Ting Yan
- Computer Networks and Communications top 2%
- Electrical and Electronic Engineering
- Statistical and Nonlinear Physics top 5%
- Artificial Intelligence top 10%
- Statistics and Probability top 5%
- Co-authors
- Tian HeTarek AbdelzaherJohn A. StankovicGang ZhouChen‐Che Jeff HuangJinfeng XuChenlei LengHong Qin
- Topics
- Complex Network Analysis Techniques (17 papers)Stochastic processes and statistical mechanics (9 papers)Random Matrices and Applications (8 papers)
- Cited by
- Computer Networks and CommunicationsStatistics and ProbabilityStatistical and Nonlinear Physics
- Partner nations
- ChinaUnited StatesEgypt
In The Last Decade
Ting Yan
44 papers receiving 831 citations
Peers
Comparison fields: 5 of 86
- Computer Networks and Communications 484
- Electrical and Electronic Engineering 270
- Statistical and Nonlinear Physics 155
- Artificial Intelligence 140
- Statistics and Probability 111
Countries citing papers authored by Ting Yan
This map shows the geographic impact of Ting Yan'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 Ting Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ting Yan more than expected).
Fields of papers citing papers by Ting Yan
This network shows the impact of papers produced by Ting Yan. 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 Ting Yan. The network helps show where Ting Yan may publish in the future.
Co-authorship network of co-authors of Ting Yan
This figure shows the co-authorship network connecting the top 25 collaborators of Ting Yan. A scholar is included among the top collaborators of Ting Yan 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 Ting Yan. Ting Yan 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 | 1 | |
| 4 | 0 | |
| 5 | Intelligent On-demand Routing Protocol for Ad Hoc Network | 0 |
| 6 | 4 | |
| 7 | 9 | |
| 8 | 10 | |
| 9 | 5 | |
| 10 | 7 | |
| 11 | On consistency of model selection for stochastic block models | 1 |
| 12 | 2 | |
| 13 | 4 | |
| 14 | 3 | |
| 15 | 21 | |
| 16 | A Practical Acoustic Localization Scheme for Outdoor Wireless Sensor Networks | 1 |
| 17 | HIGH DIMENSIONAL WILKS PHENOMENA IN RANDOM GRAPH MODELS | 1 |
| 18 | 41 | |
| 19 | Modeling Wireless Sensor Network Architectures using AADL | 3 |
| 20 | 263 |
About Ting Yan
Ting Yan is a scholar working on Statistics and Probability, Statistical and Nonlinear Physics and Mathematical Physics, having authored 48 papers that have together received 875 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (17 papers), Stochastic processes and statistical mechanics (9 papers) and Random Matrices and Applications (8 papers). The work is most often cited by research in Computer Networks and Communications (484 citations), Statistics and Probability (111 citations) and Statistical and Nonlinear Physics (155 citations). Ting Yan has collaborated with scholars based in China, United States and Egypt. Frequent co-authors include Tian He, Tarek Abdelzaher, John A. Stankovic, Gang Zhou, Chen‐Che Jeff Huang, Jinfeng Xu, Chenlei Leng, Hong Qin, Dong Jia and Lin Gu. Their work appears in journals such as Journal of the American Statistical Association, Scientific Reports and Biophysical Journal.
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.