Dr. Chenguang Zhu

Chenguang Zhu   Principal Research Manager, Knowledge and Language Team, Microsoft Cognitive Services Research Group

Ph.D., Computer Science Department, Stanford University

M.S., Statistics Department, Stanford University

B. Eng., Computer Science & Technology Department, Tsinghua University

Email: A [at] B, where A=chezhu and B is microsoft.com

Google Scholar | Books | Publications | Patents | Mentored Interns ]

Bio

 I am a Principal Research Manager in Microsoft Cognitive Services Research Group, leading the Knowledge and Language Team. My research is mainly in knowledge and NLP, covering text summarization, knowledge graph, and task-oriented dialogue. I have led teams to achieve first places in multiple NLP competitions, including achieving human parity in CommonsenseQA and CoQA, 1st places in CommonGen, FEVER, ARC and SQuAD v1.0. I got my Ph.D. in Computer Science from Stanford University.

News

 I organize the Distinguished Talk Series in Microsoft Cognitive Services Research Group. If you're interested in giving a talk, please contact me.

 May 22, 2022: Tutorial on Knowledge-Augmented Methods for Natural Language Processing at ACL 2022. [ Website ]

 May 11, 2022: My team has achieved human parity on HellaSwag leaderboard.

 Apr. 26, 2022: My paper on Impossible Triangle in Pre-trained Language Model has been reported in multiple media. [ 机器之心 | AI科技评论 ]

 Apr. 20, 2022: 1 paper accepted at IJCAI 2022.

 Mar. 17, 2022: I gave a virtual talk "How We Achieved Human Parity in CommonsenseQA – Fusing Knowledge into Language Models" at NLP seminar at Stanford University. [ Slides ]

 Mar. 1, 2022: 2 papers accepted at CVPR 2022.

 Feb. 23, 2022: 9 papers accepted at ACL 2022.

 Feb. 18, 2022: I gave a virtual talk "How We Achieved Human Parity in CommonsenseQA – Fusing Knowledge into Language Models" at NLP and AI seminar at Georgia Tech. [ Slides ]

 Feb. 9, 2022: I gave a virtual talk "How We Achieved Human Parity in CommonsenseQA – Fusing Knowledge into Language Models" at BLISS seminar (Berkeley Laboratory for Information and System Sciences) at UC Berkeley. [ Slides ]

 Jan. 10, 2022: Survey paper on Knowledge for NLG accepted at ACM Computing Surveys. [ Paper ]

 Dec. 1, 2021: Two papers accepted at AAAI 2022.

 Nov. 12, 2021: My team has achieved human parity on CommonsenseQA leaderboard. [ Blog | Paper ]

 Oct. 26, 2021: I gave a virtual talk in the Machine Learning / Duolingo Seminar at Carnegie Mellon University. [ Slides ]


 My recent work covers:

Books

MRC_book_cover   Machine Reading Comprehension: Algorithm and Practice (Chinese Edition)

《机器阅读理解:算法与实践》

Chenguang Zhu

China Machine Press (机械工业出版社) , 2020.03

Top 5 Favorite IT Books (Artificial Intelligence) in 2020 by 51CTO.com [ Link ]
Amazon.com | China-pub | jd.com | dangdang.com | tmall.com | Amazon.cn ]

GitHub Code ]

        MRC_book_cover  Machine Reading Comprehension: Algorithm and Practice

Chenguang Zhu

Elsevier, 2021.04

Amazon.com | Google Books | Barnes & Noble ]

GitHub Code ]

Publication

Patents

Mentored Interns

I am very fortunate to have mentored and worked with talented interns.

Talks

Awards

Miscellaneous