郑海涛简介
清华大学副教授、博士生导师 计算机科学与技术 深圳市智能语义挖掘技术工程实验室副主任 深圳市智搜信息技术有限公司首席科学家 清华大学知识工程研究中心副主任 主要从事人工智能和互联网领域的研究 【个人简历】 1997年09月-2001年07月 中山大学计算机软件专业本科毕业 2001年09月-2004年12月 中山大学计算机软件与理论专业硕士毕业 2005年07月-2006年02月 华南农业大学计算科学与技术系教师 2006年03月-2009年08月 韩国首尔国立大学医疗信息学专业博士毕业 【教学】 《知识工程》 《面向对象技术与应用》 《人工智能程序设计》 《游戏引擎原理与实践》 【研究领域】 郑海涛近年来一直从事人工智能和互联网相关的研究,在知识工程的相关理论和关键技术上进行了深入的研究,很多研究成果在国际上处于领先地位。同时作为联合创始人创办了中国首家AIGC的智能写作公司——深圳市智搜信息技术有限公司,担任公司的首席科学家,获得了多轮融资,目前Giiso写作机器人服务了超过千万级的用户,2019年位列中国人工智能写作平台的第一名,获得了教育部推荐的世界互联网大会先进成果,人民网内容大赛二等奖等多项荣誉。 博士在读期间在韩国从事了有关语义web的多个项目,包括新一代语义网络服务技术的开发和基于本体的电子健康记录相互合作技术的开发等科研项目。回国后负责国家自然科学青年基金一项和教育部博士点基金一项,担任一项国家863项目副组长,承担国家自然科学基金面上项目4项,广东省自然科学基金项目3项,深圳市基础研究布局项目2项,参与了多项国家自然科学基金与863项目的申请与研究,2011年被评为深圳市孔雀计划海外高层次人才,2010年担任第四届中国语义Web会议组委会主席,2012年担任主席主办了第六届中国语义Web会议。郑海涛长期深耕于人工智能、语义挖掘和计算机视觉领域理论和应用的研究工作,在智能计算和知识工程领域有着深厚的研究基础,提出了国际领先的多粒度语义理解模型和多模态语言生成模型,解决了大规模跨领域的中文语义关系抽取的难题,研发了先进的知识获取、计算、及生成技术,并成功实现相关应用,带领团队的研究成果处于世界领先地位并已经得到了国内外同行的认可,已在国际顶级期刊/会议上共发表论文75篇,其中在人工智能顶级期刊/会议发表32篇论文,包括CCF A类/清华计算机A类论文15篇,JCR 一区SCI期刊10篇,Google scholar 引用数超过4500次。此外,其长期担任国际顶级期刊/会议NIPS、ACL、TKDE、TOC、TIT的审稿人,在学术界有较大的影响力。 【代表性论文】 [1] Zhang, Y., Li,Z., Liu, Z., Zheng H T*.,Shen, Y., & Zhou, L. (2021). Event Detection with DynamicWord-Trigger-Argument Graph Neural Networks. IEEE Transactions on Knowledge andData Engineering. (CCF-A类,SCI检索) [2] Feng, L., Qiu,M., Li, Y., Zheng H T*, &Shen, Y. (2021, November). Wasserstein Selective Transfer Learning forCross-domain Text Mining. In Proceedings of the 2021 Conference on EmpiricalMethods in Natural Language Processing.2021. (CCF-B类,EI检索) [3] Chen M, Lin Z, Sun R, Ouyang K, Zheng H T*, Xie R,Wu W. Retrieval Enhanced Segment Generation Neural Network forTask-Oriented Dialog Systems. In IEEE ICASSP 2022. (CCF-B类,EI检索) [4] Sun R, Chen B,Zhou Q, Li Y, Cao Y, Zheng H T*. A Non-hierarchicalAttention Network with Modality Dropout for Textual Response Generation inMultimodal Dialogue Systems. In IEEE ICASSP 2022. (CCF-B类,EI检索) [5] Wang D , DingN , Li P , Zheng H T*, et al.CLINE: Contrastive Learning with Semantic Negative Examples for NaturalLanguage Understanding[C]// Proceedings of the 59th Annual Meeting of theAssociation for Computational Linguistics and the 11th International JointConference on Natural Language Processing. 2021. (CCF-A类,EI检索) [6] Ding N , Xu G, Y Chen, Zheng H T*, et al.Few-NERD: A Few-Shot Named Entity Recognition Dataset[C] // Proceedings of the59th Annual Meeting of the Association for Computational Linguistics and the11th International Joint Conference on Natural Language Processing. 2021.