Byol Kim is a Postdoctoral Scholar in Professor Ali Shojaie’s group in the Department of Biostatistics at the University of Washington. She received her Ph.D. in Statistics in 2021 from the University of Chicago under the supervision of Professors Rina Foygel Barber and Mladen Kolar. She studies statistical inference problems for complicated machine learning methods—which include graphical models and conformal inference—with an emphasis on obtaining provable guarantees under realistic assumptions. Her most recent published project deals with the limits of black-box tests of algorithmic stability with assumption-free validity. She is currently working on statistical inference methods for multivariate time series data. In her free time, she enjoys taking long walks, and she is trying to make most of her time in Seattle by exploring various Seattle neighborhoods on foot.