Lanshun Nie
- Computer Networks and Communications top 5%
- Computer Vision and Pattern Recognition top 5%
- Electrical and Electronic Engineering
- Industrial and Manufacturing Engineering top 2%
- Artificial Intelligence top 10%
- Topics
- Scheduling and Optimization Algorithms (6 papers)Cloud Computing and Resource Management (5 papers)Context-Aware Activity Recognition Systems (5 papers)
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Lanshun Nie
27 papers receiving 869 citations
Hit Papers
Peers
Comparison fields: 5 of 75
- Computer Networks and Communications 357
- Computer Vision and Pattern Recognition 249
- Electrical and Electronic Engineering 206
- Industrial and Manufacturing Engineering 185
- Artificial Intelligence 184
Countries citing papers authored by Lanshun Nie
This map shows the geographic impact of Lanshun Nie'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 Lanshun Nie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lanshun Nie more than expected).
Fields of papers citing papers by Lanshun Nie
This network shows the impact of papers produced by Lanshun Nie. 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 Lanshun Nie. The network helps show where Lanshun Nie may publish in the future.
Co-authorship network of co-authors of Lanshun Nie
This figure shows the co-authorship network connecting the top 25 collaborators of Lanshun Nie. A scholar is included among the top collaborators of Lanshun Nie 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 Lanshun Nie. Lanshun Nie 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 | 1 | |
| 3 | 47 | |
| 4 | 50 | |
| 5 | 48 | |
| 6 | 17 | |
| 7 | 1 | |
| 8 | 48 | |
| 9 | 145 | |
| 10 | Real-Time Wireless Sensor-Actuator Networks for Industrial Cyber-Physical Systemsbreakdown → | 285 |
| 11 | 1 | |
| 12 | 6 | |
| 13 | 3 | |
| 14 | 2 | |
| 15 | 1 | |
| 16 | Multilayer production plan model and system for shipbuilding enterprise | 1 |
| 17 | Genetic simulated annealing algorithm for resource-constrained project scheduling problem | 2 |
| 18 | 1 | |
| 19 | 5 | |
| 20 | 15 |
About Lanshun Nie
Lanshun Nie is a scholar working on Industrial and Manufacturing Engineering, Management Science and Operations Research and Hardware and Architecture, having authored 28 papers that have together received 892 indexed citations. Recurring topics across this work include Scheduling and Optimization Algorithms (6 papers), Cloud Computing and Resource Management (5 papers) and Context-Aware Activity Recognition Systems (5 papers). The work is most often cited by research in Computational Mathematics (15 citations), Industrial and Manufacturing Engineering (185 citations) and Hardware and Architecture (114 citations). Lanshun Nie has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Dechen Zhan, Xiaofei Xu, Humberto González, Chengjie Wu, Chenyang Lu, Mo Sha, Bo Li, Yixin Chen, Dolvara Gunatilaka and Shi‐Jie Cao. Their work appears in journals such as Proceedings of the IEEE, IEEE Access and Sensors.
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.