Hi! I am a Ph.D. candidate (expected to graduate in 2018) in the Computer Science Department at Stanford University.
My main research interests lie within deep learning for natural language processing and understanding,
I am fortunately advised by Prof. Christopher Manning and I work in Stanford NLP Group.
Before coming to Stanford, I received my bachelor degree from Special Pilot CS Class supervised
by Prof. Andrew Yao at Tsinghua University in 2012.
and I am particularly interested in the intersection between text understanding and knowledge reasoning.
- A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task
[bib] [acl paper] [updated version] [slides] [code]
Danqi Chen, Jason Bolton, Christopher D. Manning.
In ACL 2016 (Outstanding Paper Award).
- Representing Text for Joint Embedding of Text and Knowledge Bases
Kristina Toutanova, Danqi Chen, Patrick Pantel, Hoifung Poon, Pallavi Choudhury, Michael Gamon.
In EMNLP 2015 (oral).
- Bootstrapped Self Training for Knowledge Base Population
Gabor Angeli, Victor Zhong, Danqi Chen, Arun Chaganty, Jason Bolton,
Melvin Johnson Premkumar, Panupong Pasupat, Sonal Gupta, Christopher D. Manning.
In TAC 2015.
- Observed Versus Latent Features for Knowledge Base and Text Inference
Kristina Toutanova, Danqi Chen.
In Workshop on Continuous Vector Space Models and Their Compositionality (CVSC) 2015 (oral).
- A Fast and Accurate Dependency Parser using Neural Networks
[bib] [paper] [slides] [website & code]
Danqi Chen, Christopher D. Manning.
In EMNLP 2014 (oral).
Our dependency parser is included in Stanford CoreNLP pipeline and Stanford parser (since v3.5.0).
- Reasoning With Neural Tensor Networks for Knowledge Base Completion
[bib] [paper] [poster] [data]
Richard Socher*, Danqi Chen*, Christopher D. Manning, Andrew Ng.
In NIPS 2013. ( *: equal contribution)
- Learning New Facts From Knowledge Bases With Neural Tensor Networks and Semantic Word Vectors
Danqi Chen, Richard Socher, Christopher D. Manning, Andrew Ng.
In ICLR 2013 (workshop track).
- Beyond Ten Blue Links: Enabling User Click Modeling in Federated Web Search
Danqi Chen, Weizhu Chen, Haixun Wang, Zheng Chen, Qiang Yang.
In WSDM 2012 (plenary presentation).
- Characterizing Inverse Time Dependency in Multi-class Learning
Danqi Chen, Weizhu Chen, Qiang Yang.
In ICDM 2011.
Education / Experience
- 2012.9 - Present: Ph.D. student at Stanford University
- 2008 - 2012: B.Eng from Tsinghua University, Yao Class
- 2010 Fall: Exchange student at Hong Kong University of Science and Technology (HKUST)
- 2014.7 - 2014.9: Research intern at Microsoft Research Redmond, NLP group
- Mentors: Kristina Toutanova, Hoifung Poon, Patrick Pantel, Michael Gamon
- 2011.2 - 2012.5: Research intern at Microsoft Research Asia, ML & WSM group
- Mentors: Weizhu Chen, Haixun Wang
- Head teaching assistant for CS224N: Natural Language Processing (Fall 2015).
- Teaching assistant for Java Program Design and Training, Tsinghua University, 2011
- Lecturer at National Winter Camp in Informatics, 2008-2010
- Tutor for Fundamentals of Programming, Tsinghua University, 2008
- Microsoft Research Graduate Women's Scholarship, 2013-2014
- Outstanding Graduate Award / Undergraduate Dissertation Award, Tsinghua University, 2012
- Top Scholarship for Freshman / Comprehensive Merit Scholarship x 3, Tsinghua University, 2008-2012
- Silver Medal in ACM ICPC World Finals (6th place), 2010
- Gold Medal in International Olympiad in Informatics, 2008
- My name pronounces as "dan-/'chE/" (you may also want to look at this). However, my friends like to call me "CDQ". :-)
- I was born and grew up in Changsha, China.
- I've been studying algorithms and data structure for many years, before my interests turning into AI research.
I wrote some essays in my high school, for example, here and here (in Chinese).
They are known as "plug-like dynamic programming" and "CDQ's divide-and-conquer" nowadays to some Chinese people.
- I do a lot of things in my free time - I eat, travel, do outdoors / workouts, watch movies and read books (extensively).
- Some of my portraits: 1, 2, 3 (thanks to the author Lu Wang).
- I am on Twitter.