Sidi Wang, PhD

I work as a Mathematical Statistician at the Food and Drug Administration.

I was advised by Professor Kelley Kidwell. My research interests lie broadly in Bayesian statistics and small sample clinical trials.
I received my BSc in Economics and Finance (with specialization in maths and statistics) from the University College Dublin in 2016, my MSc in Business Analytics from the National University of Singapore in 2017, and my MSc and PhD in Biostatistics from the University of Michigan in 2021 and 2024.

Publications

Dynamic enrichment of Bayesian small sample, sequential, multiple assignment randomized trial (snSMART) design using natural history data: A case study from Duchenne muscular dystrophy.
S Wang, KM Kidwell, S Roychoudhury
Biometrics (2023)
This paper won the Society for Clinical Trials Thomas C. Chalmers Student Scholarship at the 2023 Annual Meeting.

snSMART: An R Package for Small Sample, Sequential, Multiple Assignment, Randomized Trial Data Analysis.
Sidi Wang, Fang Fang, Roy Tamura, Thomas Braun and Kelley M Kidwell
Under Review

Association between nociplastic pain and premature endocrine therapy discontinuation in breast cancer patients.
E Joyce, G Carr, S Wang, CM Brummett, KM Kidwell, NL Henry
Breast Cancer Research and Treatment 197 (2), 397-404

Associations between preexisting nociplastic pain and early discontinuation of aromatase inhibitor therapy in breast cancer.
E Joyce, S Wang, M Motamed, KM Kidwell, NL Henry
Journal of Clinical Oncology 39 (15_suppl), 12068-12068

snSMART: Small N Sequential Multiple Assignment Randomized Trial Methods. R package version 0.1.0.
Sidi Wang, Kelley Kidwell and Michael Kleinsasser (2022)

Research Projects

Genetic Prediction of Complex Traits from Summary Statistics

with Dr. Xiang Zhou

  • Developed and implemented a linear model based on certain heritability assumptions for the prediction of complex traits
  • Wrote the core algorithm in C++
  • Evaluated model prediction precision against a few other existing methods by using UK Biobank data

Hierarchical Bayesian Model in Passive Surveillance Data Mining

with Dr. Nicholas Henderson

  • Developed and implemented a hierarchical Bayesian model for analyzing reports from large databases for passive surveillance of drug-related adverse events
  • Implemented EM algorithm for estimating hyperparameters
  • Evaluated fitted models with simulation studies
  • Developed an R-package for all the methods studied in the project

Machine Learning in Predictive Analysis

with Dr. Wang Tong

  • Led a group of six and performed data visualization and primary analysis on 10-year sales data of a global skincare company
  • Completed predictive data analytics with several machine learning models

Work Experiences

Biostatistics PhD Summer Intern

  • Research Project: Predicting the landmark event and benefit of Overall Survival (OS) from available Progression Free Survival (PFS) Information in Metastatic Cancer Trials

Business Data Analyst

  • Built an end-to-end supplies forecasting model which connected and optimized the overall budgeting, supply chain planning, and revenue tracking processes of the newly established PageWide Industrial (PWI) business
  • Developed a fully automated pricing tool for the supplies, which shortened the turnaround time from hours to a few minutes

Human Resources Analytics

  • Took full ownership of the attrition model overhaul in R. Utilized machine learning algorithms (XGBoost) for employee attrition analysis and prediction
  • Achievements: successfully identified the failures of the previous model. Increased model sensitivity from 60% to 85%. Project Report: Human Resources Analytics: Machine Learning in Predicting Future Resignations, supervised by Prof. Quek Ser Aik (this project was covered by Channel NewsAsia)

Audit Intern

  • Prepared and conducted audit engagements for fund companies and one of the top four British & Irish banks; Evaluated bank loan performance and borrower company operation; Reviewed and tested company risk taking
  • Reported directly to Audit Director as an intern; I was awarded twice as “Deloitte Dots” receiver, graded as “High Performance” by the firm, and was offered a full-time contract by the time I finished my internship contract

Things I Do

  • Write all the code
  • Crunch numbers
  • Climb mountains
  • Make music
  • Draw portraits
  • Stay positive

Contact Me