معرفی
Bing Si is an Associate Professor in the School of Computing and Augmented Intelligence at Arizona State University (ASU). She specializes in statistical machine learning, data fusion, and healthcare systems engineering, focusing on precision medicine and public health applications. Her research integrates advanced analytics with healthcare data to improve patient care, disease diagnosis, and system-level decision-making.
Education:
- PhD in Industrial Engineering, ASU (2018)
- MS in Industrial Engineering, ASU (2014)
- BS in Mathematics, University of Science and Technology of China (2012)
Research interests include machine learning methodologies for heterogeneous healthcare data, including federated learning, transfer learning, and multi-modal data analysis. She actively collaborates with clinicians and public health experts to address challenges in cardiometabolic diseases, neurological disorders, and healthcare provider practices.
Her work is funded by NIH and AHRQ grants (R03, R21, R01) and has led to impactful publications in IISE Transactions, Journal of American College Health, and Frontiers in Public Health. She has received prestigious awards such as the Early-Stage Distinguished Research Award (2023) and serves as a Guest Editor for Mathematics and Associate Editor for IISE Transactions on Healthcare Systems Engineering.
Teaching includes courses like Quality Control, Mathematical Statistics, and Research Practicum. Her research group focuses on improving healthcare systems through data-driven approaches, emphasizing interdisciplinary collaboration and real-world impact.
