Photo of Xiyu Li

Xiyu Li

Also known as Rita

About Me

Hi, I'm Xiyu Li, a passionate Data Analyst with a strong academic background in statistics and computer science. I recently earned a Master of Science in Engineering in Data Science from Johns Hopkins University (May 2025), and I hold a B.A. in Statistics and Computer Science from Macalester College. I developed my skills in machine learning, statistical modeling, and data visualization through hands-on projects and academic research.

I’ve led and contributed to diverse data-driven projects, including a comprehensive flight delay prediction analysis, where my team successfully built predictive models with over 82% accuracy. My work spans across transportation data analysis, spatial crime mapping, and real-time ECG recognition, demonstrating my expertise in data wrangling, modeling, and visualization using tools such as Python, R-Studio, Tableau, and PowerBI.

With experience in both academic and industry settings, I am proficient in applying machine learning techniques, statistical analysis, and data-driven solutions to real-world problems. I am always excited to collaborate, learn, and contribute to innovative projects that have a meaningful impact.

Xiyu Li

Projects

Baltimore Crime Prediction

Baltimore Crime Prediction and Visualization Project

Analyzed spatial and temporal crime trends across Baltimore’s neighborhoods using crime, weather, and demographic data. Tested multiple ML models to predict crime by Community Statistical Area for smarter public safety planning.
Flight Delay Prediction

Flight Delay Prediction

Built machine learning models on 100M+ flight records to estimate delay duration. Explored airport, carrier, weather, and seasonal features to improve forecasting accuracy.
AI Text Comparison and Analysis

AI Text Comparison and Analysis Project

This project analyzes differences between AI-generated and human-written text using Natural Language Processing (NLP) techniques. Leveraging BERT models and FLESCH readability scores, the study examines text homogeneity, feature variation, and linguistic complexity.
Bus Ridership Analysis

Exploring the Relationship Between Public Transport Ridership and Gas Price

Explored how gas prices influence public transportation ridership using three years of daily data. Applied regression and mixed models, and built an interactive R Shiny app with Leaflet maps for dynamic visualization.
Applied Linear Mixed Model in Correlated Genetic Data

Applied Linear Mixed Model in Correlated Genetic Data
Mapping and Spatial Analyzing of Crime in Saint Paul

Mapping and Spatial Analyzing of Crime in Saint Paul

This project examines eight years of crime data across 17 neighborhoods to identify spatial and demographic crime patterns using exploratory data analysis and statistical modeling.

Exploring the Relationship Between Temperature and Spread of COVID-19

Exploring the Relationship Between Temperature and Spread of COVID-19
Language Differences between Clients & Lawyers

Language Differences between Clients & Lawyers
Data Visualization Works

Data Visualization Words