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Biography

Advisor - Statistics, Eli Lilly and Company 10/2022 – Present

茂聜路 Worked as project statistician for multiple clinical studies, including early/late-phase/pediatric development and registration of oncology assets, specializing in breast and prostate cancer

茂聜路 Responsible for statistical aspects of clinical projects, including clinical trial design, analysis, and communication of data

茂聜路 Lead projects independently, and work effectively across functions including data management, statistical programming, and clinical research

Research Assistant, Indiana University 06/2018 – 07/2022

茂聜路 Worked as a biostatistician in CARE Consortium supported by NCAA and DoD

茂聜路 Used survival analysis techniques to identify factors influencing recovery time of sports-related concussions

茂聜路 Used longitudinal analysis techniques to model the recovery trajectories of sports-related concussions

茂聜路 Collaborated with PI to prepare manuscripts for publication and slides for conference presentations

Statistics Intern, Eli Lilly and Company 06/2021 – 08/2021

茂聜路 Proposed a Bayesian information borrowing framework for modeling and projecting delayed responses with preplanned dose titration in the early-phase diabetes study

茂聜路 Conducted simulation study to evaluate the performance of the proposed method

茂聜路 Developed an R Shiny application “t-ITP” for general use, preparing a manuscript for publication

茂聜路 Organized and hosted bi-weekly intern meetup events

Statistics Intern, Sanofi 06/2020 – 08/2020

茂聜路 Conducted simulation studies to evaluate the operating characteristics of different Bayesian information borrowing methods for proof-of-concept basket trial

茂聜路 Developed and published a comprehensive R Shiny application “Basket Trial POC” for planning, analyzing, and reporting basket trials

茂聜路 Regularly presented the research work to the basket trial working group and global B&P team

Statistics Intern, dMed Biopharmaceutical Co., Ltd. 05/2017 – 08/2017

茂聜路 Conducted simulation studies to evaluate and compare traditional “3+3” design and “mCRM” Bayesian adaptive design in jointly modeling safety and efficacy outcomes for Phase I oncology trial

茂聜路 Presented research findings to Biostatistics & Programming, Data Management, and Clinical Operation Group

Research Assistant, Georgetown University 09/2015 – 04/2017

茂聜路 Developed predictive models for lung cancer based on biomarkers, clinical and radiological characteristics data

茂聜路 Applied machine learning methods and pipeline to analyze and visualize high-dimensional omics data

茂聜路 Consulted with researchers to conduct statistical analyses using appropriate computation and graphical software

茂聜路 Collaborated with investigators on the preparation of manuscripts for publication

Research Interest

Title: Marginal Regression Analysis of Clustered and Incomplete Event History Data 06/2018 – Present

Part I Semiparametric Marginal Regression for Clustered Competing Risks Data with Missing Cause of Failure

茂聜路 Proposed a framework for semiparametric marginal regression analysis of clustered competing risks data with informative cluster size and missing causes of failure

茂聜路 Conducted simulation study to evaluate the properties of the proposed methods

茂聜路 Established the uniform consistency and asymptotic normality of the proposed estimators

茂聜路 Prepared a manuscript for publication and delivered poster/oral presentations

茂聜路 Developed an R Package “ClusteredMPPLE” for public use (https://github.com/wz11/ClusteredMPPLE)

茂聜路 This work won the 2021 International Biometric Society EMR Lagakos Student Paper Award

Part II Marginal Regression on Transient State Occupation Probabilities with Clustered Multistate Process Data

茂聜路 Proposed a framework for marginal regression analysis of state occupation probabilities for clustered multistate process data based on functional generalized estimating equations

茂聜路 Proposed rigorous procedure for conducting non-parametric hypothesis tests and calculating confidence bands

茂聜路 Conducted simulation studies to evaluate the properties of the proposed methods

茂聜路 Established the uniform consistency and asymptotic normality of the proposed estimators

茂聜路 Prepared a manuscript for publication and delivered poster/oral presentations

茂聜路 This work won the Charlie Sampson Memorial Poster Award at the 2022 MBSW Student Posters Competition

Part III Marginal Regression for Clustered Multistate Process Data with Missing Covariates

茂聜路Proposed a framework for marginal regression analysis of state occupation probabilities for clustered multistate process data with missing covariates based on weighted functional pseudo-expected estimating equations

茂聜路 Proposed formal procedure for non-parametric hypothesis testing and constructing confidence bands

茂聜路 Conducted simulation studies to evaluate the properties of the proposed methods and compared them with the competitive methods

茂聜路 Preparing a manuscript for publication

Title: Phase II Basket Group Sequential Clinical Trial with Binary Responses 12/2015 – 04/2017

茂聜路 Proposed and investigated a framework for Phase II basket group sequential design with binary responses

茂聜路 Used R to conduct simulation studies and evaluate the performance of the trial

茂聜路 Prepared a manuscript for publication and delivered poster/oral presentations