(CCF-A类,EI检索) [7] Wang W, Li P, Zheng H T*, et al. Generating Diversified Comments via Reader-Aware Topic Modelingand Saliency Detection. In Proceedings of the Thirty-Fifth AAAI Conference onArtificial Intelligence (AAAI), 2021. (CCF-A类,EI检索) [8] Feng L, Qiu M, Li Y, Zheng H T*,Shen Y, et al. Learning to Augment for Data-Scarce Domain BERT KnowledgeDistillation. In Proceedings of the Thirty-Fifth AAAI Conference on ArtificialIntelligence (AAAI), 2021. (CCF-A类,EI检索) [9] Shen, Ying, etal. "Modeling Relation Paths for Knowledge Graph Completion." IEEETransactions on Knowledge and Data Engineering (2020). (CCF-A类,SCI检索) [10] Zihan Xu,Hai-Tao Zheng*,Zuoyou Fu,Wei Wang:Enhancing Question Understanding and Representationfor Knowledge Base Relation Detection. IEEEInternational Conference on Data Mining, ICDM 2018: 1362-1367(CCF-B类,EI检索) [11] Ningning Ma, Xiangyu Zhang, Hai-Tao Zheng*,Jian Sun: ShuffleNet V2: Practical Guidelines for EfficientCNN Architecture Design. ECCV (14) 2018: 122-138(CCF-B类,EI检索) [12] Lin Z , Li Z , Ding N,Hai-Tao Zheng*,et al. Integrating LinguisticKnowledge to Sentence Paraphrase Generation[J]. Proceedings of the AAAIConference on Artificial Intelligence, 2020, 34(5):8368-8375. (CCF-A类,EI检索) [13] Xu Z , Zheng H T* , Zhai S , etal. Knowledge and Cross-Pair Pattern Guided Semantic Matching for QuestionAnswering[J]. Proceedings of the AAAI Conference on Artificial Intelligence,2020, 34(5):9370-9377. (CCF-A类,EI检索) [14] Bai Y , Li Z , Ding N, Hai-Tao Zheng*, et al.Infobox-to-text Generation with Tree-like Planning based Attention Network[C]//Twenty-Ninth International Joint Conference on Artificial Intelligence andSeventeenth Pacific Rim International Conference on Artificial Intelligence{IJCAI-PRICAI-20. 2020. (CCF-A类,EI检索) [15] Li Z , Lin Z , Ding N, Hai-Tao Zheng*, et al. Triple-to-Text Generation with anAnchor-to-Prototype Framework[C]// Twenty-Ninth International Joint Conferenceon Artificial Intelligence and Seventeenth Pacific Rim International Conferenceon Artificial Intelligence {IJCAI-PRICAI-20. 2020.(CCF-A类,EI检索) [16] Ding N , Long D , Xu G , Hai-Tao Zheng*, et al. Coupling Distant Annotation and AdversarialTraining for Cross-Domain Chinese Word Segmentation[C]// Proceedings of the58th Annual Meeting of the Association for Computational Linguistics. 