Se Yoon Lee, Ph.D.

Specialties

• Bayesian Causal Inference

• Clinical Trials

• Bayesian Adaptive Design

• Group Sequential Design

• Survival Analysis

• Variable Selection

Overview of My Specialties

During the Ph.D. program in Statistics at Texas A&M University, College Station, TX, U.S.A., I conducted research on the development of Complex Innovative Trial Designs (CID) and had the opportunity to receive training at Novartis and Merck as a Ph.D. summer intern. My specialties in CIDs encompass a wide range of complex adaptive, Bayesian, and other novel clinical trial designs, with a specific focus on regulatory submissions from a sponsor's perspective. This typically requires controlling the overall type I error rate when multiple interim analyses exist or when evaluating multiple endpoints. I am proficient in both frequentist and Bayesian designs, as well as the relevant theories behind them. Additionally, my expertise in CIDs includes the practitioner skill set such as simulation and parallel computation techniques, along with the development of an R package. A proven record of publications in premier journals, such as Statistics in Medicine, Plos One and Contemporary Clinical Trial as the first authorship, and peer-reviewer experience, such as Statistics in Medicine or The Journal of Clinical Pharmacology, and industrial experience (Amgen, Johnson & Johnson, AbbVie) demonstrates my excellence in writing or reviewing Statistical Analysis Plans, Protocols, and more, and daily basis work as a Biostatistician. Every day, I aspire to become a proficient biostatistician with the ability to understand and follow the trends in the modern complexity of CIDs.

Publications

Journal Article (Statistical Methodology)

[1] Seyoon Lee and Joseph H.T. Kim. (2018) “Exponentiated generalized Pareto distribution: Properties and applications towards extreme value theory,” Communications in Statistics - Theory and Methods  Journal  arXiv 

[2] Se Yoon Lee, Bowen Lei, and Bani K. Mallick. (2020) “Estimation of COVID­19 spread curves integrating global data and borrowing information,” PLOS ONE Journal Github

[3] Kahkashan Afrin*, Ashif Iquebal*, Mostafa Karimi*, Allyson Larsen*, Se Yoon Lee*, and Bani K Mallick*. (2020) “Directionally Dependent Multi­View Clustering Using Copula Model,” PLOS ONE (*: Equal contribution, authors are alphabetically ordered in the last name) Journal

[4] Se Yoon Lee and Bani K. Mallick. (2021) “Bayesian Hierarchical modeling: application towards production results in the Eagle Ford Shale of South Texas,” Sankhyā: The Indian Journal of Statistics, Series B Journal SharedIt Github 

[5] Se Yoon Lee. (2021) “Gibbs sampler and coordinate ascent variational inference: a set-theoretical review,” Communications in Statistics - Theory and Methods Journal arXiv

[6] Se Yoon Lee, Alain Munafo, Pascal Girard, and Kosalaram Goteti. (2022) “Optimization of dose selection using multiple surrogates of toxicity as a continuous variable in Phase I cancer trial,” Contemporary Clinical Trials Journal Github Slides

[7] Se Yoon Lee. (2022) “Bayesian Nonlinear Models for Repeated Measurement Data: An Overview, Implementation, and Applications,” Mathematics Journal  arXiv 

[8] Se Yoon Lee. (2022) “The Use of a Log-Normal Prior for the Student t-Distribution,” Axioms Journal R Package

[9] Abhinav Prakash, Se Yoon Lee, Xin Liu, Lei Liu, Bani Mallick, Yu Ding (2023) “A Bayesian hierarchical model to understand the effect of terrain on wind turbine power curves,” IEEE Transactions on Sustainable Energy Journal

[10] Se Yoon Lee (2023) “A flexible dose-response modeling framework based on continuous toxicity outcomes in phase I cancer clinical trials,” BMC Trials Journal

[11] Se Yoon Lee (2024) “Using Bayesian Statistics in Confirmatory Clinical Trials in the Regulatory Setting: A Tutorial Review,” BMC Medical Research Methodology Journal

[12] Se Yoon Lee (2024) “Eliciting the discount parameter in a power prior method on the basis of the type I error consideration,” Statistics in Biopharmaceutical Research Journal

