Growing up in a family of physicians, I often heard my parents discuss clinical practice and medical decision-making. Those conversations made me curious about the gap between the wealth of available clinical data and the knowledge clinicians can use in an individual patient's care. That question led me from computer science to biomedical informatics.
After earning my bachelor's degree in computer science, I completed an M.S. in Biomedical Informatics at the University of Pittsburgh, where I began studying predictive models for heart failure. I then returned to China to work on data-driven chronic disease management and software development. These experiences taught me to value systems that combine methodological rigor with a clear clinical purpose.
At UTHealth Houston, discussions with Dr. Liu, Xiaoyang Ruan, Liwei Wang, and colleagues at McGovern Medical School helped sharpen my interest in perioperative care. Dr. Liu's advice to start with the clinical problem and design the right tool has become central to my research: the question should guide the method, and the method should fit the clinical workflow.
Looking ahead, I aim to develop explainable, patient-specific decision support for perioperative risk management, including orthopedic care. One direction is a multi-agent framework that integrates heterogeneous clinical data and the perspectives of different clinical roles. This remains a research goal, with clinical validation and workflow integration essential to its development. Ultimately, I want my work to help clinicians turn complex evidence into informed, individualized care.