Research

Research Interests

• High dimensional statistics

• Latent variable models

• Clustering methods

• Generalized linear models

• Causal representation learning

• Directed acyclic graphs / Structural equation modeling

Publications ( *First authors contributed equally. )

Peer Reviewed Manuscripts

• *Fan, J., *Imai, K., *Lee, I., *Liu, H., *Ning, Y., *Yang, X., "Optimal Covariate Balancing Conditions in Propensity Score Estimation," Journal of Business & Economic Statistics, Dec. 2021. Link. Reproducible Codes: Link. 

• Lee, I., Deng, S., Ning, Y., "Optimal Variable Clustering for High-Dimensional Matrix Valued Data," Information and Inference, Mar 2025.  Link. 

Submitted / Under Review

• Lee, I., Ning, Y., "G-HIVE: Parameter Estimation and Approximate Inference for Multivariate Response Generalized Linear Models with Hidden Variables." 

Software

• R Package "CBPS": Created the "AsyVar" function which estimates the asymptotic variance of the ATE (average treatment effect) obtained with the CBPS or oCBPS method outlined in Fan, Imai, Lee, Liu, Ning, Yang (2021). It also returns the finite variance estimate, the finite standard error, and a CI (confidence interval) for the ATE.

Awards and Scholarships

• Winner of the Ph.D/Postdoc Brainteaser Battle (2023), Susquehanna International LLP (SIG)

• Conference Travel Grant (2023), Cornell University

• Conference Travel Grant (2022), Cornell University

• ASA SLDS Student Paper Competition Award (2022), American Statistical Association, Statistical Learning and Data Science Section

• National Memorial Scholarship (2017-2019), Ministry of Patriots and Veterans Affairs

• Veritas Research Program Scholarship (2017),  Korea University, Dept. of Mathematics

• Best Honors Scholarship (2013), Korea University, Dept. of Mathematics

• Honors Scholarship (2013),  Korea University, Dept. of Mathematics