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]：社会计算与大数据解析

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，获得国家科技进步二等奖。1993-1999年，在中国科学院研究生院（国科大前身）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课程。1999-2001年，赴德国人工智能研究中心（DFKI）进行合作研究，2001年任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，在美国南加州大学创新技术研究所（USC/ICT）任研究助理，是两项重大研究计划中社会模拟技术的第一研制人，博士工作提出首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；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及重点项目课题、国家重点研发计划课题、中国科学院及国家部委合作项目，致力于人工智能理论方法与技术研究及其在复杂社会计算系统和网络大数据环境下的应用。2015年起担任互联网大数据与安全信息学研究中心副主任、中国科学院大学岗位教授等职。

社会任职：

担任《ACM Computing Surveys》、《IEEE Intelligent Systems》等国际期刊编委，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余次及本领域主要国际会议的PC/SPC、领域或Session主席。先后担任ACM北京分会主席、中国人工智能学会理事、中国计算机学会大数据专家委执行委员、中国指控学会大数据科学与工程专委会常务委员、IEEE SMC学会Homeland Security专委会委员等职。

担任学术会议PC/SPC/AC：AAAI、AAMAS、ACL、AILA、AMT、CCDM、CCF AI/Bigdata、CCIS、CogSci、ECAI、EMNLP、EUROMEDIA、GAMEON、IEEE ICBK、IEEE ISI、IEEE/WIC/ACM IAT、ICONIP、IIP、IJCAI、IVA、PAAMS、PAISI、PRIMA、SMP、WI 等

