Han-Wen Hu
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence
- Hardware and Architecture top 10%
- Cellular and Molecular Neuroscience
- Co-authors
- Hsiang-Pang LiChia-Lin YangHung-Sheng ChangHsiang-Yun ChengTzu-Hsien YangMeng‐Fan ChangWei‐Ting LinBaochang Zhang
- Topics
- Advanced Memory and Neural Computing (9 papers)Ferroelectric and Negative Capacitance Devices (6 papers)Advanced Neural Network Applications (3 papers)
- Cited by
- Hardware and ArchitectureElectrical and Electronic EngineeringComputer Vision and Pattern Recognition
- Partner nations
- TaiwanChinaUnited Arab Emirates
In The Last Decade
Han-Wen Hu
14 papers receiving 270 citations
Peers
Comparison fields: 5 of 40
- Electrical and Electronic Engineering 218
- Computer Vision and Pattern Recognition 77
- Artificial Intelligence 67
- Hardware and Architecture 37
- Cellular and Molecular Neuroscience 26
Countries citing papers authored by Han-Wen Hu
This map shows the geographic impact of Han-Wen Hu'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 Han-Wen Hu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Han-Wen Hu more than expected).
Fields of papers citing papers by Han-Wen Hu
This network shows the impact of papers produced by Han-Wen Hu. 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 Han-Wen Hu. The network helps show where Han-Wen Hu may publish in the future.
Co-authorship network of co-authors of Han-Wen Hu
This figure shows the co-authorship network connecting the top 25 collaborators of Han-Wen Hu. A scholar is included among the top collaborators of Han-Wen Hu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Han-Wen Hu. Han-Wen Hu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 20 | |
| 5 | 11 | |
| 6 | 3 | |
| 7 | 8 | |
| 8 | 10 | |
| 9 | 14 | |
| 10 | 113 | |
| 11 | 19 | |
| 12 | 10 | |
| 13 | 58 | |
| 14 | 3 | |
| 15 | 1 |
About Han-Wen Hu
Han-Wen Hu is a scholar working on Hardware and Architecture, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering, having authored 15 papers that have together received 273 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (9 papers), Ferroelectric and Negative Capacitance Devices (6 papers) and Advanced Neural Network Applications (3 papers). The work is most often cited by research in Hardware and Architecture (37 citations), Electrical and Electronic Engineering (218 citations) and Computer Vision and Pattern Recognition (77 citations). Han-Wen Hu has collaborated with scholars based in Taiwan, China and United Arab Emirates. Frequent co-authors include Hsiang-Pang Li, Chia-Lin Yang, Hung-Sheng Chang, Hsiang-Yun Cheng, Tzu-Hsien Yang, Meng‐Fan Chang, Wei‐Ting Lin, Baochang Zhang, Keh-Chung Wang and Jing Dai. Their work appears in journals such as Micromachines, Thermal Science and Engineering Progress and Neural Processing Letters.
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.