Zhixin Wu
- Automotive Engineering top 5%
- Electric and Hybrid Vehicle Technologies 4
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- Advanced Memory and Neural Computing 10
- Electric Vehicles and Infrastructure 6
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- Energy and Environment Impacts 3
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- Photoreceptor and optogenetics research 4
- Neuroscience and Neural Engineering 3
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- Neural dynamics and brain function 4
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- Composite Structure Analysis and Optimization 3
Zhixin Wu
45 papers receiving 797 citations
Hit Papers
Peers
Comparison fields: 5 of 103
- Energy Engineering and Power Technology 83
- Automotive Engineering 280
- Renewable Energy, Sustainability and the Environment 170
- Electrical and Electronic Engineering 544
- Pollution 50
Countries citing papers authored by Zhixin Wu
This map shows the geographic impact of Zhixin Wu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Zhixin Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhixin Wu more than expected).
Fields of papers citing papers by Zhixin Wu
This network shows the impact of papers produced by Zhixin Wu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Zhixin Wu. The network helps show where Zhixin Wu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Zhixin Wu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2025 | 3 | |
| 3 | 2025 | 1 | |
| 4 | 2025 | 6 | |
| 5 | 2025 | 1 | |
| 6 | 2024 | 2 | |
| 7 | 2024 | 4 | |
| 8 | Effect of various design configurations and operating conditions for optimization of a wind/solar/hydrogen/fuel cell hybrid microgrid system by a bio-inspired algorithmbreakdown → | 2024 | 87 |
| 9 | 2024 | 1 | |
| 10 | 2024 | 1 | |
| 11 | 2024 | 13 | |
| 12 | 2024 | 2 | |
| 13 | 2024 | 2 | |
| 14 | 2023 | 1 | |
| 15 | 2023 | 47 | |
| 16 | 2022 | 2 | |
| 17 | 2021 | 4 | |
| 18 | 2017 | 1 | |
| 19 | 2013 | 2 | |
| 20 | Parameter design for power train and simulation of dynamic performance of electrical vehicles | 2006 | 3 |
About Zhixin Wu
Zhixin Wu is a scholar working on Automotive Engineering, Electrical and Electronic Engineering and Cellular and Molecular Neuroscience, having authored 49 papers that have together received 822 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (10 papers), Electric Vehicles and Infrastructure (6 papers), Photoreceptor and optogenetics research (4 papers), Neural dynamics and brain function (4 papers), Electric and Hybrid Vehicle Technologies (4 papers), Composite Structure Analysis and Optimization (3 papers), Neuroscience and Neural Engineering (3 papers) and Energy and Environment Impacts (3 papers). The work is most often cited by research in Energy Engineering and Power Technology (83 citations), Automotive Engineering (280 citations) and Renewable Energy, Sustainability and the Environment (170 citations). Zhixin Wu has collaborated with scholars based in China, Iran and India. Frequent co-authors include Jihu Zheng, Xin Sun, Xue Wang, Michael Wang, Noradin Ghadimi, Akbar Maleki, Yunhe Zou, Xuetao Li, Steven Przesmitzki and Zhenhong Lin. Their work appears in journals such as Nature Communications, Renewable and Sustainable Energy Reviews and NeuroImage.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.