Welcome!

Currently, I am a Statistics PhD student at Cornell Tech. My current research interests are personalization in causal inference (via partial identification) and central limit theorems for high-dimensional data points. I am co-advised by Raaz Dwivedi and Kengo Kato.

Education

Statistics, PhD, Cornell Tech (2021 - Present)
Biostatistics, MS, University of Michigan, Ann Arbor (2021)
BBA Business Administration, Korea University (2019)

Preprints

Learning counterfactual distribution via kernel nearest neighbors
Kyuseong Choi, Jacob Feitelberg, Anish Agarwal, Raaz Dwivedi
Distributional matrix completion via nearest neighbors in the Wasserstein space
Jacob Feitelberg, Kyuseong Choi, Anish Agarwal, Raaz Dwivedi
N2: A Unified Python Package and Test Bench for Nearest Neighbor-Based Matrix Completion
Caleb Chin, Aashish Khubchandani, Harshvardhan Maskara, Kyuseong Choi, Jacob Feitelberg, Albert Gong, Manit Paul, Tathagata Sadhukhan, Anish Agarwal, Raaz Dwivedi

Publications

Supervised kernel thinning
Albert Gong, Kyuseong Choi, Raaz Dwivedi
NeurIPS 2024
Robust data integration from multiple external sources for generalized linear models with binary outcomes
Kyuseong Choi, Jeremy M.G. Taylor, Peisong Han
Biometrics, Volume 80, Issue 1, March 2024
Data integration: exploiting ratios of parameter estimates from a reduced external model
Jeremy M.G. Taylor, Kyuseong Choi, Peisong Han
Biometrika, Volume 110, Issue 1, March 2023, Pages 119-134

Working Papers

Wild regenerative block bootstrap for Harris recurrent Markov Chains
Kyuseong Choi, Gabriela Ciolek, Kengo Kato
Gaussian approximation in Reproducing kernel Hilbert space, applications to kernel ridge regression
Kyuseong Choi, Kengo Kato