About me

Welcome to my webpage!

I am Tzu-Chun Chu, first-year PhD student with an emphasis in Epidemiology. My training and educational background are in plant genetics and biostatistics. Over the past four years, I gained experiences working with interdisciplinary research teams to answer critical questions pertaining to infectious disease at a national and international level. I have worked on a broad range of infectious disease topics concerning HIV, HCV, bacterial diarrhea, Ebola and COVID-19 utilizing different data sources such as electronic medical record, clinical trial, line list and questionnaire. I joined Brown University as a Senior Biostatistician in 2019. While working there, I collaborated with Pediatricians, field epidemiologists, computational scientists and clinical investigators to develop a clinical predictive model for Ebola virus disease (EVD) targeting pediatric patients I thoroughly enjoyed the work and am delighted to lead the statistical analysis. The manuscript is currently under review, and hopefully that I can show you the published article soon. Another exiting project was to analyze a N-of-1 crossover trial study to test individualized trigger(s) for the Atrial Fibrillation (AF) with the aim of improving quality of life (QoL). The importance of this study is to assess outcomes at the individual level by applying meta-analyses and Bayesian multilevel methods to a N-of-1 trial. That was my first time working with Bayesian models using the single subject clinical trial data in R, which was quite intense but fun at the same time. You can find more of my published works here. I have also become increasingly interested in sophisticated approach for model development using machine learning application. I often hear many interesting projects completed using machine learning from my coworkers but have never done it myself, so I am looking forward to learning more about it with everyone!

Programming Experiences and Research Interests

I primarily use R to conduct all my research work but I also write SAS and Stata codes. I would consider myself an intermediate R user with 3-year experiences in writing different functions for data cleaning and reconstruction, statistical analysis, model development and data visualization, but I want to learn more about other advanced R functional programming tools such as purr. My research interests are global infectious disease, treatment effectiveness and patient-centered outcomes research. Specifically, I am interested in the development and application of different statistical methods to aid clinical decision-making, and more recently, I am also developing interests in infectious disease forecasting.

Course Goal

• I want to learn how to engineer some modern R applications such as interactive graph, R shiny and personal website (already cross one item off my list at first week!!!).
• I would like to advance my R programming skills and also develop new skills in applying basic concepts and techniques of machine learning.
• I hope to get to know others who are also passionate about Public Health research and programming. I would love to know your tips in learning programming faster and more efficient. Sometimes, it gets very frustrated to get stuck and it is helpful to discuss with others who might have experienced the same issues.
  
• My goal is also to start practicing collaborative work using Github.
  
  
  

More about me outside of Public Health, mostly my life in 2020

• I LOVE traveling and I am happy that I got to explore some national parks, mountain trails and beaches with my 6-year old lab retriever mix last year! She has been very spoiled since I worked from home.
• I have leveled up my cooking/baking skills in the past year and learned how to make fruit tart, Yule log cake, Reese’s peanut butter cup cheesecake, clam chowder, lobster roll and more.
  

Useful Website

I took this open source and interactive course Link to learn about running generalized additive models for some of the projects I was working on, and I found it really helpful. The website is actually built into GitHub, including model building and data visualization for gam fit. Hope that you will also have fun learning this function!