Guohao Dai
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Hardware and Architecture top 5%
- Computer Networks and Communications top 10%
- Topics
- Advanced Memory and Neural Computing (12 papers)Advanced Neural Network Applications (10 papers)Ferroelectric and Negative Capacitance Devices (8 papers)
- Journals
- IEEE Transactions on ComputersIEEE Transactions on Computer-Aided Design of Integrated Circuits and SystemsACM Transactions on Reconfigurable Technology and Systems
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Guohao Dai
39 papers receiving 427 citations
Peers
Comparison fields: 5 of 44
- Electrical and Electronic Engineering 199
- Computer Vision and Pattern Recognition 160
- Artificial Intelligence 157
- Hardware and Architecture 113
- Computer Networks and Communications 84
Countries citing papers authored by Guohao Dai
This map shows the geographic impact of Guohao Dai'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 Guohao Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guohao Dai more than expected).
Fields of papers citing papers by Guohao Dai
This network shows the impact of papers produced by Guohao Dai. 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 Guohao Dai. The network helps show where Guohao Dai may publish in the future.
Co-authorship network of co-authors of Guohao Dai
This figure shows the co-authorship network connecting the top 25 collaborators of Guohao Dai. A scholar is included among the top collaborators of Guohao Dai 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 Guohao Dai. Guohao Dai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 4 | |
| 8 | 49 | |
| 9 | 9 | |
| 10 | 12 | |
| 11 | 9 | |
| 12 | 1 | |
| 13 | 2 | |
| 14 | 7 | |
| 15 | 18 | |
| 16 | 3 | |
| 17 | 6 | |
| 18 | 67 | |
| 19 | 3 | |
| 20 | 6 |
About Guohao Dai
Guohao Dai is a scholar working on Computational Mathematics, Hardware and Architecture and Computer Vision and Pattern Recognition, having authored 46 papers that have together received 432 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (12 papers), Advanced Neural Network Applications (10 papers) and Ferroelectric and Negative Capacitance Devices (8 papers). The work is most often cited by research in Computational Mathematics (24 citations), Hardware and Architecture (113 citations) and Computer Vision and Pattern Recognition (160 citations). Guohao Dai has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Yu Wang, Huazhong Yang, Zhenhua Zhu, Guyue Huang, Huazhong Yang, Yu Wang, Hanbo Sun, Lixue Xia, Shulin Zeng and Song Han. Their work appears in journals such as IEEE Transactions on Computers, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems and ACM Transactions on Reconfigurable Technology and Systems.
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.