# Yejin Choi

Yejin Choi is a computer scientist specializing in natural language processing and commonsense reasoning. She is a professor at Stanford University and a researcher at the Allen Institute for AI, known for developing the ATOMIC knowledge base and winning a MacArthur Fellowship.

Yejin Choi (Korean: 최예진; born 1977) is a computer scientist specializing in [natural language processing](https://www.wikiprompt.org/wiki/natural-language-processing) and commonsense reasoning in [artificial intelligence](https://www.wikiprompt.org/wiki/artificial-intelligence). She is the Dieter Schwarz Foundation Professor and Senior Fellow at the Department of Computer Science at Stanford University and the Stanford Institute for Human-Centered Artificial Intelligence (HAI), respectively. Her research focuses on endowing computers with statistical understanding of written language and detecting biases in language models.

Choi is also a senior researcher at the Allen Institute for AI, where she has led efforts to build large-scale commonsense knowledge bases. She is known for developing ATOMIC (Atlas of Machine Commonsense) and COMET (Commonsense Transformers), which combine symbolic reasoning with [neural networks](https://www.wikiprompt.org/wiki/neural-network). Her work has been recognized with numerous awards, including a 2022 MacArthur Fellowship.

## Early life and education

Choi was born in South Korea in 1977. She attended Seoul National University, where she earned a bachelor's degree in Computer Science. She then moved to the United States to pursue graduate studies at Cornell University, working under the supervision of Claire Cardie on natural language processing. After completing her doctorate, Choi joined Stony Brook University as an Assistant Professor of Computer Science. During her time at Stony Brook, she developed a statistical technique to identify fake hotel reviews, which became one of her early notable contributions to the field.

## Research and career

In 2018, Choi joined the Allen Institute for AI. Her research aims to give computers a statistical understanding of written language, moving beyond simple pattern matching. She became interested in [deep learning](https://www.wikiprompt.org/wiki/deep-learning) and its applications in [machine learning](https://www.wikiprompt.org/wiki/machine-learning). She started assembling a knowledge base that became known as ATOMIC. By the time she finished creating ATOMIC, the [large language model](https://www.wikiprompt.org/wiki/large-language-model) GPT-2 had been released. ATOMIC does not rely on linguistic rules but instead combines representations of different languages within a neural network.

In 2020, Choi was endowed with the Brett Helsel Professorship, which she held until she became Chair of Computer Science in 2023. She has since used Commonsense Transformers (COMET) with Good Old Fashioned Artificial Intelligence (GOFAI), an approach that combines symbolic reasoning and neural networks. She has developed computational models that can detect biases in language that work against people from underrepresented groups. For example, one study demonstrated that female film characters are portrayed as less powerful than their male counterparts.

In 2023, Choi became The Wissner-Slivka Chair of Computer Science. She is also a scientific advisor to French research group Kyutai, which is funded by Xavier Niel, Rodolphe Saadé, Eric Schmidt, and others. In 2025, Stanford HAI announced the appointment of Choi as senior fellow and the Dieter Schwarz Foundation HAI Professor and Professor of Computer Science at Stanford University.

## Awards and honours

Choi has received numerous awards throughout her career. In 2013, she won the International Conference on Computer Vision Marr Prize. In 2016, she was named an Institute of Electrical and Electronics Engineers AI One to Watch. In 2017, she received a Facebook ParlAI Research Award. In 2018, she won the Anita Borg Early Career Award. In 2020, she received the Association for the Advancement of Artificial Intelligence Outstanding Paper Award. In 2021, she won the Conference on Neural Information Processing Systems Outstanding Paper Award and the Association for Computational Linguistics Test-of-time Paper Award. In 2022, she received the Conference on Computer Vision and Pattern Recognition Longuet-Higgins Prize, 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, she won the Association for Computational Linguistics Best Paper Award and was named to the TIME100 AI list. In 2025, she received the Association for Computational Linguistics Outstanding Paper Award and Best Demo Paper Award, and was again named to the TIME100 AI list.

## Select publications

Choi has published extensively in top-tier venues. Her notable works include "Finding Deceptive Opinion Spam by Any Stretch of the Imagination" (2011), which introduced a method for detecting fake reviews. She also co-authored "BabyTalk: Understanding and Generating Simple Image Descriptions" (2013), which addressed image captioning. Earlier, in 2005, she published "Identifying sources of opinions with conditional random fields and extraction patterns," a foundational paper in opinion mining. These publications have been widely cited and have influenced subsequent research in natural language processing and computer vision.

## Impact and legacy

Choi's work on commonsense reasoning has been particularly influential. ATOMIC and COMET have provided resources that enable language models to reason about everyday situations, such as cause and effect. Her research on bias detection has also highlighted the importance of fairness in AI systems. By combining symbolic AI with neural approaches, she has bridged a gap between traditional and modern methods, contributing to the broader field of [generative AI](https://www.wikiprompt.org/wiki/generative-ai). Her transition to Stanford in 2025 marks a continuation of her leadership in AI research.

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Source: https://www.wikiprompt.org/wiki/yejin-choi
License: CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/)
Last updated: 2026-09-05T13:30:24.566706+00:00