
Chen at ICLR 2025
English
Danqi Chen (IPA: [ ʈ͡ʂʰə̌n tan t͡ɕʰǐ]; born in Changsha, China) is a Chinese computer scientist and assistant professor at Princeton University specializing in the artificial intelligence field of natural language processing (NLP).[8] She earned her BS from Tsinghua University and her Ph.D. at Stanford University.[1] In 2008, she won a gold medal at the International Informatics Olympiad.[7,5] Known among friends as CDQ, the competitive programming algorithm CDQ Divide and Conquer is named after her acronym.[8] She is married to Huacheng Yu, an assistant professor in theoretical computer science at Princeton University.[9]
Previously a visiting scientist at Facebook AI Research (FAIR), she joined the Princeton NLP group in 2019 alongside Sanjeev Arora, Christiane Fellbaum, and Karthik Narasimhan.[2] Her primary research interests lie in text understanding as well as knowledge representation and reasoning.[6] Chen is the author of Neural Reading Comprehension and Beyond, a dissertation on utilizing artificial intelligence to access knowledge in ordinary and structured documents.[3] She has authored or co-authored multiple journal articles, including Reading Wikipedia to Answer Open-Domain Questions.[4] Additionally, Google's SyntaxNet is based on algorithms developed by Danqi Chen and Christopher Manning at Stanford.
Life and Biography
Born in Changsha, Hunan in 1990, they graduated from Changsha Yali High School in 2008. In August of the same year, they traveled to Cairo, Egypt to participate in the 20th International Olympiad in Informatics and won a gold medal. Subsequently admitted to Tsinghua University without examination, they graduated from Tsinghua University's Computer Science Laboratory (Yao Class) in 2012. In the same year, they went to the United States to pursue further studies.
They previously served as a visiting scientist at Facebook Artificial Intelligence and earned a Ph.D. from Stanford University in 2018 with the doctoral dissertation "Neural Reading Comprehension and Beyond", advised by Christopher D. Manning. In 2019, they served as an assistant professor in the Department of Computer Science at Princeton University. They were selected for the Google AI 2021 Research Scholar Program in 2021. In algorithmic competitions, the famous CDQ divide and conquer algorithm is named after the English pinyin abbreviation of their name.
Education
He received a BS degree from Tsinghua University and a PhD degree at Stanford University.[8]
Career
She was previously a visiting scientist at Facebook AI Research (FAIR). In 2019, she joined the Princeton NLP group with Sanjeev Arora, Christiane Fellbaum, and Karthik Narasimhan.[1] Google's SyntaxNet is based on algorithms developed by Danqi Chen and Christopher D. Manning at Stanford.[2]
Research
Her primary research interests are text understanding, knowledge representation, and reasoning.[3] Chen is the author of Neural Reading Comprehension and Beyond, a dissertation on using artificial intelligence to access knowledge in general and structured documents.[4] She is the author or co-author of several journal articles, including Reading Wikipedia to Answer Open-Domain Questions.[5]
Awards and Honors
They won a gold medal at the 2008 International Olympiad in Informatics.[7] The CDQ Divide and Conquer algorithm, famous in competitive programming, is named after their abbreviation "CDQ".[9] In 2019, they received the title of Pioneer in MIT Technology Review's '35 Innovators Under 35'.
Personal Life and Family
She married her Tsinghua University classmate, computer scientist Huacheng Yu, who is an assistant professor of theoretical computer science at Princeton University.[10]
References
The subject is a living Chinese-American woman computer scientist, artificial intelligence and natural language processing researcher, and writer from Changsha, Hunan, whose year of birth is unrecorded. She is an alumna of Yali High School, Tsinghua University, and Stanford University, as well as an educator from Hunan and a faculty member at Princeton University.