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Wei Zhang
Functional Magnetic Resonance Imaging (fMRI)
Hierarchical Functional Connectivity
Machine Learning Optimization Techniques
Neurodegenerative Disease Translational Applications
Computational Neuroscience
About
Dr. Wei Zhang is an assistant professor in the School of Computer and Cyber Sciences at Augusta University. Our primary research interest concentrates on interdisciplinary studies of state-of-art machine learning and computational neuroscience, more specifically identifying functional connectivity networks via functional Magnetic Resonance Imaging (fMRI). We have contributed to the field by advancing the machine learning approach and cutting-edge optimization techniques to investigate the hierarchical functional connectivity in humans, as well as applying innovative approaches to clinical translational application on neurodegenerative disease.
Research Performance Summary
2012-2026
Active Research Span
First Recorded Paper
Studying on conductivity of cardiac tissues in magnetocardiography
Year:
2012
Citations:
1
Venue:
2012 International Conference on Biomedical Engineering and Biotechnology
Latest Recorded Paper
Large language models for bioinformatics
Year:
2026
Citations:
23
Venue:
Quantitative Biology 14 (1), e70014
Last 10 Years Publication Activity
This timeline shows the professor's yearly publication activity.
Publication Venues and Collaboration
Journal, Conference, and Book Publication Breakdown
Top Coauthors
Zhang
Liu
Zhao
Research Impact by Period
Papers
17
Citations
104
Avg. Citations / Paper
6.1
H-Index
6
Papers
47
Citations
815
Avg. Citations / Paper
17.3
H-Index
14
Papers
22
Citations
679
Avg. Citations / Paper
30.9
H-Index
13
Papers
2
Citations
2
Avg. Citations / Paper
1
H-Index
1
Contact and Professional Links
Detected Research Keywords
Neural Architecture Search
Task Fmri Data
Functional Brain Networks
Frequency Selective Surface
Hierarchical Functional Connectivity
Functional Connectivity Human
Connectivity Human Brain
Convolutional Neural Networks
Supervised Stochastic Coordinate
Stochastic Coordinate Coding