Yejin Choi (Hangul: 최예진; born 1977) is a South Korean computer scientist, professor, and artificial intelligence researcher.[4,13,2,42,43,44,9,41] While English and Korean sources state that she is the Dieter Schwarz Foundation Professor of Computer Science at Stanford University and a Senior Fellow at the Stanford Institute for Human-Centered Artificial Intelligence (HAI)—with Korean sources also noting her role as a Distinguished Scientist and Senior Director at NVIDIA—Mandarin Chinese Wikipedia describes her as the Wissner-Slivka Professor of Computer Science at the University of Washington.[4,13,2,45] Her prior academic career includes serving as an Assistant Professor at Stony Brook University (2010–2014) and as a professor at the University of Washington (Brett Helsel Career Development Professor from 2020 to 2023, and Wissner-Slivka Chair from 2021 to 2024).
Choi earned her B.S. in computer science from Seoul National University in 1999 and completed her Ph.D. in computer science at Cornell University in 2010 under the supervision of Claire Cardie with the dissertation "Fine-grained opinion analysis : structure-aware approaches". Her research focuses on natural language processing, computer vision, commonsense reasoning, neuro-symbolic approaches, generative model alignment and safety, and small language models (SLMs), including projects such as ATOMIC, COMET, and PIQA.[34,9] Named a MacArthur Fellow in 2022, her honors also include the ICCV Marr Prize (2013), IEEE Intelligent Systems "AI's 10 to Watch" (2016), the Amazon Alexa Prize with her team (2017), and the CRA-WP Borg Early Career Award (2018).[34,9]
Early life and education
Choi Yejin was born and grew up in South Korea. She attended Seoul National University, graduating in 1999 with a bachelor's degree in computer science according to English and Chinese Wikipedia, or in computer engineering according to Korean Wikipedia.[3] Afterwards, she moved to the United States to join Cornell University as a graduate student, where she conducted research on natural language processing with advisor Claire Cardie and earned a doctorate in computer science in 2010.[4]
After earning her doctorate, Choi joined Stony Brook University as an Assistant Professor of Computer Science.[4] At Stony Brook University, Choi developed a statistical technique to identify fake hotel reviews.[5,49]
Research and career
From 2010 to 2014, Choi served as an Assistant Professor in the Department of Computer Science at Stony Brook University. She was a professor at the Paul G. Allen School of Computer Science & Engineering at the University of Washington from 2014 to 2024, serving as a Full Professor from 2021 to 2024. In 2017, she advised and participated in winning the Amazon Alexa Prize with Team 'Sounding Board'. In 2018, she joined the Allen Institute for AI (AI2), where she worked from 2018 to 2023 as Senior Research Manager for the Mosaic Project.[6] In 2020, Choi was endowed with the Brett Helsel Professorship (or Brett Helsel Career Development Professorship), which she held until 2023 when she became The Wissner-Slivka Chair of Computer Science.[9,10,11,12]
Her research looks to endow computers with a statistical understanding of written language, and she developed an interest in neural networks and their application in artificial intelligence.[7] She began assembling a knowledge base that became known as the atlas of machine commonsense (ATOMIC), which does not make use of linguistic rules, but combines the representations of different languages within a neural network.[10] By the time she had finished the creation of ATOMIC, the language model Generative Pre-trained Transformer 2 (GPT-2) had already been released.[8] She has since made use of Commonsense Transformers (COMET) with Good old fashioned artificial intelligence (GOFAI), an approach combining symbolic reasoning and neural networks.[8,10] Choi has also developed computational models that can detect biases in language that work against people from underrepresented or vulnerable groups, with one study demonstrating that female film characters are portrayed as less powerful than their male counterparts.[11,7,13]
In 2023, Choi was a TED Main Stage Speaker, presenting "Why AI is incredibly smart—and shockingly stupid". She is also a scientific advisor to the French research group Kyutai, which is funded by Xavier Niel, Rodolphe Saadé, Eric Schmidt, and others.[12] Starting in 2024, she became an AI2050 Senior Fellow at Schmidt Sciences and a Distinguished Scientist / Senior Director of Language and Cognition Research at NVIDIA. In 2025, Stanford HAI announced Choi's appointment as a Senior Fellow, the Dieter Schwarz Foundation HAI Professor, and Professor of Computer Science at Stanford University.
Major achievements and evaluation
ATOMIC (2019) organized knowledge for commonsense reasoning, such as the causes, effects, and intents of human behavior, into an if-then format.[43] COMET (2019) contributed to the scalability and diversity of knowledge graphs by presenting a commonsense knowledge generation approach utilizing pretrained language models.[44] PIQA (2020) provided a benchmark for measuring physical commonsense reasoning performance.[42]
The "Entry-Level Categories" study, presented at ICCV in 2013, won the Marr Prize for proposing a method to link image recognition results to "entry-level vocabulary" names used by humans.[38] The original text of the paper can be found in CVF Open Access and the Princeton repository.[47,48] In 2023 and 2025, they were selected for the TIME100 AI list.[24,47]
Awards and honours
Honours received earlier in the career include the 2013 International Conference on Computer Vision Marr Prize and being named an Institute of Electrical and Electronics Engineers AI One to Watch in 2016. These were followed by the Facebook ParlAI Research Award in 2017 and the Anita Borg Early Career Award in 2018. In 2020, the Association for the Advancement of Artificial Intelligence Outstanding Paper Award was conferred.
In 2021, recognitions included the Conference on Neural Information Processing Systems Outstanding Paper Award, the Association for Computational Linguistics Test-of-time Paper Award, and the Conference on Computer Vision and Pattern Recognition Longuet-Higgins Prize. In 2022, accolades included the North American Chapter of the Association for Computational Linguistics Best Paper Award, the International Conference on Machine Learning Outstanding Paper Award, and a MacArthur Fellowship.
In 2023, honors included the Association for Computational Linguistics Best Paper Award, selection for TIME100 AI 2023, and the Empirical Methods in Natural Language Processing Outstanding Paper Award. In 2025, awards received included the Association for Computational Linguistics Outstanding Paper Award, the Association for Computational Linguistics Best Demo Paper Award, and inclusion in TIME100 AI 2025.
Publications
In 2005, Yejin Choi, Claire Cardie, Ellen Riloff, and Siddharth Patwardhan published work in the Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing - HLT '05, published by the Association for Computational Linguistics. Myle Ott, Yejin Choi, Claire Cardie, and Jeffrey T. Hancock published "Finding Deceptive Opinion Spam by Any Stretch of the Imagination" in the Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies in 2011. In 2013, Girish Kulkarni, Visruth Premraj, Vicente Ordonez, Sagnik Dhar, Siming Li, Yejin Choi, Alexander C. Berg, and Tamara L. Berg published "BabyTalk: Understanding and Generating Simple Image Descriptions" in IEEE Transactions on Pattern Analysis and Machine Intelligence.