Byol Kim

Assumption-lean inference for spectral differential network analysis of high-dimensional time series

Fri, 11 Sep 2026 00:00:00 +0000

Statistical inference for high-dimensional spectral differential networks

Wed, 01 Jul 2026 00:00:00 +0000

Black-box tests for algorithmic stability

Wed, 01 Oct 2025 00:00:00 +0000

Spectral differential network analysis for high-dimensional time series

Thu, 01 May 2025 00:00:00 +0000

Black-box tests for algorithmic stability

Sun, 01 Jan 2023 00:00:00 +0000

Invited discussant, International Seminar on Selective Inference

Tue, 01 Nov 2022 00:00:00 +0000

Enhancement-constrained acceleration (ECA)

Fri, 01 Oct 2021 00:00:00 +0000

Demonstration code for the enhancement-constrained acceleration reconstruction framework in breast DCE-MRI.

Enhancement-constrained acceleration: A robust reconstruction framework in breast DCE-MRI

Fri, 01 Oct 2021 00:00:00 +0000

Predictive inference is free with the jackknife+-after-bootstrap

Fri, 01 Oct 2021 00:00:00 +0000

KLIEPInference.jl

Fri, 01 Jan 2021 00:00:00 +0000

Julia implementation of two-sample inference for high-dimensional Markov networks via density-ratio (KLIEP) estimation.

Two-sample inference for high-dimensional Markov networks

Fri, 01 Jan 2021 00:00:00 +0000

Predictive inference is free with the jackknife+-after-bootstrap

Tue, 01 Dec 2020 00:00:00 +0000

Direct inference for Gaussian differential networks

Thu, 01 Aug 2019 00:00:00 +0000

MRI reconstruction

Wed, 01 May 2019 00:00:00 +0000

Two-sample inference for high-dimensional Markov networks

Wed, 01 May 2019 00:00:00 +0000

Bio

Mon, 01 Jan 0001 00:00:00 +0000

Byol Kim is an Assistant Professor in the Department of Statistics at Sookmyung Women’s University, which she joined in September 2024. Before that she was a postdoctoral scholar in the Department of Biostatistics at the University of Washington and a UW Data Science Postdoctoral Fellow at the eScience Institute, working with Ali Shojaie .

Care to talk?

Mon, 01 Jan 0001 00:00:00 +0000

Does it feel like your grades refuse to acknowledge your effort? Do you keep resolving to be more disciplined, only to find yourself with your phone in your hand hours later? Do you dread people asking you what you want to do after you graduate? Or is it something you can’t quite put your finger on—just a sense that something is wrong?

Contact

Mon, 01 Jan 0001 00:00:00 +0000

Email

byolkim@sookmyung.ac.kr

linkedin.com/in/byolkim

Office

Department of Statistics
Sookmyung Women's University
100 Cheongpa-ro 47-gil, Yongsan-gu
Seoul 04310, South Korea

Care to talk? →

Interested in having me as your thesis advisor? →

Interested in having me as your thesis advisor?

Mon, 01 Jan 0001 00:00:00 +0000

Please fill out the form above to set up a meeting with me if you are interested in working with me as your thesis advisor. I am likely to consider your application positively if you would like to explore (1) statistical properties of multivariate time series analysis methods using the functional dependence framework (see Wu, 2005 ), (2) asymptotic properties of conformal prediction (see Chapter 5 of Angelopoulos et al., 2024 ), or both. I also have several ideas for master’s-level projects that are more about applying conformal prediction to solve particular problems.

Notes on the pedagogical design

Mon, 01 Jan 0001 00:00:00 +0000

One of the first things you realize when you try to design and run a real experiment for the first time is that even the simplest idea hides layers of complexity—if you try to do it right.

Teaching

Mon, 01 Jan 0001 00:00:00 +0000

Teaching Mathematics in the Age of AI

Mon, 01 Jan 0001 00:00:00 +0000

Byol Kim

Assumption-lean inference for spectral differential network analysis of high-dimensional time series

Statistical inference for high-dimensional spectral differential networks

Black-box tests for algorithmic stability

Spectral differential network analysis for high-dimensional time series

Black-box tests for algorithmic stability

Invited discussant, International Seminar on Selective Inference

Enhancement-constrained acceleration (ECA)

Enhancement-constrained acceleration: A robust reconstruction framework in breast DCE-MRI

Predictive inference is free with the jackknife+-after-bootstrap

KLIEPInference.jl

Two-sample inference for high-dimensional Markov networks

Predictive inference is free with the jackknife+-after-bootstrap

Direct inference for Gaussian differential networks

MRI reconstruction

Two-sample inference for high-dimensional Markov networks

Bio

Care to talk?

Contact

Email

LinkedIn

Office

Care to talk? →

Interested in having me as your thesis advisor? →

Interested in having me as your thesis advisor?

Notes on the pedagogical design

Teaching

Teaching Mathematics in the Age of AI