姓名：黄民烈
职称：副教授
电子邮件：aihuang@tsinghua.edu.cn
电话：
个人主页：http://coai.cs.tsinghua.edu.cn/hml/
教育背景工学学士 (工程物理), 清华大学, 中国, 2000;
工学博士 (计算机科学与技术), 清华大学, 中国, 2006.
研究领域人工智能、机器学习理论与方法，包括深度学习、强化学习等；
自然语言处理技术与方法，如语言理解、语言生成、语言匹配与推理，具体应用包括自动问答、阅读理解、对话系统、情感分析等。
研究概况研究兴趣主要集中在人工智能与机器学习方法包括深度学习、强化学习等，自然语言处理方法与应用，包括自动问答、阅读理解、对话系统、情感分析等。主要研究语言理解、语言生成、语言匹配与推理中的科学问题，致力于解决对话系统、自动问答、阅读理解中具有挑战性的人工智能问题。曾获得汉王青年创新奖、微软合作研究奖（Microsoft Collaborative Research Award）、IJCAI-ECAI 2018杰出论文奖、CCL 2018最佳系统展示奖、NLPCC 2015最佳论文奖，2016、2017年两次入选PaperWeekly评选的最值得读10/15篇NLP论文之一；其关于情绪化聊天机器人的工作被MIT Technology Review、NVIDIA、英国卫报(The Guardian)、参考消息、新华社等媒体广泛报道，故事生成的工作被TechXplore报道。已超过60篇CCF A/B类论文发表在ACL、IJCAI、AAAI、WWW、SIGIR、EMNLP、KDD、ACM TOIS等国际顶级或主流会议及期刊上。曾担任多个国际顶级会议的领域主席或高级程序委员，如AAAI 2019、IJCAI 2019、IJCAI 2018（杰出SPC）、IJCAI 2017、ACL 2016、EMNLP 2014/2011，IJCNLP 2017等，长期担任ACM TOIS、TKDE、TPAMI、CL等顶级期刊的审稿人。与工业界建立了广泛合作，包括微软、三星、腾讯、阿里、美团、搜狗等，2019年获得微软合作研究奖。
研究课题
国家自然科学基金: 基于图结构的文献挖掘算法与理论研究 (2009-2011);
国家自然科学基金：信息多样性与信息摘要（2013-2016）；
国家科技支撑计划：法律文本中的自然语言处理问题研究（2013-2015）；
国家973项目：社会感知数据处理的基础理论（2012-2016）；
国家自然科学基金：开放领域人机对话技术研究（2019-2022）
奖励与荣誉清华大学优秀博士论文 (2006)；
清华大学优秀博士毕业生 (2006)；
2014年入选北京市世纪人才计划。
2018年获得“钱伟长中文信息处理科学技术奖汉王青年创新奖”
学术成果[1].Zheng Zhang, Minlie Huang, Zhongzhou Zhao, Feng Ji, Haiqing Chen, Xiaoyan Zhu. Memory-augmented Dialogue Management for Task-oriented Dialogue Systems.ACM Transaction on Information Systems, 2019.
