Luan Tran
Impact in
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- Mobile Crowdsensing and Crowdsourcing
- Transportation top 5%
- Human Mobility and Location-Based Analysis
Papers in
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- Anomaly Detection Techniques and Applications 4
- Machine Learning in Healthcare 2
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- Network Security and Intrusion Detection 4
- Co-authors
- Cyrus Shahabi (11 shared papers)Liyue Fan (5 shared papers)Hien To (2 shared papers)Lindsay Aitkin (1 shared paper)Josef Syka (1 shared paper)Min Mun (2 shared papers)Allen R. Kunselman (2 shared papers)Luciano Nocera (3 shared papers)
- Journals
- Proceedings of the VLDB Endowment (3 papers)Statistics in Medicine (2 papers)Experimental Brain Research (1 paper)JMIR mhealth and uhealth (1 paper)ACM Transactions on Intelligent Systems and Technology (1 paper)
- Partner nations
- United StatesVietnamSouth Korea
In The Last Decade
Luan Tran
17 papers receiving 480 citations
Peers
Comparison fields: 5 of 86
- Computer Science Applications 129
- Transportation 79
- Sensory Systems 33
- Signal Processing 67
- Developmental Biology 13
Countries citing papers authored by Luan Tran
This map shows the geographic impact of Luan Tran'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 Luan Tran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luan Tran more than expected).
Fields of papers citing papers by Luan Tran
This network shows the impact of papers produced by Luan Tran. 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 Luan Tran. The network helps show where Luan Tran may publish in the future.
Co-authors
The 17 scholars most cited alongside Luan Tran, 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 | 2016 | 86 | |
| 2 | 2016 | 83 | |
| 3 | 1994 | 64 | |
| 4 | 2018 | 55 | |
| 5 | 2020 | 41 | |
| 6 | 1999 | 39 | |
| 7 | 2020 | 32 | |
| 8 | 2022 | 23 | |
| 9 | MultiFusionNet: Atrial Fibrillation Detection With Deep Neural Networks. | 2020 | 19 |
| 10 | 2020 | 14 | |
| 11 | 2019 | 9 | |
| 12 | 2023 | 8 | |
| 13 | 2019 | 7 | |
| 14 | 2019 | 7 | |
| 15 | 2019 | 4 | |
| 16 | 1999 | 1 | |
| 17 | 2021 | 1 |
About Luan Tran
Luan Tran is a scholar working on Artificial Intelligence, Computer Networks and Communications, Management Science and Operations Research, Civil and Structural Engineering and Cardiology and Cardiovascular Medicine, having authored 17 papers that have together received 493 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (4 papers), Network Security and Intrusion Detection (4 papers), Machine Learning in Healthcare (2 papers), Statistical Methods and Bayesian Inference (2 papers), Optimal Experimental Design Methods (2 papers), Sepsis Diagnosis and Treatment (2 papers), Water Systems and Optimization (2 papers) and Indoor and Outdoor Localization Technologies (2 papers). The work is most often cited by research in Computer Science Applications (129 citations), Transportation (79 citations), Sensory Systems (33 citations), Signal Processing (67 citations) and Developmental Biology (13 citations). Luan Tran has collaborated with scholars based in United States, Vietnam and South Korea. Frequent co-authors include Cyrus Shahabi, Liyue Fan, Hien To, Lindsay Aitkin, Josef Syka, Min Mun, Allen R. Kunselman, Luciano Nocera, Yanfang Li and Li Xiong. Their work appears in journals such as Proceedings of the VLDB Endowment, Statistics in Medicine, Experimental Brain Research, JMIR mhealth and uhealth and ACM Transactions on Intelligent Systems and Technology.
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.