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Danqi Chen (陈丹琦, IPA: [ʈ͡ʂʰə̌n tan t͡ɕʰi]; born in Changsha, China) is a Chinese-American computer scientist and assistant professor at Princeton University specializing in the AI field of NLP. In 2019, she recently joined the Princeton NLP group, alongside Sanjeev Arora, Christiane Fellbaum, Karthik Narasimhan. She is currently visiting Facebook AI Research. She earned her Ph.D at Stanford University and her BS from Qinghua University, taking classes with Turing award-winner Andrew Yao (also former professor at Princeton).
Chen is the author of Neural Reading Comprehension and Beyond, a book on using artificial intelligence to access knowledge in ordinary and structured documents. She is the author or co-author of a number of journal articles, including Reading Wikipedia to Answer Open-Domain Questions.
- "Danqi Chen's Homepage". https://cs.stanford.edu/~danqi/.
- "Princeton NLP". http://nlp.cs.princeton.edu/.
- Danqi Chen (2018). Neural Reading Comprehension and Beyond. Stanford University Press. https://books.google.ca/books?id=V7s_wAEACAAJ&dq=Danqi+Chen&hl=en&sa=X&ved=0ahUKEwjb0-Tsxr_jAhXMB80KHVEvBycQ6AEIMTAB. Retrieved 2019-07-18.
- Danqi Chen; Adam Fisch; Jason Weston; Antoine Bordes (2017-04-28). "Reading Wikipedia to Answer Open-Domain Questions". Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics: 1870–1879.. doi:https://doi.org/10.18653/v1/P17-1171.. https://arxiv.org/pdf/1704.00051.pdf. Retrieved 2019-07-18. "Using Wikipedia articles as the knowledge source causes the task of question answering (QA) to combine the challenges of both large-scale open-domain QA and of machine comprehension of text.".