Ling Huang
- Computer Networks and Communications top 0.2%
- Network Security and Intrusion Detection 13
- Software System Performance and Reliability 9
- Artificial Intelligence top 0.2%
- Advanced Graph Neural Networks 17
- Anomaly Detection Techniques and Applications 14
- Computational Mathematics top 2%
- Software top 1%
- Signal Processing top 0.5%
-
- Recommender Systems and Techniques 20
-
- Complex Network Analysis Techniques 20
-
- Face and Expression Recognition 13
- Advanced Image and Video Retrieval Techniques 11
- Co-authors
- Anthony D. JosephMichael I. JordanChang‐Dong WangWei XuDavid A. PattersonArmando FoxBenjamin I. P. RubinsteinJohn Kubiatowicz
- Journals
- SHILAP Revista de lepidopterología (1 paper)Scientific Reports (1 paper)Environmental Pollution (1 paper)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Ling Huang
130 papers receiving 6.0k citations
Hit Papers
Peers
Comparison fields: 5 of 141
- Computer Networks and Communications 3.0k
- Artificial Intelligence 3.1k
- Computational Mathematics 56
- Software 307
- Signal Processing 803
Countries citing papers authored by Ling Huang
This map shows the geographic impact of Ling Huang'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 Ling Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ling Huang more than expected).
Fields of papers citing papers by Ling Huang
This network shows the impact of papers produced by Ling Huang. 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 Ling Huang. The network helps show where Ling Huang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ling Huang, 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 | 2023 | 9 | |
| 2 | 2022 | 13 | |
| 3 | 2022 | 5 | |
| 4 | 2022 | 2 | |
| 5 | 2021 | 24 | |
| 6 | 2021 | 42 | |
| 7 | 2021 | 15 | |
| 8 | 2020 | 43 | |
| 9 | 2020 | 38 | |
| 10 | 2020 | 41 | |
| 11 | 2020 | 11 | |
| 12 | 2020 | 42 | |
| 13 | 2019 | 4 | |
| 14 | 2019 | 31 | |
| 15 | 2019 | 46 | |
| 16 | 2019 | 31 | |
| 17 | 2019 | 32 | |
| 18 | 2019 | 60 | |
| 19 | 2018 | 92 | |
| 20 | Mining console logs for large-scale system problem detection | 2008 | 82 |
About Ling Huang
Ling Huang is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Information Systems, having authored 136 papers that have together received 6.3k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (20 papers), Complex Network Analysis Techniques (20 papers), Advanced Graph Neural Networks (17 papers), Anomaly Detection Techniques and Applications (14 papers), Network Security and Intrusion Detection (13 papers), Face and Expression Recognition (13 papers), Advanced Image and Video Retrieval Techniques (11 papers) and Software System Performance and Reliability (9 papers). The work is most often cited by research in Computer Networks and Communications (3.0k citations), Artificial Intelligence (3.1k citations) and Computational Mathematics (56 citations). Ling Huang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Anthony D. Joseph, Michael I. Jordan, Chang‐Dong Wang, Wei Xu, David A. Patterson, Armando Fox, Benjamin I. P. Rubinstein, John Kubiatowicz, J. D. Tygar and Jeremy Stribling. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and Environmental Pollution.
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.