Xinghong Tang is part of the Pediatric Complex Care Integration (PCCI) Learning Health Project, where she is responsible for constructing the pipeline for predictive modeling, designing quantitative evaluations for program implementation, and developing a clinical decision-support tool using the Tableau data visualization suite. She received an MS in biomedical engineering from Duke University and a BS in materials science and engineering from UCLA. Before becoming an AI Health Fellow, she worked as a Health Data Scientist Intern at Duke Clinical Research Institute where she developed models for the Medicare Shared Savings Program (MSSP) Project. Her interest in data science stems from her desire to apply artificial intelligence in many different areas. She believes AI will revolutionize the healthcare industry and exhibit its power in medical applications.