Mao and Y. Zhang. An Enhanced 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.

[17] 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.

[18] 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.

[19] 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.

[20] 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.

[21] B. Martinovski, W. Mao, J. Gratch, et al. Mitigation Theory: An Integrated Approach. Proceedings of the Twenty-Seventh Annual Conference of the Cognitive Science Society (CogSci'05), pp.1407-1412. Lawrence Erlbaum Associates, 2005.

[22] 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.

主要期刊论文及论著:

[23] X. Zhang, X. Zheng and W. Mao. Adversarial Perturbation Defense on Deep Neural Networks. ACM Computing Surveys, accepted as regular paper.

[24] 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.

[25] P. Wei, J. Zhao and W. Mao. A Graph-to-Sequence Learning Framework for Summarizing Opinionated Texts. IEEE/ACM Transactions on Audio, Speech and Language Processing, 29:1650-1660, 2021.

[26] 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.

[27] 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.

[28] G. Chen, Q. Kong, N. Xu and W. Mao. NPP: A Neural Popularity Prediction Model for Social Media Content. Neurocomputing, 333:221-230, 2019.

[29] J. Lin, W. Mao and D. Zeng. Personality-based Refinement for Sentiment Classification in Microblog. Knowledge-Based Systems, 132:204-214, 2017.

[30] L. Zhou, L. Kaati, W. Mao, et al (Eds.). Intelligence and Security Informatics. IEEE Press, 2015.

[31] D. Zeng and W. Mao. Supporting Global Collective Intelligence via Artificial Intelligence. IEEE Intelligent Systems, 29(2):2-4, 2014.

[32] 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.

[33] C. Yang, W. Mao, X. Zheng, et al (Eds.). Intelligent Systems for Security Informatics. Elsevier, February, 2013.

[34] P. Su, W. Mao, D. Zeng, et al. Mining Actionable Behavioral Rules. Decision Support Systems, 54(1):142-152, 2012.

[35] W. Mao, J. Gratch and X. Li. Probabilistic Plan Inference for Group Behavior Prediction. IEEE Intelligent Systems, 27(4):27-36, 2012.

[36] W. Mao and J. Gratch. Modeling Social Causality and Responsibility Judgment in Multi-Agent Interactions. Journal of Artificial Intelligence Research, 44:223-273, 2012.

[37] W. Mao and F. Wang. Advances in Intelligence and Security Informatics. Academic Press, 2012.

[38] 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.

[39] 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.

[40] X. Li, W. Mao and D. Zeng. Forecasting Complex Group Behavior via Multiple Plan Recognition. Frontiers of Computer Science, 6(1):102-110, 2012.

[41] W. Mao, A. Ge and X. Li. From Causal Scenario to Social Causality: An Attributional Approach. IEEE Intelligent Systems, 26(6):48-57, 2011.

[42] W. Mao, A. Tuzhilin and J. Gratch. Social and Economic Computing. IEEE Intelligent Systems, 26(6):19-21, 2011.

[43] Q. Yang, Z. Zhou, W. Mao, et al. Social Learning. IEEE Intelligent Systems, 25(4):9-11, 2010.

[44] W. Mao and J. Gratch. Modeling Social Inference in Agent Society. AI & Society, 24(1):5-11, 2009.

[45] 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.

[46] X. Li, W. Mao, D. Zeng, et al. Performance Evaluation of Machine Learning Methods in Cultural Modeling. Journal of Computer Science and Technology, 24(6):1010-1017, 2009.

[47] F. Wang, N. Sun, W. Mao, et al. Special Section on International Partnership Program. Journal of Computer Science and Technology, 24(6):997-999, 2009.

[48] F. Wang, D. Zeng, K. Carley and W. Mao. Social Computing: From Social Informatics to Social Intelligence. IEEE Intelligent Systems, 22(2):79-83, 2007.

[49] 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, 2006.

[50] R. Lu, C. Cao, Y. Chen, W. Mao, et al. A PNLU Approach to Automatic Generation of ICAI Systems. Science in China (Series A), 38(suppl.):1-11, 1995.

[51] 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.

[52] 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.

[53] 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.

[54] 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.

[55] 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.

[56] 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.

[57] 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.

[58] 毛文吉, 陆汝钤.基于SELD描述语言的英文文本知识自动获取. 计算机学报, 21(suppl.):105-111, 1998.

教学情况

2020-2021学年,中国科学院大学人工智能学院,研究生课程“多智能体系统”(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“社会智能”(首席教授)

2018-2019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)

2020-2021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)

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)

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)

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)

指导学生

博士研究生:

李晓晨(07硕博-12,合作导师;百度/阿里)

葛安生(08硕博-13,合作导师;百度/腾讯)

苏鹏(08普博-11,合作导师;齐鲁学院,教授)

孔庆超(11硕博-16,中科院自动化所,副研)

张育浩(12硕博-17,京东科学家/阿里巴巴)

林俊杰(13硕博-18,腾讯/字节跳动)

陈观淡(14硕博-19,阿里达摩院)

徐楠(15直博-20,中科院自动化所,特别研助)

韦鹏辉(16硕博-21,阿里妈妈)

王帅(17直博,在读)

曾志雄(18硕博,在读)

肖星琳(18普博,在读)

赵嘉豪(19直博,在读)

张兴伟(19普博,在读)

张睿珂(20直博,在读)

杨瀚轩(20普博,在读)

田元(21直博,在读)

陈诺(21直博,在读)

硕士研究生:

王永庆(08硕-11,中科院计算所,副研)

李悦群(09硕-12,百度/阿里巴巴)

皇甫璐雯(10硕-13,San Diego State Univ., Asst. Prof.)

崔宸熙(14硕-17,FreeWheel)

孔祥飞(15硕-18,滴滴出行/美团)

孙颖(19硕,在读)

汤伟(20硕,在读)

邹瀚仪(21硕,在读)