Keming Lu
Impact in
-
- Artificial Intelligence in Healthcare and Education
-
- Topic Modeling
- Speech and dialogue systems
Papers in
-
- Topic Modeling 4
- Domain Adaptation and Few-Shot Learning 1
- Speech and dialogue systems 1
- Natural Language Processing Techniques 1
-
- Biomedical Text Mining and Ontologies 3
- Co-authors
- Yucong Lin (4 shared papers)Sheng Yu (4 shared papers)Yunjie Yang (1 shared paper)Delin Hu (1 shared paper)Jingren Zhou (3 shared papers)Yingyun Yang (2 shared papers)Hongyi Yuan (4 shared papers)Muhao Chen (2 shared papers)
- Journals
- BMC Medical Informatics and Decision Making (2 papers)Journal of Biomedical Informatics (1 paper)Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) (1 paper)arXiv (Cornell University) (3 papers)PubMed (1 paper)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Keming Lu
15 papers receiving 191 citations
Peers
Comparison fields: 5 of 26
- Health Informatics 8
- Artificial Intelligence 55
- Genetics 15
- Computer Vision and Pattern Recognition 10
- Electrical and Electronic Engineering 22
Countries citing papers authored by Keming Lu
This map shows the geographic impact of Keming Lu'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 Keming Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Keming Lu more than expected).
Fields of papers citing papers by Keming Lu
This network shows the impact of papers produced by Keming Lu. 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 Keming Lu. The network helps show where Keming Lu may publish in the future.
Co-authors
The 25 scholars most cited alongside Keming Lu, 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 | 2020 | 41 | |
| 2 | 2024 | 31 | |
| 3 | 2019 | 24 | |
| 4 | 2022 | 22 | |
| 5 | 2023 | 20 | |
| 6 | 2023 | 15 | |
| 7 | 2024 | 12 | |
| 8 | 2024 | 9 | |
| 9 | 2023 | 5 | |
| 10 | 2023 | 5 | |
| 11 | 2023 | 4 | |
| 12 | 2020 | 3 | |
| 13 | 2024 | 2 | |
| 14 | 2025 | 2 | |
| 15 | 2023 | 1 | |
| 16 | 2024 | 0 | |
| 17 | 2025 | 0 |
About Keming Lu
Keming Lu is a scholar working on Artificial Intelligence, Molecular Biology, Electrical and Electronic Engineering, Nuclear Energy and Engineering and Waste Management and Disposal, having authored 17 papers that have together received 196 indexed citations. Recurring topics across this work include Topic Modeling (4 papers), Biomedical Text Mining and Ontologies (3 papers), Domain Adaptation and Few-Shot Learning (1 paper), Electrical and Bioimpedance Tomography (1 paper), Speech and dialogue systems (1 paper) and Natural Language Processing Techniques (1 paper). The work is most often cited by research in Health Informatics (8 citations), Artificial Intelligence (55 citations), Genetics (15 citations), Computer Vision and Pattern Recognition (10 citations) and Electrical and Electronic Engineering (22 citations). Keming Lu has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Yucong Lin, Sheng Yu, Yunjie Yang, Delin Hu, Jingren Zhou, Yingyun Yang, Hongyi Yuan, Muhao Chen, I-Hung Hsu and Tianxi Cai. Their work appears in journals such as BMC Medical Informatics and Decision Making, Journal of Biomedical Informatics, Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), arXiv (Cornell University) and PubMed.
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.