Chuan recently received her Ph.D’s degree in public health. Her main research areas are environmental health sciences, with a focus on environmental epidemiology. By using a series of data collection, statistical analysis, and modeling, her research studies the relationship between prenatal methylmercury exposure and neonatal outcomes. For her capstone project at NYCDSA, she built a complete machine learning pipeline to track and predict food desert in US. This pipeline consists of web scraping data from various sources, collecting real-time Twitter data through its Streaming API, natural language analysis (e.g. LDA topic modeling), and classification modeling, such as logistic regression, random forest, and XGBoost etc.