Zhiqiu Ye
· Assistant ProfessorUniversity of Florida · Pharmacy Education and Practice
Active 2022–2024
About
Zhiqiu (Sophie) Ye, Ph.D., is an Assistant Professor within the Department of Pharmaceutical Outcomes and Policy at the University of Florida College of Pharmacy. Her research focuses on promoting equity in healthy aging for optimized medication management. She examines the organization, delivery, and regulation of pharmaceutical services during care transitioning as well as long-term services and supports related to medication use, employing a stakeholder-partnered computational social science approach. Dr. Ye's research interests include fairness in quality measurement related to medication use, with a focus on interorganizational relationships; equitability in policy implementation, emphasizing social determinants of health; and theory-informed policy analysis for cardiovascular diseases and stroke care delivery, concentrating on the effectiveness and implementation of public health laws. She has received recognition for her work, including a pilot grant from the Bucksbaum Institute for Clinical Excellence at the University of Chicago Medicine and the 2023 Janet D. Rowley Research Day Best Poster award for Health Services Research at the Department of Medicine at the University of Chicago. Dr. Ye holds a Bachelor of Medicine in nursing science from Shandong University, China, and a Ph.D. in Health Services Research and Policy from the University of Rochester.
Research topics
- Computer Science
- Machine Learning
- Information Retrieval
- Mathematics
- Artificial Intelligence
- Computer Security
- Chemistry
- Environmental engineering
- Geology
- Econometrics
- Biology
- Theoretical computer science
- Environmental chemistry
- Paleontology
- Organic chemistry
- Inorganic chemistry
Selected publications
Bioresource Technology · 2024 · 17 citations
- Chemistry
- Environmental chemistry
- Inorganic chemistry
Information Sciences · 2024 · 6 citations
- Computer Science
- Computer Security
- Computer Science
Research on the Improved Combinatorial Prediction Model of Steel Price Based on Time Series
Tehnicki vjesnik - Technical Gazette · 2023 · 6 citations
- Computer Science
- Machine Learning
- Computer Science
Accurately predicting the price change of steel (main building materials) is an effective means to control and manage the cost of construction projects. It is one of the ways for construction enterprises to reasonably allocate building materials, save resources, reduce carbon emissions and reduce environmental pollution. Based on the monthly historical price data of 100 steel rebar (16 mm) from November 2010 to February 2019, the separation and retrieval process of the four components in the time series are improved. The improved multiplicative and additive models were used to make separate predictions, and the reasonable weight is given to combine the multiplication and addition model by the reciprocal of variance method. Finally, an improved prediction model of steel bar price combination with higher prediction accuracy is obtained. The prediction results show that the improved multiplication model and addition model have higher prediction accuracy, their MAPE are 2.62% and 2.36% respectively. Moreover, the prediction accuracy of the combined model is even higher, its MAPE is 2.29%. The prediction accuracy of the improved composite model is higher than that of the individual models. The improved combined prediction model of reinforcement price based on time series method can provide some reference and help for cost control and management in construction engineering, further reduce resource waste and construction non-point source pollution.
Frequent coauthors
- 121 shared
Peter C. Knipe
Queen's University Belfast
- 121 shared
Travis A. Hammerstad
- 121 shared
Garima Dahiya
Duke University
- 121 shared
Changsheng Zhang
Zhengzhou University
- 121 shared
Guangfeng Jiang
- 121 shared
Attilio C. Neto
Universidade Federal de São Carlos
- 121 shared
Ir
Dalian University of Technology
- 121 shared
X Sun
Education
- 2018
PhD Health Services Research & Policy Analysis
University of Rochester
- 2008
Bachelor Degree
Shandong University
Awards & honors
- 2023 Janet D. Rowley Research Day Best Poster award for Heal…
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