Scholar
Zhijin Wang
Google Scholar ID: rKUpBpMAAAAJ
Jimei University
Citations & Impact
Citations
691
H-index
14
i10-index
21
Publications
20
Co-authors
0
Contact
Publications
Resume
Academic Achievements
- Published multiple journal articles covering topics such as time series forecasting, disease prediction, and energy forecasting. Some of the papers include:
- - Explainable time-varying directional representations for photovoltaic power generation forecasting
- - Sparse dynamic graph learning for district heat load forecasting
- - Carbon futures price forecasting based on feature selection
- - A new feature selection method based on importance measures for crude oil return forecasting
- - Temporal collaborative attention for wind power forecasting
- - Enhanced transfer learning with data augmentation
- - Crosstalk between computational medicine and neuroscience in healthcare
- - Oriented Transformer for Infectious Disease Case Prediction
- - Explainable district heat load forecasting with active deep learning
- - A multivariate time series graph neural network for district heat load forecasting
- - A low-complexity evolutionary algorithm for wind farm layout optimization
- - Laplacian Lp norm least squares twin support vector machine
- - HFMD Cases Prediction using Transfer One-step-ahead Learning
- - Dual-grained directional representation for infectious disease case prediction
- - A Multi-view Multi-omics Model for Cancer Drug Response Prediction
- - A multi-view time series model for share turnover prediction
- - COVID-19 cases prediction in multiple areas via shapelet learning
- - Parallel XPath query based on cost optimization
- - Protein Secondary Structure Prediction With a Reductive Deep Learning Method
- - Dual-grained representation for hand, foot, and mouth disease
Research Experience
- Held a position at the College of Computer Engineering, Jimei University from July 2016 to present; project founder and lead programmer of the popular open-source time series forecasting library pyFAST.
Education
- No specific educational background information provided.
Background
- Research interests include: AI in health/healthcare (developing predictive models for infectious diseases and personalized medicine), time series forecasting (creating advanced models for multivariate, graph-based, and sparse time series forecasting), and recommendation systems (enhancing user experience through personalized recommendations). Affiliated with the College of Computer Engineering, Jimei University.
Miscellany
- Contributions to pyFAST are welcome! Please submit issues or pull requests on GitHub.