Danqi Chen

Danqi Chen is an Associate Professor in the Department of Computer Science at Princeton University. She co-leads the Princeton NLP Group and serves as associate director of Princeton Language and Intelligence, an initiative focused on fundamental research of large AI models. Her research interests include deep learning for natural language processing, particularly in the intersection of text understanding, knowledge representation, and reasoning, with applications in question answering, information extraction, and conversational systems. Before joining Princeton, she worked as a visiting scientist at Facebook AI Research in Seattle. She received her Ph.D. from Stanford University (2018) and B.E. from Tsinghua University (2012), both in Computer Science.

Danqi Chen is a researcher at Princeton University specializing in Natural Language Processing and Machine Learning. His work focuses on improving language models through advanced pre-training techniques, such as RoBERTa and SimCSE, which enhance the robustness and performance of language models. He has also contributed to open-domain question answering with Dense Passage Retrieval and CoQA, as well as knowledge base completion and conversational question answering. His research explores the capabilities and limitations of large language models, including their ability to generate text with citations and detect pretraining data. Chen's work emphasizes the development of efficient and effective methods for text representation, reasoning, and model optimization.