Weijia Fu

• adkj49@r.postjobfree.com • +1-206-***-**** • Seattle, WA

EDUCATION

University of Washington Seattle, WA

M.S. in Biostatistics Thesis (STEM) September 2017 - June 2019 Relevant Coursework: Statistical Inference, Machine Learning for Biomedical Big Data, Biostatistical Consulting, Computational Skills for Biostatistics

Nankai University Tianjin, China

B.S. in Biotechnology September 2013 - June 2017

SKILLS

Statistical software: 4 years in R (ggplot2, dplyr, data.table); STATA; MATLAB Programming languages: Python (pandas, numpy, scikit-learn); JAVA RDBMS: MySQL

Tools: Bash Shell Commands; Git; Microsoft Office; LaTeX; Markdown PROFESSIONAL EXPERIENCE

Institute for Health Metrics and Evaluations Seattle, WA Research Scientist I in Global Burden of Disease, Cancer September 2019 - Present

• Led researches on mortality, incidence and prevalence estimation for 20 cancers, of which 2 cancers are the first release in the world.

• Performed parameter tunning and feature selection for the Cause of Death Ensemble model and improved predictions of models for 7 causes by reducing at least 13% root mean squared error (RMSE).

• Improved working efficiency of the team greatly by conducting exploratory data analysis, developing systematic methods to identify outliers and producing model diagnostic visualizations for model vetting.

• Collaborated with IHME collaborators from 50 countries by explaining cancer estimation pipeline, providing information on progress and answering over 150 results- or model-related questions.

• Led 3 projects on development and implementation of modelling innovations to improve cancer modelling pipeline. One of the projects developed a new cancer survival estimation model which outperformed the previous model by 23% to 55% for 4 causes. The innovated method and results were presented in IHME seminar and external collaborator meetings.

• Participated in ETL process on cancer data from 521 datasets which contains over 100k queries and applied MySQL queries to carry out a daily maintenance.

• Responsible for documenting statistical methodologies and management of git repository in bitbucket.

• Involved in the publishment of 3 papers on Lancet in the past year. Responsible for the appendix writing, figure and table generation of the results of 15 cancers in the global burden of disease 2019 final paper. Fred Hutchinson Cancer Research Center Seattle, WA Research Assistant December 2018 - June 2019

• Developed a robust, kernel machine regression-based association test framework for microbiome community level analysis. Evaluated the method performance by estimating type I error and power under different simulation scenarios.

• Presented the method and results in 2019 annual meeting of the Eastern North American Region conference. Published the method and results on Bioinformatics in November 2020. University of Washington Seattle, WA

Statistical Consultant January 2019 - June 2019

• Provided 50+ statistical consulting sessions to UW students and faculty member engaged in quantitative research. The consulting topics included regression modeling, hypothesis testing, experimental design and machine learning techniques. Wrote consulting summary to every client including question description, related statistical knowledge and potential next steps.

• Finished a project with a client to investigate the effects of moonlight and artificial light on human activity levels using mixed effects model with splines.

Biostats Tutor September 2017 - June 2019

• Tutored graduate student enrolled in statistical courses on topics including probability theory, linear regression, hypothesis testing and basic R programming.

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