Yo Joong (YJ) Choe
Assistant Professor of Decision Sciences
Biography
Dr. Yo Joong ("YJ") Choe is an Assistant Professor of Decision Sciences at INSEAD. He received a joint Ph.D. in Statistics and Machine Learning from Carnegie Mellon University in 2023. From 2023 to 2025, he was a Faraco Family Postdoctoral Fellow at the University of Chicago’s Data Science Institute.
Dr. Choe is an interdisciplinary researcher with a background in statistics, machine learning, and large language models (LLMs). His recent interests include understanding uncertainty via betting games ("game-theoretic statistics"), developing flexible statistical methods for sequentially observed data ("anytime-valid inference"), and applying these tools to forecast evaluation problems. In addition, Dr. Choe has a long-standing interest in LLMs, with a recent focus on understanding the geometry of concept representations in LLM embedding spaces.
Dr. Choe's research has been recognized with the Faraco Family Postdoctoral Fellowship for Outstanding Research (2025), the Best Paper Award at ICML Workshop on Mechanistic Interpretability (2024), and the Franklin V. Taylor Memorial Award from the IEEE SMC Society (2018). Outside of academia, he spent three years working in the tech industry (at Kakao and Kakao Brain) as an AI and LLM researcher.
Dr. Choe is an interdisciplinary researcher with a background in statistics, machine learning, and large language models (LLMs). His recent interests include understanding uncertainty via betting games ("game-theoretic statistics"), developing flexible statistical methods for sequentially observed data ("anytime-valid inference"), and applying these tools to forecast evaluation problems. In addition, Dr. Choe has a long-standing interest in LLMs, with a recent focus on understanding the geometry of concept representations in LLM embedding spaces.
Dr. Choe's research has been recognized with the Faraco Family Postdoctoral Fellowship for Outstanding Research (2025), the Best Paper Award at ICML Workshop on Mechanistic Interpretability (2024), and the Franklin V. Taylor Memorial Award from the IEEE SMC Society (2018). Outside of academia, he spent three years working in the tech industry (at Kakao and Kakao Brain) as an AI and LLM researcher.