Ming Ling
Impact in
- Hardware and Architecture top 5%
- Parallel Computing and Optimization Techniques
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- Computational Drug Discovery Methods
Papers in
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- Parallel Computing and Optimization Techniques 30
- VLSI and Analog Circuit Testing 8
- Embedded Systems Design Techniques 7
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- Low-power high-performance VLSI design 14
- VLSI and FPGA Design Techniques 5
- Advanced Memory and Neural Computing 4
- Co-authors
- Shidi Tang (11 shared papers)Jiansheng Wu (5 shared papers)Haifeng Hu (4 shared papers)Longxing Shi (18 shared papers)Ruiqi Chen (8 shared papers)Jianping Pan (3 shared papers)Qinqin Huang (1 shared paper)Jun Peng (1 shared paper)
In The Last Decade
Ming Ling
51 papers receiving 436 citations
Peers
Comparison fields: 5 of 99
- Hardware and Architecture 107
- Computational Theory and Mathematics 84
- Computer Networks and Communications 99
- Electrical and Electronic Engineering 127
- Human-Computer Interaction 13
Countries citing papers authored by Ming Ling
This map shows the geographic impact of Ming Ling'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 Ming Ling with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Ling more than expected).
Fields of papers citing papers by Ming Ling
This network shows the impact of papers produced by Ming Ling. 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 Ming Ling. The network helps show where Ming Ling may publish in the future.
Co-authors
The 25 scholars most cited alongside Ming Ling, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 81 | |
| 2 | 2023 | 68 | |
| 3 | 2019 | 55 | |
| 4 | 2019 | 24 | |
| 5 | 2024 | 21 | |
| 6 | 2024 | 19 | |
| 7 | 2019 | 14 | |
| 8 | 2022 | 12 | |
| 9 | 2017 | 11 | |
| 10 | 2023 | 10 | |
| 11 | 2008 | 9 | |
| 12 | 2017 | 8 | |
| 13 | 2017 | 8 | |
| 14 | 2021 | 7 | |
| 15 | 2019 | 7 | |
| 16 | 2019 | 5 | |
| 17 | 2020 | 5 | |
| 18 | 2018 | 4 | |
| 19 | 2017 | 4 | |
| 20 | 2019 | 4 |
About Ming Ling
Ming Ling is a scholar working on Hardware and Architecture, Electrical and Electronic Engineering, Computer Networks and Communications, Computational Theory and Mathematics and Control and Systems Engineering, having authored 61 papers that have together received 446 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (30 papers), Advanced Data Storage Technologies (16 papers), Low-power high-performance VLSI design (14 papers), Interconnection Networks and Systems (13 papers), VLSI and Analog Circuit Testing (8 papers), Embedded Systems Design Techniques (7 papers), VLSI and FPGA Design Techniques (5 papers) and Advanced Memory and Neural Computing (4 papers). The work is most often cited by research in Hardware and Architecture (107 citations), Computational Theory and Mathematics (84 citations), Computer Networks and Communications (99 citations), Electrical and Electronic Engineering (127 citations) and Human-Computer Interaction (13 citations). Ming Ling has collaborated with scholars based in China, Belgium and Canada. Frequent co-authors include Shidi Tang, Jiansheng Wu, Haifeng Hu, Longxing Shi, Ruiqi Chen, Jianping Pan, Qinqin Huang, Jun Peng, Kaiyang Liu and Zhiwu Huang. Their work appears in journals such as IEEE Transactions on Very Large Scale Integration (VLSI) Systems, IEEE Access, Journal of Systems Architecture, ACM Transactions on Embedded Computing Systems and Ecological Informatics.
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.