研究领域：

人工智能、社会计算、网络大数据分析挖掘

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。1993-1999年在中国科学院研究生院计算机学部任讲师，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。1999-2001年赴德国人工智能研究中心（DFKI）进行交流访学，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创新技术研究所任研究助理，发展了基于多智能体交互的社会模拟技术；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，获南加州大学杰出学术成就奖。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、中国科学院及部委合作项目。2015年起担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、ICONIP、IIP、IJCAI、IVA、PAAMS、PRIMA、SMP、WI-IAT 等

代表性论文：

1.      W. Mao, X. Qiu and A. Abbasi. LLMs and Their Applications in Medical Artificial Intelligence. ACM Transactions on Management Information Systems, accepted for publication.

2.      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.

3.      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.

4.      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.

5.      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.

6.      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.

7.      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.

8.      H. Yang, Q. Kong and W. Mao. A Deep Latent Space Model for Directed Graph Representation Learning. Neurocomputing, 576:127342, 2024.

9.      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.

10.   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.

11.   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.

12.   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.

13.   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.

14.   Y. Tian, N. Xu, R. Zhang and W. Mao. Dynamic Routing Transformer Network for Multimodal Sarcasm Detection. Proceedings of ACL, pp.2468-2480, 2023.

15.   J. Zhao and W. Mao. Generative Adversarial Training with Perturbed Token Detection for Model Robustness. Proceedings of EMNLP, pp.13012-13025, 2023.

16.   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.

17.   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.

18.   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.

19.   S. Wang, W. Mao, P. Wei, et al. Knowledge Structure Driven Prototype Learning and Verification for Fact Checking. Knowledge-Based Systems, 238:107910, 2022.

20.   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.

21.   X. Zhang, X. Zheng and W. Mao. Adversarial Perturbation Defense on Deep Neural Networks. ACM Computing Surveys (CSUR), 54(8):159, 2021.

22.   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.

23.   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.

24.   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.

25.   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.

26.   S. Wang and W. Mao. Modeling Inter-Cliam Interactions for Verifying Multiple Claims.  Proceedings of ACM CIKM, pp.3503-3507, 2021.

27.   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.

28.   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.

29.   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.

30.   Z. Zeng, N. Xu and W. Mao. Event-Driven Network for Cross-Modal Retrieval. Proceedings of ACM CIKM, pp.2297-2300, 2020.

31.   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.

32.   P. Wei, W. Mao and G. Chen. A Topic-Aware Reinforced Model for Weakly Supervised Stance Detection. Proceedings of AAAI, pp.7249-7256, 2019.

33.   N. Xu, W. Mao and G. Chen. Multi-Interactive Memory Network for Aspect Based Multimodal Sentiment Analysis. Proceedings of AAAI, pp.371-378, 2019.

34.   P. Wei and W. Mao. Modeling Transferable Topics for Cross-Target Stance Detection. Proceedings of SIGIR, pp.1173-1176, 2019.

35.   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.

36.   N. Xu, W. Mao and G. Chen. A Co-Memory Network for Multimodal Sentiment Analysis. Proceedings of SIGIR, pp.929-932, 2018.

37.   P. Wei, J. Lin and W. Mao. Multi-Target Stance Detection via a Dynamic Memory-Augmented Network. Proceedings of SIGIR, pp.1229-1232, 2018.

荣誉及奖励：

1.      中国自动化学会“科技进步一等奖”（排名第三）

2.      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）

3.      美国南加州大学“杰出学术成就奖"（2006）