[13] Se Yoon Lee, Peng Zhao, Debdeep Pati, Bani K.Mallick. (2024) “Tail-adaptive Bayesian Shrinkage”, Electronic Journal of Statistics Journal Github Arkiv

[14] Se Yoon Lee. (2025) “A note on the sample size formula for a win ratio endpoint”, Statistics in Medicine Journal Github

Journal Article (Medical Research and Collaboration)

[1] Hyung-Kyu Chae, Hyun Jeong Hong, Se Yoon Lee, Jung-Hoon Park, Woo Joo Choi, Seungkuk Oh, Seoyeoun Ji, Yeon-Jung Hong (2022) “Factors Affecting the Outcome of Medical Treatment in Cats with Obstructive Ureteral Stones Treated with Tamsulosin: 70 Cases (2018–2022),” Veterinary Sciences Journal

[2] Hyung-Kyu Chae, Ju-Yeon Jeong, Se Yoon Lee, Hyun-Min Hwang, Kyoung-In Shin, Jung-Hoon Park, Seo-Hoon Park, Yeon-Jung Hong (2023) “Clinical Outcomes in Dogs Undergoing Cholecystectomy via a Transverse Incision: A Meta-Analysis of 121 Animals Treated between 2011 and 2021,” Veterinary Sciences Journal

Conference Paper/Poster

[1] Se Yoon Lee, Shankar Lanke, Alain Munafo, Pascal Girard, and Kosalaram Goteti. (2020) “Optimization of dose selection using multiple surrogates of toxicity as continuous variable in Phase I cancer trial” ACoP11, ISSN:2688-3953 Vol2 Github

Summer Internship Training

Biostatistics Intern, Ophthalmology Department, Novartis International AG 

"Prediction of best-corrected visual acuity for wet age-related macular degeneration patients in HAWK and HARRIER studies via a Bayesian hierarchical linear model" Abstract 

Pharmacometrics Intern, Pharmacometric Department, Merck Group

"Optimization of dose selection using multiple surrogates of toxicity as a continuous variable in Phase I cancer trial " Abstract  Poster Journal

 The internship work has been accepted to American Conference on Pharmacometrics 2020

The full paper has been published in a top medical journal "Contemporary Clinical Trials"

Open-sourse Software

[1] Bayesian Hierarchical Richards Model (Written in R, Supplemental material for the paper titled by "Estimation of COVID­19 spread curves integrating global data and borrowing information"), Download Github

[2] Spatial Weibull Model (Written in R, Appendix for the paper titled by "Bayesian Hierarchical modeling: application towards production results in the Eagle Ford Shale of South Texas"), Github 

[3] bayesestdft (Written in R, R package developed for the paper titled by "The Use of a Log-Normal Prior for the Student t-Distribution"), Github

[4] winratiosim (Written in R, R package developed for the paper titled by "A note on the sample size formula for a win ratio endpoint"), Github

Professional Activities

Editorial Service

• Editorial Board Member of BMC Medical Research Methodology (Impact Factor : 3.9)

Paper Review

• Invited Peer Reviewer of Nature Medicine (Impact Factor : 58.7)

• Invited Peer Reviewer of Statistics in Medicine (Impact Factor : 2.373)

• Invited Peer Reviewer of Pharmaceutical Statistics (Impact Factor : 1.77)

• Invited Peer Reviewer of Statistical Methods in Medical Research (Impact Factor : 1.6)

• Invited Peer Reviewer of Biostatistics (Impact Factor : 1.8)

• Invited Peer Reviewer of Bayesian Analysis (Impact Factor : 3.728)

• Invited Peer Reviewer of European Journal of Clinical Investigation (Impact Factor : 4.686)

• Invited Peer Reviewer of Artificial Intelligence Review (Impact Factor : 8.139)

• Invited Peer Reviewer of The Journal of Clinical Pharmacology (Impact Factor : 3.126)

• Invited Peer Reviewer of Frontiers in Public Health (Impact Factor : 3.709)

• Invited Peer Reviewer of The R Journal (Impact Factor : 3.984)

• Invited Peer Reviewer of Computational Geosciences (Impact Factor : 2.948)

• Invited Peer Reviewer of Journal of Applied Statistics (Impact Factor : 1.416)