Wencong Xiao
- Computational Mathematics top 10%
- Hardware and Architecture top 5%
- Parallel Computing and Optimization Techniques 6
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- Advanced Neural Network Applications 7
- Graph Theory and Algorithms 5
- Information Systems top 5%
- Cloud Computing and Resource Management 8
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- Advanced Graph Neural Networks 5
- Stochastic Gradient Optimization Techniques 4
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- Ferroelectric and Negative Capacitance Devices 3
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- Machine Learning in Materials Science 2
- Co-authors
- Lintao ZhangShi‐Jie CaoChen ZhangLanshun NieZhuliang YaoHaoxiang LinYunxin LiuYongqiang Xiong
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Wencong Xiao
22 papers receiving 669 citations
Peers
Comparison fields: 5 of 49
- Computational Mathematics 16
- Hardware and Architecture 176
- Computer Vision and Pattern Recognition 290
- Computer Networks and Communications 314
- Information Systems 244
Countries citing papers authored by Wencong Xiao
This map shows the geographic impact of Wencong Xiao'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 Wencong Xiao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wencong Xiao more than expected).
Fields of papers citing papers by Wencong Xiao
This network shows the impact of papers produced by Wencong Xiao. 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 Wencong Xiao. The network helps show where Wencong Xiao may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Wencong Xiao, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 0 | |
| 6 | 2024 | 5 | |
| 7 | 2023 | 7 | |
| 8 | 2023 | 4 | |
| 9 | 2023 | 1 | |
| 10 | Zico: Efficient {GPU} Memory Sharing for Concurrent {DNN} Training | 2021 | 7 |
| 11 | 2020 | 4 | |
| 12 | AntMan: Dynamic Scaling on GPU Clusters for Deep Learning. | 2020 | 22 |
| 13 | 2019 | 47 | |
| 14 | 2019 | 50 | |
| 15 | 2018 | 9 | |
| 16 | Multi-tenant GPU Clusters for Deep Learning Workloads: Analysis and Implications | 2018 | 30 |
| 17 | 2017 | 19 | |
| 18 | 2017 | 146 | |
| 19 | TUX 2 : distributed graph computation for machine learning | 2017 | 29 |
| 20 | 2015 | 90 |
About Wencong Xiao
Wencong Xiao is a scholar working on Hardware and Architecture, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 25 papers that have together received 683 indexed citations. Recurring topics across this work include Cloud Computing and Resource Management (8 papers), Advanced Neural Network Applications (7 papers), Parallel Computing and Optimization Techniques (6 papers), Graph Theory and Algorithms (5 papers), Advanced Graph Neural Networks (5 papers), Stochastic Gradient Optimization Techniques (4 papers), Ferroelectric and Negative Capacitance Devices (3 papers) and Machine Learning in Materials Science (2 papers). The work is most often cited by research in Computational Mathematics (16 citations), Hardware and Architecture (176 citations) and Computer Vision and Pattern Recognition (290 citations). Wencong Xiao has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Lintao Zhang, Shi‐Jie Cao, Chen Zhang, Lanshun Nie, Zhuliang Yao, Haoxiang Lin, Yunxin Liu, Yongqiang Xiong, Yuanwei Lu and Enhong Chen.
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.