Simeng Wu | Personal Website

Personal academic website of Simeng Wu, including education, projects, skills, and CV.

Simeng Wu

M.S. Student in Statistical Science, Duke University

Statistical Modeling · Bayesian Methods · Applied Machine Learning

I am a Master’s student in Statistical Science at Duke University. Before Duke, I studied Statistics, Economics, and Finance at University College London (UCL).

My interests span statistical modeling, missing data, Bayesian methods, machine learning, and data-driven decision making. I enjoy projects that combine rigorous statistical thinking with practical implementation.

View Projects

View Experience

Download CV

Statistical Modeling · Missing Data · Bayesian Methods · Machine Learning · Quantitative Finance · Risk Management · Data-Driven Decision Making ·

Education & Skills

Academic training and selected technical tools that support my work in statistical modeling and applied data analysis.

Education

2025 - Present

Duke University

M.S. in Statistical Science

2022 - 2025

University College London (UCL)

B.Sc. in Statistics, Economics and Finance

Selected Skills

Programming

Python R SQL Stata SAS

Statistical Methods

Regression Time Series Bayesian Modeling Machine Learning

Tools

Quarto Git Docker FastAPI QuantConnect

Beyond Work - Baking Moments

Outside of academic and technical work, I enjoy baking as a slower, hands-on form of creativity. I like the balance between precision and presentation: adjusting small details, working patiently through a process, and seeing how the final result comes together.

Pistachio · Strawberry · Milk

Click the arrows to browse baking moments.

About

My academic background combines statistics, economics, and finance, with a growing focus on statistical modeling for complex real-world data. Through coursework and independent projects, I have worked across time series modeling, Bayesian computation, machine learning, data engineering, and applied analytics.

I am particularly drawn to problems where statistical methodology and implementation need to work together. I enjoy turning open-ended questions into structured analytical workflows: defining the target, building reproducible pipelines, comparing models carefully, and communicating results through reports, visualizations, and interactive tools.

Beyond technical work, I have long been interested in writing and visual communication. In high school, I founded and managed a bilingual history-focused WeChat account that grew to over 8,000 followers. This experience helped me develop a stronger sense of audience, structure, and storytelling when communicating complex ideas.