[2].Mantong Zhou, Minlie Huang, Xiaoyan Zhu. Story Ending Selection by Finding Hints from Pairwise Candidate Endings. IEEE Transactions on Audio, Speech and Language Processing, 2019
[3].Zheng Zhang, Lizi Liao, Minlie Huang, Xiaoyan Zhu, Tat-Seng Chua. Neural Multimodal Belief Tracker with Adaptive Attention for Dialogue Systems. the Web Conference (WWW) 2019, San Francisco, USA
[4].Hao Zhou, Minlie Huang, Yishun Mao, Changlei Zhu, Peng Shu, Xiaoyan Zhu. Domain-Constrained Advertising Keyword Generation. the Web Conference (WWW) 2019, San Francisco, USA
[5].Ryuichi Takanobu, Tao Zhuang, Minlie Huang, Jun Feng, Haihong Tang, Bo Zheng. Aggregating E-commerce Search Results from Heterogeneous Sources via Hierarchical Reinforcement Learning. the Web Conference (WWW) 2019, San Francisco, USA
[6].Zhouxing Shi, Minlie Huang. A Deep Sequential Model for Discourse Parsing on Multi-Party Dialogues. AAAI 2019, Honolulu, Hawaii, USA
[7].Jian Guan, Yansen Wang, Minlie Huang. Story Ending Generation with Incremental Encoding and Commonsense Knowledge. AAAI 2019, Honolulu, Hawaii, USA
[8].Takanobu Ryuichi, Tianyang Zhang, Jiexi Liu, Minlie Huang. A Hierarchical Framework for Relation Extraction with Reinforcement Learning. AAAI 2019, Honolulu, Hawaii, USA
[9].Hao Zhou, Tom Yang, Minlie Huang, Haizhou Zhao, Jingfang Xu, Xiaoyan Zhu. Commonsense Knowledge Aware Conversation Generation with Graph Attention. IJCAI-ECAI 2018, Stockholm, Sweden. [IJCAI2018 Distinguished Paper]
[10].Hao Zhou, Minlie Huang, Tianyang Zhang, Xiaoyan Zhu, Bing Liu. Emotional Chatting Machine: Emotional Conversation Generation with Internal and External Memory. AAAI 2018, New Orleans, Louisiana, USA.
[11].Pei Ke, Jian Guan, Minlie Huang, Xiaoyan Zhu. Generating Informative Responses with Controlled Sentence Function. ACL 2018, Melbourne, Australia.
[12].Qiao Qian, Minlie Huang, Haizhou Zhao, Jingfang Xu, Xiaoyan Zhu. Assigning personality/identity to a chatting machine for coherent conversation generation. IJCAI-ECAI 2018, Stockholm, Sweden.
[13].Ryuichi Takanobu, Minlie Huang, Zhongzhou Zhao, Fenglin Li, Haiqing Chen, Xiaoyan Zhu, Liqiang Nie. A Weakly Supervised Method for Topic Segmentation and Labeling in Goal-oriented Dialogues via Reinforcement Learning. IJCAI-ECAI 2018, Stockholm, Sweden.
[14].Tianyang Zhang, Minlie Huang, Li Zhao. Learning Structured Representation for Text Classification via Reinforcement Learning. AAAI 2018, New Orleans, Louisiana, USA.
[15].Yansen Wang, Chenyi Liu, Minlie Huang, Liqiang Nie. Learning to Ask Questions in Open-domain Conversational Systems with Typed Decoders. ACL 2018, Melbourne, Australia.
[16].Minlie Huang, Qiao Qian, Xiaoyan Zhu. Encoding Syntactic Knowledge in Neural Networks for Sentiment Classification.ACM Trans. Inf. Syst. 35, 3, Article 26 (June 2017), 27 pages.
[17].Qiao Qian, Minlie Huang, Jinhao Lei, Xiaoyan Zhu. Linguistically Regularized LSTMs for Sentiment Classification.ACL 2017.
[18].Han Xiao, Minlie Huang, Lian Meng, Xiaoyan Zhu. SSP: Semantic Space Projection for Knowledge Graph Embedding with Text Descriptions.AAAI 2017. February 4–9, San Francisco, US.
[19].Yequan Wang, Minlie Huang, Li Zhao, Xiaoyan Zhu. Attention-based LSTM for Aspect-level Sentiment Classification.EMNLP 2016, Austin, Texas, USA.
[20].Han Xiao, Minlie Huang, Xiaoyan Zhu. TransG: A Generative Model for Knowledge Graph Embedding.ACL 2016, Berlin, Germany.
[21].Biao Liu, Minlie Huang, Song Liu, Xuan Zhu, Xiaoyan Zhu. A Sentence Interaction Network for Modeling Dependence between Sentences.ACL 2016, Berlin, Germany.
[22].Han Xiao, Minlie Huang, Xiaoyan Zhu. From One Point to A Manifold: Knowledge Graph Embedding For Precise Link Prediction.IJCAI 2016, New York, USA.
[23].Li Zhao, Minlie Huang, Ziyu Yao, Rongwei Su, Yingying Jiang, Xiaoyan Zhu. Semi-Supervised Multinomial Naive Bayes for Text Classification by Leveraging Word-Level Statistical Constraint.AAAI 2016, Phoenix, Arizona, USA.