Portrait of Ming Zhou

Ming Zhou

Assistant Managing Director


Dr. Ming Zhou is an Assistant Managing Director of Microsoft Research Asia and research manager of the Natural Language Computing Group.  He is the president (election manifesto) of Association of Computational Linguistics (ACL). He is the chair of the Chinese Computer Federation’s (CCF) Chinese Information Technology Committee and an executive member of the Chinese Information Processing Society (CIPS). With his relentless efforts of decades, he made important contribution to the promotion and development of NLP, especially in China.

In 1989 he designed the CEMT-I machine translation system, the first experiment on Chinese-English machine translation obtaining the government’s science and technology advancement prize in Mainland China. In 1998, he designed the famous Chinese-Japanese machine translation software product J-Beijing in Japan which was later deployed in J-Server, a popular translation service in Japan that won the Makoto Nagao Award given by the Japan Machine Translation Association in 2008. He is the leader of the renowned AI gaming of Chinese Couplets/Poetry Generation and Riddles (http://duilian.msra.cn), MS Windows IME for Chinese and Japanese, and the English Assistance Search Engine, Engkoo, which won the Wall Street Journal’s 2010 Asian Innovation Readers’ Choice Award and was packaged into Bing in 2011 as Bing Dictionary (http://cn.bing.com/dict/), and Engkoo cloud IME which was packaged as Bing IME in 2012. In 2008, the system submitted by a joint team from MSR-NLP Group, his Group and NRC and SRI obtained the top ranking in NIST Chinese-English machine translation evaluation, and the system submitted from his group obtained the 2nd ranking in NIST English-Chinese machine translation evaluation. In recent years, his group made important breakthrough in Machine Reading Comprehension (SQuAD) tasks, as the first systems reaching human-parity on both metrics of exact matching and fuzzy matching. The NMT system out of the joint effort of his group, Machine Learning Group and MS Translator also reaches the human-parity on WMT 2018 evaluation task. His group made important contributions to MS Bing search engine with NLP technologies such as word breaker, sentiment analysis, speller, dependency parser, semantic parser and QnA. His group created Chinese-English, and Cantonese-Chinese-English machine translation engine for MS Translator and Skype Translator. Recently, his group worked closely with Microsoft product teams to create well-known chat-bot products in China (Xiaoice), Japan (Rinna) and the US (Tay) with total of 200 million users. He has presented and published over 180 papers at top conferences (including 65+ ACL papers) and NLP journals, and obtained 48 international patents. He received the Ability Award from Microsoft CEO Satya Nadella in 2014 and  Beijing Outstanding Worker Medal (May-1st Labor Medal) in 2018.

He has served as area chairs of ACL, EMNLP, COLING, IJCNLP, MT SUMMIT, AAAI, IJCAI during various periods in his career, and as PC chair or general chair of important conferences in Asian-Pacific such as AIRS and NLPCC. He was the associate editor of TALLIP, and an editorial board member of Computational Linguistics and Machine Translation.

He has collaborated with universities across the Asia-Pacific and various academy associations to advance NLP research and development. For instance, in 2003 he worked with the Harbin Institute of Technology to set up an annual NLP summer school which has trained over 2000 students since then. He is one of the main organizers of the NLPCC conference since 2011, which has become China’s flagship NLP conference. His group has hosted about 500 students for internships since 1999. As the director of the Microsoft-Harbin Institute of Technology Joint Lab on NLP and the Microsoft-Tsinghua Joint Lab on Networks and Media, and PhD advisors or adjunct professors at universities such as Harbin Institute of Technology, Tianjin University, Nankai University, Shandong University, Chongqing University, Dalian University of Technology, he contributed to increases in NLP research at these universities.

Dr. Zhou received his B.S. in computer engineering from Chongqing University in 1985, and his M.S. degree and Ph.D. in computer science from Harbin Institute of Technology in 1988 and 1991. He did post-doctoral work at Tsinghua University from 1991 to 1993, later became an associate professor there. From 1996-1999, during a sabbatical, he worked for Kodensha Ltd. Co. in Japan as the leader of the Chinese-Japanese machine translation project. He joined the natural language group at Microsoft Research China (now Microsoft Research Asia) in September 1999 as researcher. He became the manager of this group in 2001. His research interests include next generation search engines, statistical and neural machine translation, question-answering, chatbots, computer poetry, riddle resolving and generation, knowledge graph, commonsense graph, semantic parser, text mining, user modelling and recommendation system.

New: I co-authored three books recently:

Machine Translation, High Education Publisher, 2018 (机器翻译,高教出版社,2018, 简介
Intelligence Question-Answering, High Education Publisher, 2018 (智能问答,高教出版社,2018,简介
Introduction to AI, Science Publisher, 2018  (人工智能导论,科学出版社,2018,简介



New: I recently co-authored three books on NLP and AI: 

      1. Machine Translation, High Education Publisher, 2018 (机器翻译,高教出版社,2018, 简介
      2. Intelligence Question-Answering, High Education Publisher, 2018 (智能问答,高教出版社,2018,简介
      3. Introduction to AI, Science Publisher, 2018 (人工智能导论,科学出版社,2018,简介


