Hao Ye
- Electrical and Electronic Engineering top 1%
- Artificial Intelligence top 0.5%
- Computer Networks and Communications top 1%
- Aerospace Engineering top 1%
- Signal Processing top 1%
- Co-authors
- Geoffrey Ye LiBiing‐Hwang JuangLe LiangZhijin QinGuanding YuWei JiaKathiravetpillai SivanesanJoonBeom Kim
- Topics
- Wireless Signal Modulation Classification (9 papers)Vehicular Ad Hoc Networks (VANETs) (8 papers)Computational Drug Discovery Methods (6 papers)
- Cited by
- Computer Networks and CommunicationsArtificial IntelligenceElectrical and Electronic Engineering
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Hao Ye
54 papers receiving 4.8k citations
Hit Papers
Peers
Comparison fields: 5 of 150
- Electrical and Electronic Engineering 3.0k
- Artificial Intelligence 1.9k
- Computer Networks and Communications 1.4k
- Aerospace Engineering 716
- Signal Processing 461
Countries citing papers authored by Hao Ye
This map shows the geographic impact of Hao Ye'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 Hao Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hao Ye more than expected).
Fields of papers citing papers by Hao Ye
This network shows the impact of papers produced by Hao Ye. 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 Hao Ye. The network helps show where Hao Ye may publish in the future.
Co-authorship network of co-authors of Hao Ye
This figure shows the co-authorship network connecting the top 25 collaborators of Hao Ye. A scholar is included among the top collaborators of Hao Ye 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 Hao Ye. Hao Ye is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 1 | |
| 9 | 7 | |
| 10 | 26 | |
| 11 | 108 | |
| 12 | 14 | |
| 13 | 62 | |
| 14 | 194 | |
| 15 | Spectrum Sharing in Vehicular Networks Based on Multi-Agent Reinforcement Learningbreakdown → | 386 |
| 16 | 154 | |
| 17 | 75 | |
| 18 | 86 | |
| 19 | 12 | |
| 20 | 9 |
About Hao Ye
Hao Ye is a scholar working on Signal Processing, Computer Networks and Communications and Artificial Intelligence, having authored 60 papers that have together received 4.9k indexed citations. Recurring topics across this work include Wireless Signal Modulation Classification (9 papers), Vehicular Ad Hoc Networks (VANETs) (8 papers) and Computational Drug Discovery Methods (6 papers). The work is most often cited by research in Computer Networks and Communications (1.4k citations), Artificial Intelligence (1.9k citations) and Electrical and Electronic Engineering (3.0k citations). Hao Ye has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Geoffrey Ye Li, Biing‐Hwang Juang, Le Liang, Zhijin Qin, Guanding Yu, Wei Jia, Kathiravetpillai Sivanesan, JoonBeom Kim, Lu Lu and May Wu. Their work appears in journals such as PLoS ONE, Proceedings of the IEEE and Journal of Hydrology.
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.