YJ Choe

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YJ Choe
(Officially: Yo Joong Choe, 최요중)

Ph.D. Student
Department of Statistics and Data Science
Machine Learning Department
Carnegie Mellon University

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About Me

I am a fourth-year joint Ph.D. student in Statistics and Machine Learning at Carnegie Mellon University. I work on problems in feedback-driven machine learning and active learning for deep learning, under the able supervision of Aarti Singh. I am also fortunate to have worked with Aaditya Ramdas recently on the problem of (sequentially) comparing sequential forecasters. From mid-2017 to 2020, I took a lengthy leave of absence from the program to work as a Research Scientist at Kakao Brain and Kakao. In Spring 2017, I received my M.S. in Machine Learning as part of the Ph.D. program, advised by Aarti Singh, Sivaraman Balakrishnan, and Timothy Verstynen. Before that, I got my B.S. in Mathematics and Computer Science at the University of Chicago, where I worked with John Lafferty and at the Knowledge Lab.

In terms of research, I am broadly interested in statistical machine learning and deep learning, with a recent focus on feedback-driven machine learning, sequential decision making, and forecasting. At Kakao Brain and Kakao, I worked on various projects involving deep learning and (multilingual) natural language processing. During my first two years at CMU, I worked on problems in high-dimensional statistics with applications to neuroscience, and I also dabbled with statistical analyses of neural networks. Please refer to my research page or CV for further information.

I was born and raised in Seoul, South Korea. My legal first name is Yo Joong (요중), which I prefer to abbreviate as YJ in English.

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