专利与奖励

美国南加州大学“杰出学术成就奖"（2006）

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）

IEEE 国际情报安全信息学年会“最佳论文奖”（2021）

IEEE 大数据分析国际会议“最佳学生论文奖”（2022）

中国科学院大学（院级）“优秀研究生课程”（2023）

出版信息

近期主要论文：

  • Wenji Mao, Xipeng Qiu and Ahmed Abbasi. LLMs and Their Applications in Medical Artificial Intelligence. ACM Transactions on Management Information Systems, accepted for publication.
  • Z. Zeng, S. He, Y. Zhang and W. Mao. A Multimodal Embedding Transfer Approach for Consistent and Selective Learning Processes in Cross-Modal Retrieval. Information Sciences, 704:121974, 2025.
  • Z. Yu, X. Xiao and W. Mao. One Unified Model for Diverse Tasks: Emotion Cause Analysis via Self-Promote Cognitive Structure Modeling. Proceedings of NAACL 2025.
  • Y. Tian, M. Wang, N. Xu and W. Mao. ImaRA: An Imaginative Frame Augmented Method for Low-Resource Multimodal Metaphor Detection and Explanation. Findings of NAACL 2025.
  • S. Wang, P. Wei, Q. Kong and W. Mao. A Knowledge Enhanced Learning and Semantic Composition Model for Multi-Claim Fact Checking. Knowledge-Based Systems, 304:112439, 2024.
  • H. Yang, Q. Kong, R. Zhang and W. Mao. Efficient Spiking Variational Graph Autoencoders for Unsupervised Graph Representation Learning Tasks. IEEE Intelligent Systems, 39(5):37-46, 2024.
  • N. Chen, L. Li and W. Mao. Equilibrium Strategy of Pursuit-Evasion Game in Three-Dimensional Space. IEEE/CAA Journal of Automatica Sinica (JAS), 11(2):446-458, 2024.
  • J. Zhao, W. Mao and D. Zeng. Disentangled Text Representation Learning with Information-Theoretic Perspective for Adversarial Robustness. IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP), 32:1237-1247, 2024.
  • H. Yang, Q. Kong and W. Mao. A Deep Latent Space Model for Directed Graph Representation Learning. Neurocomputing, 576:127342, 2024.
  • Y. Tian, R. Zhang, N. Xu and W. Mao. Bridging Word-Pair and Token-Level Metaphor Detection with Explainable Domain Mining. Proceedings of ACL, pp.13311-13325, 2024.
  • J. Zhao, M. Wang, N. Xu, Y. Luo and W. Mao. Enhancing Adversarial Robustness of LLMs with Analytic Hierarchy Process. Proceedings of COLM, pp.1-6, 2024.
  • M. Wang, N. Xu, J. Zhao, Y. Luo and W. Mao. PromISe: Releasing the Capabilities of LLMs with Prompt Introspective Search. Proceedings of COLING, pp.13120-13130, 2024.
  • Y. Tian, N. Xu and W. Mao. A Theory Guided Scaffolding Instruction Framework for LLM-Enabled Metaphor Reasoning. Proceedings of NAACL, pp.7738-7755, 2024.
  • R. Zhang, Y. Tian, P. Wei, D. Zeng and W. Mao. An LLM-Enabled Knowledge Elicitation and Retrieval Framework for Zero-Shot Cross-Lingual Stance Identification. Findings of EMNLP, pp.12253-12266, 2024.
  • Y. Cao, J. Zhao, R. Zhang, H. Zou and W. Mao. TARA: Token-Level Attribute Relation Adaptation for Multi-Attribute Controllable Text Generation. Findings of EMNLP, pp.12570-12579, 2024.
  • H. Zou, H. Xu, Q. Kong, Y. Cao and W. Mao. Generating Relevant Article Comments via Variational Multi-Layer Fusion. Proceedings of IJCNN, pp.1-8, 2024.
  • N. Xu, J. Wang, Y. Tian, R. Zhang and W. Mao. AnANet: Association and Alignment Network for Modeling Implicit Relevance in Cross-model Correlation Classification. IEEE Transactions on Multimedia (TMM), 25:7867-7880, 2023.
  • X. Zhang, X. Zheng, W. Mao, et al. Hashing Fake: Producing Adversarial Perturbation for Online Privacy Protection against Automatic Retrieval Models. IEEE Transactions on Computational Social Systems (TCSS), 10(6):3241-3251, 2023.
  • X. Xiao, W. Mao, Y. Sun, et al. A Cognitive Model Enhanced Sequential Method for Social Emotion Cause Identification. Information Processing & Management (IP&M), 60(3):103305, 2023.
  • X. Zhang, X. Zheng, B. Liu, X. Wang, W. Mao, et al. Towards Human-Machine Recognition Alignment: An Adversarially Robust Multimodal Retrieval Hashing Framework. IEEE Transactions on Computational Social Systems (TCSS), 10(5):2847-2859, 2023.
  • Y. Tian, N. Xu, R. Zhang and W. Mao. Dynamic Routing Transformer Network for Multimodal Sarcasm Detection. Proceedings of ACL, pp.2468-2480, 2023.
  • R. Zhang, N. Xu, H. Yang, Y. Tian and W. Mao. Target-Oriented Relation Alignment for Cross-Lingual Stance Detection. Findings of ACL, pp.6391-6404, 2023.
  • J. Zhao and W. Mao. Generative Adversarial Training with Perturbed Token Detection for Model Robustness. Proceedings of EMNLP, pp.13012-13025, 2023.
