معرفی
Bing Yao is an Assistant Professor in the Department of Industrial and Systems Engineering at the University of Tennessee Knoxville, where she holds the Dan Doulet Early Career Assistant Professor title and serves as Director of the RME Program. She previously served as an Assistant Professor at Oklahoma State University's School of Industrial Engineering and Management from Fall 2019 to Summer 2022.
Education:
- Dual-Title PhD in Industrial Engineering and Operations Research, The Pennsylvania State University, 2019
- MS in Physics, The Pennsylvania State University, 2015
- BS in Physics, University of Science and Technology of China, 2012
Dr. Yao's research centers on developing physics-informed machine learning models for decision optimization in complex systems, with applications in healthcare and advanced manufacturing. Her work integrates statistical learning with physical constraints to model spatiotemporal dynamics, particularly in cardiac electrophysiology and EHR-based disease prediction. She employs deep learning, simulation optimization, and signal processing to address challenges in data quality, missing values, and system complexity.
Her recent publications demonstrate a strong trend toward AI-driven healthcare solutions, including personalized cardiac surgery planning, diabetic retinopathy screening, and sepsis prediction using longitudinal EHR data. The research consistently leverages multi-branching neural networks, physics constraints, and tensor-based imputation to improve model robustness and accuracy.
Scientific Awards:
- Best Poster Award, NERCCS, 2018
- Susan Schall Fellowship, Penn State, 2018
- First Place, IISE Healthcare Systems Student Paper, 2017
- IMS/ASA Spring Research Conference Scholarship, 2017
- First Place, Penn State IEGA/IME Poster Competition, 2017
- Best Poster Finalist, INFORMS MIF, 2016
- Samsung Scholarship, USTC, 2011
Dr. Yao actively mentors PhD students, including Jianxin Xie, Zekai Wang, and others, many of whom have received prestigious awards such as the Gilbreth Fellowship and Best Paper Finalist recognitions. She is the Lead PI on a $1.1M NSF/NIH grant for cardiac surgical planning and a Co-I on a $1.2M grant for diabetic retinopathy screening. Her research is supported by the AI TENNessee Initiative as well.
She leads a research group focused on spatiotemporal system dynamics, EHR analytics, and deep learning for medical diagnostics, currently recruiting PhD students with strong backgrounds in data science and engineering.
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