Xiaoyao Liang
- Electrical and Electronic Engineering top 5%
- Hardware and Architecture top 0.5%
- Computer Networks and Communications top 1%
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Topics
- Parallel Computing and Optimization Techniques (41 papers)Low-power high-performance VLSI design (31 papers)Advanced Memory and Neural Computing (29 papers)
- Cited by
- Hardware and ArchitectureComputer Networks and CommunicationsElectrical and Electronic Engineering
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Xiaoyao Liang
123 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 83
- Electrical and Electronic Engineering 1.1k
- Hardware and Architecture 896
- Computer Networks and Communications 828
- Artificial Intelligence 357
- Computer Vision and Pattern Recognition 273
Countries citing papers authored by Xiaoyao Liang
This map shows the geographic impact of Xiaoyao Liang'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 Xiaoyao Liang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaoyao Liang more than expected).
Fields of papers citing papers by Xiaoyao Liang
This network shows the impact of papers produced by Xiaoyao Liang. 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 Xiaoyao Liang. The network helps show where Xiaoyao Liang may publish in the future.
Co-authorship network of co-authors of Xiaoyao Liang
This figure shows the co-authorship network connecting the top 25 collaborators of Xiaoyao Liang. A scholar is included among the top collaborators of Xiaoyao Liang 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 Xiaoyao Liang. Xiaoyao Liang 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 | 0 | |
| 3 | 0 | |
| 4 | 5 | |
| 5 | 3 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 3 | |
| 9 | 31 | |
| 10 | 9 | |
| 11 | 31 | |
| 12 | 8 | |
| 13 | 16 | |
| 14 | 3 | |
| 15 | 4 | |
| 16 | 178 | |
| 17 | 18 | |
| 18 | R 6T SRAM 3T1D DRAM L1 D C C P V | 24 |
| 19 | The Importance of Deep Roots and Hydraulic Redistribution to Amazonian Rainforest Resilience and Response to Hydro-Climatic Variability: A Simulation Analysis | 1 |
| 20 | Process Variation Tolerant 3T1D-Based Cache Architecturesbreakdown → | 383 |
About Xiaoyao Liang
Xiaoyao Liang is a scholar working on Hardware and Architecture, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 135 papers that have together received 2.0k indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (41 papers), Low-power high-performance VLSI design (31 papers) and Advanced Memory and Neural Computing (29 papers). The work is most often cited by research in Hardware and Architecture (896 citations), Computer Networks and Communications (828 citations) and Electrical and Electronic Engineering (1.1k citations). Xiaoyao Liang has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Gu-Yeon Wei, David J. Brooks, David Brooks, R. Canal, Li Jiang, Naifeng Jing, Chao Li, Zhuoran Song, Minyi Guo and Yiran Chen. Their work appears in journals such as Nature Communications, Applied Physics Letters and IEEE Transactions on Medical Imaging.
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.