  • Y. Tian, N. Xu, W. Mao, et al. Modeling Conceptual Attribute Likeness and Domain Inconsistency for Metaphor Detection. Proceedings of EMNLP, pp.7736-7752, 2023.
  • R. Zhang, H. Yang and W. Mao. Cross-Lingual Cross-Target Stance Detection with Dual Knowledge Distillation Framework. Proceedings of EMNLP, pp.10804-10819, 2023.
  • X. Xiao, Y. Tian, Y. Luo and W. Mao. A Cognitive Knowledge Enriched Joint Framework for Social Emotion and Cause Mining. Proceedings of KSEM, pp.396-405, 2023.
  • S. Wang, W. Mao, P. Wei, et al. Knowledge Structure Driven Prototype Learning and Verification for Fact Checking. Knowledge-Based Systems, 238:107910, 2022.
  • Z. Zeng, N. Xu, W. Mao, et al. An Orthogonal Subspace Decomposition Method for Cross-Modal Retrieval. IEEE Intelligent Systems, 37(3):45-53, 2022.
  • Y. Sun, Q. Kong, W. Mao, et al. Multi-level News Recommendation via Modeling Candidate Interactions. Proceedings of IEEE ICBDA, pp.290-295, 2022.
  • X. Zhang, X. Zheng and W. Mao. Adversarial Perturbation Defense on Deep Neural Networks. ACM Computing Surveys (CSUR), 54(8):159, 2021.
  • 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 (TASLP), 29:1650-1660, 2021.
  • N. Xu, W. Mao, P. Wei, et al. MDA: Multimodal Data Augmentation Framework for Boosting Performance on Sentiment/Emotion Classification Tasks. IEEE Intelligent Systems, 36(6):3-12, 2021.
  • Z. Zeng, Y. Sun and W. Mao. Multimodal Coordinated Clustering Network for Large-Scale Cross-Modal Retrieval. Proceedings of ACM MM, pp.5427-5435, 2021.
  • J. Zhao, P. Wei and W. Mao. Robust Neural Text Classification and Entailment via Mixup Regularized Adversarial Training. Proceedings of SIGIR, pp.1778-1782, 2021.
  • Z. Zeng, S. Wang, N. Xu and W. Mao. PAN: Prototype-based Adaptive Network for Robust Cross-Modal Retrieval. Proceedings of SIGIR, pp.1125-1134, 2021.
  • S. Wang and W. Mao. Modeling Inter-Cliam Interactions for Verifying Multiple Claims.  Proceedings of ACM CIKM, pp.3503-3507, 2021.
  • 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 (TSMC), 50(10):3817-3827, 2020.
  • P. Wei, J. Zhao and W. Mao. Effective Inter-Clause Modeling for End-to-End Emotion-Cause Pair Extraction. Proceedings of ACL, pp.3171-3181, 2020.
  • N. Xu, Z. Zeng and W. Mao. Reasoning with Multimodal Sarcastic Tweets via Modeling Cross-Modality Contrast and Semantic Association. Proceedings of ACL, pp.3777-3786, 2020.
  • Z. Zeng, N. Xu and W. Mao. Event-Driven Network for Cross-Modal Retrieval. Proceedings of ACM CIKM, pp.2297-2300, 2020.
  • X. Xiao, L. Wang, Q. Kong and W. Mao. Social Emotion Cause Extraction from Online Texts. Proceedings of IEEE ISI, pp.1-6, 2020.
  • 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.
  • G. Chen, Q. Kong, N. Xu and W. Mao. NPP: A Neural Popularity Prediction Model for Social Media Content. Neurocomputing, 333:221-230, 2019.
  • P. Wei, W. Mao and G. Chen. A Topic-Aware Reinforced Model for Weakly Supervised Stance Detection. Proceedings of AAAI, pp.7249-7256, 2019.
  • N. Xu, W. Mao and G. Chen. Multi-Interactive Memory Network for Aspect Based Multimodal Sentiment Analysis. Proceedings of AAAI, pp.371-378, 2019.
  • P. Wei and W. Mao. Modeling Transferable Topics for Cross-Target Stance Detection. Proceedings of SIGIR, pp.1173-1176, 2019.
  • P. Wei, N. Xu and W. Mao. Modeling Conversation Structure and Temporal Dynamics for Jointly Predicting Rumor Stance and Veracity. Proceedings of EMNLP, pp.4789-4800, 2019.
  • N. Xu, W. Mao and G. Chen. A Co-Memory Network for Multimodal Sentiment Analysis. Proceedings of SIGIR, pp.929-932, 2018.
  • P. Wei, J. Lin and W. Mao. Multi-Target Stance Detection via a Dynamic Memory-Augmented Network. Proceedings of SIGIR, pp.1229-1232, 2018.
  • G. Chen, N. Xu and W. Mao. An Encoder-Memory-Decoder Framework for Sub-Event Detection in Social Media. Proceedings of ACM CIKM, pp.1575-1578, 2018.
  • J. Lin, W. Mao and D. Zeng. Personality-based Refinement for Sentiment Classification in Microblog. Knowledge-Based Systems, 132:204-214, 2017.
  • N. Xu and W. Mao. MultiSentiNet: A Deep Semantic Network for Multimodal Sentiment Analysis. Proceedings of ACM CIKM, pp.2399-2402, 2017.
  • J. Lin, W. Mao and Y. Zhang. An Enhanced Topic Modeling Approach to Multiple Stance Identification. Proceedings of ACM CIKM, pp.2167-2170, 2017.