      • Zhao Yan, Nan Duan, Jun-Wei Bao, Peng Chen, Ming Zhou, Zhoujun Li, Response selection from unstructured documents for human-computer conversation systems. Knowl.-Based Syst. 142: 149-159 (2018)
      • Jun-Wei Bao, Duyu Tang, Nan Duan, Zhao Yan, Yuanhua Lv, Ming Zhou, Tiejun Zhao, Table-to-Text: Describing Table Region With Natural Language. AAAI 2018: 5020-5027
      • Zhao Yan, Duyu Tang, Nan Duan, Shujie Liu, Wendi Wang, Daxin Jiang, Ming Zhou, Zhoujun Li, Assertion-Based QA With Question-Aware Open Information Extraction. AAAI 2018: 6021-6028
      • Yikang Li, Nan Duan, Bolei Zhou, Xiao Chu, Wanli Ouyang, Xiaogang Wang, Ming Zhou, Visual Question Generation as Dual Task of Visual Question Answering. CVPR 2018: 6116-6124
      • Xingxing Zhang, Mirella Lapata, Furu Wei, Ming Zhou, Neural Latent Extractive Document Summarization. EMNLP 2018: 779-784
      • Daya Guo, Yibo Sun, Duyu Tang, Nan Duan, Jian Yin, Hong Chi, James Cao, Peng Chen, Ming Zhou, Question Generation from SQL Queries Improves Neural Semantic Parsing. EMNLP 2018: 1597-1607
      • Minghao Hu, Yuxing Peng, Furu Wei, Zhen Huang, Dongsheng Li, Nan Yang, Ming Zhou, Attention-Guided Answer Distillation for Machine Reading Comprehension. EMNLP 2018: 2077-2086
      • Tao Ge, Qing Dou, Heng Ji, Lei Cui, Baobao Chang, Zhifang Sui, Furu Wei, Ming Zhou, Fine-grained Coordinated Cross-lingual Text Stream Alignment for Endless Language Knowledge Acquisition. EMNLP 2018: 2496-2506
      • Ming Zhou, What Will Search Engines be Changed by NLP Advancements. PPT, ICTIR 2018: 7
      • Chuanqi Tan, Furu Wei, Wenhui Wang, Weifeng Lv, Ming Zhou, Multiway Attention Networks for Modeling Sentence Pairs. IJCAI 2018: 4411-4417
      • Pan Lu, Lei Ji, Wei Zhang, Nan Duan, Ming Zhou, Jianyong Wang, R-VQA: Learning Visual Relation Facts with Semantic Attention for Visual Question Answering. KDD 2018: 1880-1889
      • Chuanqi Tan, Furu Wei, Qingyu Zhou, Nan Yang, Weifeng Lv, Ming Zhou, I Know There Is No Answer: Modeling Answer Validation for Machine Reading Comprehension. NLPCC (1) 2018: 85-97
      • Jian Yang, Shuangzhi Wu, Dongdong Zhang, Zhoujun Li, Ming Zhou, Improved Neural Machine Translation with Chinese Phonologic Features. NLPCC (1) 2018: 303-315


      • Zhao Yan, Nan Duan, Peng Chen, Ming Zhou, Jianshe Zhou, Zhoujun Li, Building Task-Oriented Dialogue Systems for Online Shopping. AAAI 2017: 4618-4626
      • Shuangzhi Wu, Ming Zhou, Dongdong Zhang, Improved Neural Machine Translation with Source Syntax. IJCAI 2017: 4179-4185
      • Shuangzhi Wu, Dongdong Zhang, Shujie Liu, Ming Zhou, Modeling Indicative Context for Statistical Machine Translation. NLPCC 2017: 224-232
      • Jun-Wei Bao, Nan Duan, Ming Zhou, Tiejun Zhao, An Information Retrieval-Based Approach to Table-Based Question Answering. NLPCC 2017: 601-611













      • Kun Yu, Gang Guan, Ming Zhou: Resume Information Extraction with Cascaded Hybrid Model. ACL 2005
      • Sung-Hyon Myaeng, Ming Zhou, Kam-Fai Wong, HongJiang Zhang (Eds.): Information Retrieval Technology, Asia Information Retrieval Symposium, AIRS 2004, Beijing, China, October 18-20, 2004, Revised Selected Papers. Lecture Notes in Computer Science 3411, Springer 2005, ISBN 3-540-25065-4







Invited Talks

  1. NLP lecture at Chongqing University. 2018. PPT
  2. NLP Progress, method and focus (in Chinese), Tsinghua University, 2018. PPT
  3. How to Do Interesting Research (in Chinese), Turing Class, Peking University, 2018. PPT
  4. What Will Search Engines be Changed by NLP Advancements. ICTIR 2018: 7. PPT
  5. NLP: Its progress, opportunities and challenges, CCF-AI, 2018. PPT
  6. Latest progress of KB-QA, NLPCC 2018 QA Workshop. PPT
  7. Computer couplets, poetry and music (in Chinese). O’Reilly AI 2018, China. PPT
  8. NLP Progress at MSRA, EmTech 2018 Beijing. PPT
  9. Entertaining with Word Play-Computer Couplet, Poetry, Lyric and Riddle,  ROCLING 2016. PPT

New: I recently co-authored three books on NLP and AI: 

  1. Machine Translation, High Education Publisher, 2018 (机器翻译,高教出版社,2018, 简介
  2. Intelligence Question-Answering, High Education Publisher, 2018 (智能问答,高教出版社,2018,简介
  3. Introduction to AI, Science Publisher, 2018  (人工智能导论,科学出版社,2018,简介
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