Curriculum Vitae

Ph.D. in Biostatistics · GPA 4.0 / 4.0 · In Progress

Joint Program with UT Southwestern Medical Center

Courses: Mathematical Statistics, Computational Statistics, Statistical Analysis, Linear Regression

Sc.M. in Biostatistics (Thesis) · GPA 3.83 / 4.0 · Graduated

Courses: Survival Analysis, Causal Inference & Missing Data, Bayesian Statistical Methods, Statistical Inference, Applied Generalized Linear Models, Longitudinal Data Analysis, Multilevel Data Analysis, Statistical Learning/Big Data, Practical Data Analysis, Statistical Programming with R

B.S. in Data Science and Big Data Technology · GPA 3.87 / 4.0 · Graduated

Courses: Mathematical Analysis, Database Principles and Applications, Object-Oriented Programming, Linear Algebra, Calculus, Python Programming, Operating System, Introduction to Computer Systems, Data Structure and Algorithms, Probability and Statistics, Optimization Theory and Algorithms, Algorithm Design and Analysis, Time Series Analysis, Machine Learning and Data Mining, Multivariate Statistical Analysis, Distributed Data Warehouse

• Awarded for National Scholarship.
• Graduated with distinction.

UT Southwestern Medical Center · Dallas, Texas

McDermott Center Bioinformatics Lab · Dr. Chao Xing

Southern Methodist University · Dallas, Texas

Practical Introduction to Data Science · Dr. Danhyang Lee

Southern Methodist University · Dallas, Texas

Intro Statistical Methods · Dr. Niloofar Ghorbani

Brown University · Providence, Rhode Island

Optimization Algorithms in Data Science · Prof. Alice Paul

Brown University & Syndemics Lab at Boston Medical Center · Providence, Rhode Island

HEAL Data2Action (D2A) Program - Emulator of RESPOND Model · Prof. Stavroula Chrysanthopoulou

• Utilized GEE, GLME, MERF and LSTM models to emulate the outcome of RESPOND model;
• Advanced data transformation and model tuning techniques such as Hyperband search are used to conduct comparisons between models to find out the one with the best performance;
• Constructed a model fitting and predicting pipeline for Boston Medical Center's research workflow.

Brown University · Providence, Rhode Island

A Causal Approach to Fair Predictive Modeling via Penalized Maximum Likelihood Estimation · Prof. Alice Paul

• Utilized path-specific effects (PSEs) and penalized maximum likelihood estimation (PMLE) to address discrimination in datasets, ensuring fairer predictive outcomes;
• Employed the g-formula to estimate causal parameters, such as natural direct and indirect effects, for decomposing the total effect of variables on outcomes;
• Generalized this algorithm and developed a python package.

Brown University · Providence, Rhode Island

Applied Regression Analysis · Prof. Anarina Murillo

PricewaterhouseCoopers Shanghai Acceleration Center · Shanghai, China

• Designed and implemented the database migration scripts and added them to the project pipeline, improving the process deployment efficiency by 50%;
• Optimized SQL queries for 60 million rows of data, reducing their execution time to one-third of the original;
• Analyzed the features and distribution of user data, providing insights from a data science perspective;
• Advanced the project launching date by one day by fixing bugs from a business perspective.

Enligence Laboratory of Shanghai Lixin University of Accounting and Finance · Shanghai, China