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Nova · Professor Researcher · re-ranking top 20…
Zhiqiu Ye

Zhiqiu Ye

· Assistant Professor

University of Florida · Pharmacy Education and Practice

Active 2022–2024

h-index2
Citations10
Papers1515 last 5y
Funding
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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

  • New insights into nitrogen removal by divalent iron-enhanced moving bed biofilm reactor: Performance, interfacial interaction and co-occurrence network

    Bioresource Technology · 2024 · 17 citations

    • Chemistry
    • Environmental chemistry
    • Inorganic chemistry
  • Controllable forward secure identity-based encryption with equality test in privacy-preserving text similarity analysis

    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

  • 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

    121 shared

Education

  • PhD Health Services Research & Policy Analysis

    University of Rochester

    2018
  • Bachelor Degree

    Shandong University

    2008

Awards & honors

  • 2023 Janet D. Rowley Research Day Best Poster award for Heal…

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