其它主要论文：

  • N. Xu, G. Chen and W. Mao. MNRD: A Merged Neural Model for Rumor Detection in Social Media. Proceedings of IJCNN, pp.885-891, 2018.
  • P. Wei, W. Mao and D. Zeng. A Target-Guided Neural Memory Model for Stance Detection in Twitter. Proceedings of IJCNN, pp. 2068-2075, 2018.
  • 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.
  • Y. Zhang, W. Mao and J. Lin. Dynamic Topic Modeling in Short Texts. Proceedings of IEEE ICBK, pp.315-319, 2017.
  • C. Cui, W. Mao, X. Zheng, et al. Mining User Intents in Online Interactions: Applying to Discussions about Medical Event on Sina Weibo. Proceedings of ICSH, pp.177-183, 2017.
  • Y. Zhang, W. Mao and D. Zeng. A Non-Parametric Topic Model for Short Texts Incorporating Word Coherence Knowledge. Proceedings of ACM CIKM, pp.2017-2020, 2016.
  • Q. Kong, W. Mao and C. Liu. Popularity Prediction Based on Interactions of Online Contents. Proceedings of IEEE CCIS, pp.1-5, 2016.
  • L. Zhou, L. Kaati, W. Mao, et al (Eds.). Intelligence and Security Informatics. IEEE Press, 2015.
  • D. Zeng and W. Mao. Supporting Global Collective Intelligence via Artificial Intelligence. IEEE Intelligent Systems, 29(2):2-4, 2014.
  • 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, 第24-37页. 科学出版社, 2014.
  • 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.
  • C. Yang, W. Mao, X. Zheng, et al (Eds.). Intelligent Systems for Security Informatics. Elsevier, 2013.
  • P. Su, W. Mao and D. Zeng. An Empirical Study of Cost-Sensitive Learning in Cultural Modeling. Information Systems and e-Business Management (ISeB), 11(3):437-455, 2013.
  • W. Mao and J. Gratch. Modeling Social Causality and Responsibility Judgment in Multi-Agent Interactions: Extended Abstract. Proceedings of IJCAI, pp.3166-3170, 2013.
  • L. Huangfu, W. Mao, D. Zeng, et al. OCC Model-Based Emotion Extraction from Online Reviews. Proceedings of IEEE ISI, pp.116-121, 2013.
  • W. Mao and F. Wang. Advances in Intelligence and Security Informatics. Academic Press, 2012.
  • W. Mao and J. Gratch. Modeling Social Causality and Responsibility Judgment in Multi-Agent Interactions. Journal of Artificial Intelligence Research (JAIR), 44:223-273, 2012.
  • W. Mao, J. Gratch and X. Li. Probabilistic Plan Inference for Group Behavior Prediction. IEEE Intelligent Systems, 27(4):27-36, 2012.
  • P. Su, W. Mao, D. Zeng, et al. Mining Actionable Behavioral Rules. Decision Support Systems, 54(1):142-152, 2012.
  • X. Li, W. Mao and D. Zeng. Forecasting Complex Group Behavior via Multiple Plan Recognition. Frontiers of Computer Science, 6(1):102-110, 2012.
  • 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.
  • 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.
  • W. Mao, A. Ge and X. Li. From Causal Scenario to Social Causality: An Attributional Approach. IEEE Intelligent Systems, 26(6):48-57, 2011.
  • Z. Liu, D. Yang, D. Wen, W. Zhang and W. Mao. Cyber-Physical-Social Systems for Command and Control. IEEE Intelligent Systems, 26(4):92-96, 2011.
  • W. Mao, A. Tuzhilin and J. Gratch. Social and Economic Computing. IEEE Intelligent Systems, 26(6):19-21, 2011.
  • X. Li, W. Mao, D. Zeng, et al. Automatic Construction of Domain Theory for Attack Planning. Proceedings of IEEE ISI, pp.65-70, 2010.
  • Q. Yang, Z. Zhou, W. Mao, et al. Social Learning. IEEE Intelligent Systems, 25(4):9-11, 2010.
  • B. Martinovski and W. Mao. Emotion as an Argumentation Engine: Modeling the Role of Emotion in Negotiation. Group Decision and Negotiation (GDN), 18(3):235-259, 2009.
  • W. Mao and J. Gratch. Modeling Social Inference in Agent Society. AI & Society, 24(1):5-11, 2009.
  • X. Li, W. Mao, D. Zeng, et al. Performance Evaluation of Machine Learning methods in Culture Modeling. Journal of Computer Science and Technology, 24(6):1010-1017, 2009.
  • 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.
  • X. Li, W. Mao, D. Zeng, et al. Agent-Based Social Simulation and Modeling in Social Computing. Proceedings of SOCO, pp.401-412, 2008.
  • 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.
  • 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.
  • 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.
  • W. Mao and J. Gratch. Modeling Social Inference in Virtual Agents. Proceedings of SID, pp.81-94, 2007.
  • 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.
  • W. Mao and J. Gratch. Evaluating a Computational Model of Social Causality and Responsibility. Proceedings of AAMAS, pp.985-992, 2006.
  • J. Gratch, S. Marsella and W. Mao. Towards a Validated Model of Emotional Intelligence. Proceedings of AAAI, pp.1613-1616, 2006.
  • B. Martinovski, W. Mao, J. Gratch and S. Marsella. Mitigation Theory: An Integrated Approach. Proceedings of CogSci, pp.1407-1412, 2005.
  • W. Mao and J. Gratch. Social Causality and Responsibility: Modeling and Evaluation. Proceedings of IVA, pp.191-204, 2005.
  • W. Mao and J. Gratch. Social Judgment in Multiagent Interactions. Proceedings of AAMAS, pp.210-217, 2004.
  • W. Mao and J. Gratch. A Utility-Based Approach to Intention Recognition. AAMAS Workshop on Agent Tracking: Modeling Other Agents from Observation (MOO), 2004.
  • W. Mao and J. Gratch. The Social Credit Assignment Problem. Proceedings of IVA, pp.39-47, 2003.
  • R. Lu and W. Mao. Automatic Generation of ITS from English Text. Proceedings of ICCE, pp.319-324, 1998.
  • 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.
  • 毛文吉, 熊竟, 董占球. 存储与处理合一的智能系统. 计算机研究与发展, 34(2):118-123, 1997.
  • 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.

