Haoran Sun
- Electrical and Electronic Engineering top 5%
- Computer Networks and Communications top 5%
- Artificial Intelligence top 5%
- Aerospace Engineering top 10%
- Computational Mechanics top 10%
- Co-authors
- Mingyi HongXiao FuQingjiang ShiXiangyi ChenNicholas D. SidiropoulosSongtao LuXinwei ZhangWenqiang Pu
- Topics
- Sparse and Compressive Sensing Techniques (7 papers)Indoor and Outdoor Localization Technologies (5 papers)Distributed Control Multi-Agent Systems (5 papers)
- Cited by
- Computer Networks and CommunicationsElectrical and Electronic EngineeringArtificial Intelligence
- Journals
- IEEE Transactions on Signal ProcessingSIAM Journal on OptimizationFrontiers in Aging Neuroscience
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Haoran Sun
15 papers receiving 1.0k citations
Hit Papers
Peers
Comparison fields: 5 of 61
- Electrical and Electronic Engineering 744
- Computer Networks and Communications 415
- Artificial Intelligence 300
- Aerospace Engineering 153
- Computational Mechanics 97
Countries citing papers authored by Haoran Sun
This map shows the geographic impact of Haoran Sun'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 Haoran Sun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haoran Sun more than expected).
Fields of papers citing papers by Haoran Sun
This network shows the impact of papers produced by Haoran Sun. 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 Haoran Sun. The network helps show where Haoran Sun may publish in the future.
Co-authorship network of co-authors of Haoran Sun
This figure shows the co-authorship network connecting the top 25 collaborators of Haoran Sun. A scholar is included among the top collaborators of Haoran Sun 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 Haoran Sun. Haoran Sun is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 30 | |
| 2 | 4 | |
| 3 | 1 | |
| 4 | 27 | |
| 5 | 7 | |
| 6 | 14 | |
| 7 | Improving the Sample and Communication Complexity for Decentralized Non-Convex Optimization: Joint Gradient Estimation and Tracking | 18 |
| 8 | 38 | |
| 9 | 9 | |
| 10 | 40 | |
| 11 | Learning to Optimize: Training Deep Neural Networks for Interference Managementbreakdown → | 586 |
| 12 | 11 | |
| 13 | 23 | |
| 14 | 19 | |
| 15 | 225 |
About Haoran Sun
Haoran Sun is a scholar working on Computational Mechanics, Signal Processing and Computer Networks and Communications, having authored 15 papers that have together received 1.1k indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (7 papers), Indoor and Outdoor Localization Technologies (5 papers) and Distributed Control Multi-Agent Systems (5 papers). The work is most often cited by research in Computer Networks and Communications (415 citations), Electrical and Electronic Engineering (744 citations) and Artificial Intelligence (300 citations). Haoran Sun has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Mingyi Hong, Xiao Fu, Qingjiang Shi, Xiangyi Chen, Nicholas D. Sidiropoulos, Songtao Lu, Xinwei Zhang, Wenqiang Pu, Tsung‐Hui Chang and Tie Zhong. Their work appears in journals such as IEEE Transactions on Signal Processing, SIAM Journal on Optimization and Frontiers in Aging Neuroscience.
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.