2020. (CCF-A类,EI检索) [17] Lin Z , Cai D , Wang Y , Hai-Tao Zheng*,et al. The World is Not Binary: Learning to Rankwith Grayscale Data for Dialogue Response Selection[C]// Proceedings of the2020 Conference on Empirical Methods in Natural Language Processing ,2020. (CCF-B类,EI检索) [18] Jin-Yuan Chen, Hai-Tao Zheng*,Yong Jiang, Shu-Tao Xia, Cong-Zhi Zhao: A probabilistic model for semantic advertising. Knowl. Inf. Syst. 59(2): 387-412 (2019) (CCF-B类,EI检索) [19] Ziran Li,Ning Ding, Zhiyuan Liu, Hai-Tao Zheng*, Ying Shen. Chinese RelationExtraction with Multi-Grained Information and External LinguisticKnowledge[C]//Proceedings of the 57th Annual Meeting of the Association forComputational Linguistics (ACL). 2019. (CCF-A类,EI检索) [20] Jin-YuanChen, Hai-Tao Zheng*, Yong Jiang, Shu-Tao Xia, Cong-Zhi Zhao: Aprobabilistic model for semantic advertising. knowledge and informationsystems. 59(2): 387-412 (2019) (CCF-B类,SCI检索) [21] Wei Wang, Hai-Tao Zheng*, Hao Liu. UserPreference-Aware Review Generation[C] //Pacific-Asia Conference on KnowledgeDiscovery and Data Mining. Springer, Cham, 2019: 225-236. (CCF-B类,EI检索) [22] Ning Ding, Ziran Li, Zhiyuan Liu, Hai-Tao Zheng*, Zibo Lin. Event Detection with Trigger-Aware Lattice NeuralNetwork.[C] // Proceedings of the 2019 Conference on Empirical Methods inNatural Language Processing and the 9th International Joint Conference onNatural Language Processing (EMNLP-IJCNLP), 2019, 347-356. (CCF-B类,EI检索) [23] Wang D , Li Z , Hai-Tao Zheng* , et al. Integrating User History intoHeterogeneous Graph for Dialogue Act Recognition[C]// Proceedings of the 28thInternational Conference on Computational Linguistics. 2020. (CCF-B类,EI检索) [24] Wang L , Xu Z , Lin Z , Hai-Tao Zheng*,et al. Answer-driven Deep Question Generationbased on Reinforcement Learning[C]// Proceedings of the 28th InternationalConference on Computational Linguistics. 2020. (CCF-B类,EI检索) [25] Sheng D , Wang D , Shen Y , Hai-Tao Zheng*, et al. Summarize before Aggregate: AGlobal-to-local Heterogeneous Graph Inference Network for ConversationalEmotion Recognition[C]// Proceedings of the 28th International Conference onComputational Linguistics. 2020. (CCF-B类,EI检索) [26] Hai-Tao Zheng, Ji-Min Guo, Yong Jiang,Shu-Tao Xia:Query-Focused Multi-document Summarization Based on ConceptImportance. PAKDD (2) 2016: 443-453(CCF-B类,EI检索) 【兼职情况】 中国语义网及网络科学国际会议组委会主席 国际语义处理促进会议技术评委 【获奖情况】 2020年腾讯AI Lab犀牛鸟专项研究及访问学者计划 技术创新奖(全国仅2名); 2021年度腾讯犀牛鸟精英人才计划“优秀导师奖”; 2022年10月获得第二十一届中国计算语言学大会CCL2022年度“汉语学习者文本纠错评测竞赛一等奖”; CSWS2010 BestPoster Award; VALSE2019 年度杰出论文奖; 深圳市孔雀计划海外高层次人才; 深圳市南山区“领航人才”; 深圳市地方级领军人才。 【优秀学生】 丁宁:2021“百度奖学金”、2020、2021年博士研究生国家奖学金、清华大学深圳国际研究生院“学术新秀”提名奖、清华大学研究生“清峰”奖学金 李自然:2019年硕士研究生国家奖学金、全球“西贝尔”学者称号(中国仅6人)、清华大学优秀硕士毕业论文、清华大学计算机系优秀毕业生 林子博:清华大学计算机系优秀毕业生 徐子涵:清华大学优秀毕业生、清华大学优秀硕士毕业论文 周颖敏:清华大学优秀硕士毕业论文 陈望:清华大学计算机系优秀毕业生
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