教学情况

2020-2025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）

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）

2023-2024学年，中国科学院大学人工智能学院，本科生课程“多智能体系统”（主讲教师）

2019-2022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学院，研究生课程“人工智能理论与实践”（主讲教师之一）

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）

孔庆超（11硕博-16，中科院自动化所）

张育浩（12硕博-17，京东/阿里/腾讯）

林俊杰（13硕博-18，腾讯/字节跳动）

陈观淡（14硕博-19，阿里/字节跳动）

徐楠（15直博-20，中科院特别研助/中科闻歌）

韦鹏辉（16硕博-21，阿里妈妈/百度）

王帅（17直博-22，百度/Chalmers Tech Univ）

肖星琳（18普博-23，中科闻歌）

曾志雄（18硕博-23，腾讯/美团）

张兴伟（19普博-22，中科院自动化所）

赵嘉豪（19直博-24，中科闻歌）

杨瀚轩（20普博-24，国家电网）

张睿珂（20直博，在读）

田元（21直博，在读）

陈诺（21直博，在读）

曹艺琳（22直博，在读）

刘雪龙（22直博，在读）

何淑怡（23普博，在读）

王民政（23直博，在读）

余昭昕（24直博，在读）

陈坤（24直博，在读）

硕士研究生：

王永庆（08硕-11，中国科学院计算所）

李悦群（09硕-12，百度/阿里）

皇甫璐雯（10硕-13，San Diego State Univ）

崔宸熙（14硕-17，FreeWheel）

孔祥飞（15硕-18，滴滴出行/美团）

孙颖（19硕-22，工行研发中心）

汤伟（20硕-23，国家某部）

邹瀚仪（21硕-24，新浪微博）