Wei Lin
- Computer Networks and Communications top 1%
- Information Systems top 1%
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 2%
- Hardware and Architecture top 5%
- Topics
- Advanced Neural Network Applications (18 papers)Cloud Computing and Resource Management (16 papers)Parallel Computing and Optimization Techniques (15 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Wei Lin
72 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 106
- Computer Networks and Communications 912
- Information Systems 702
- Computer Vision and Pattern Recognition 645
- Artificial Intelligence 635
- Hardware and Architecture 239
Countries citing papers authored by Wei Lin
This map shows the geographic impact of Wei Lin'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 Wei Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wei Lin more than expected).
Fields of papers citing papers by Wei Lin
This network shows the impact of papers produced by Wei Lin. 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 Wei Lin. The network helps show where Wei Lin may publish in the future.
Co-authorship network of co-authors of Wei Lin
This figure shows the co-authorship network connecting the top 25 collaborators of Wei Lin. A scholar is included among the top collaborators of Wei Lin 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 Wei Lin. Wei Lin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 7 | |
| 9 | 4 | |
| 10 | 1 | |
| 11 | 4 | |
| 12 | 16 | |
| 13 | Exploring Sparse Expert Models and Beyond | 4 |
| 14 | AntMan: Dynamic Scaling on GPU Clusters for Deep Learning. | 22 |
| 15 | 179 | |
| 16 | STREAMSCOPE: continuous reliable distributed processing of big data streams | 46 |
| 17 | Apollo: scalable and coordinated scheduling for cloud-scale computingbreakdown → | 214 |
| 18 | 2 | |
| 19 | 17 | |
| 20 | WiDS checker: combating bugs in distributed systems | 63 |
About Wei Lin
Wei Lin is a scholar working on Computational Mathematics, Hardware and Architecture and Computer Vision and Pattern Recognition, having authored 81 papers that have together received 1.9k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (18 papers), Cloud Computing and Resource Management (16 papers) and Parallel Computing and Optimization Techniques (15 papers). The work is most often cited by research in Computational Mathematics (27 citations), Computer Networks and Communications (912 citations) and Hardware and Architecture (239 citations). Wei Lin has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Lidong Zhou, Fan Li, Pei Cao, Quinn Jacobson, Jingren Zhou, Jingren Zhou, Zhengping Qian, Éric Boutin, Bing Shi and Ming Wu. Their work appears in journals such as PLoS ONE, Scientific Reports and Journal of Biomechanics.
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.