Luan Tran

17 papers receiving 465 citations

Peers

Luan Tran
Comparison fields: 5 of 87
  • Computer Science Applications 127
  • Transportation 79
  • Sensory Systems 34
  • Developmental Biology 14
  • Signal Processing 67
Replace Vigneshwaran Subbaraju with:
Vigneshwaran Subbaraju Singapore
Taiwoo Park South Korea
Alessandro Montanari United Kingdom
Danny Wyatt United States
Sougata Sen United States
Nicky Kern Switzerland
Gabriele Civitarese Italy
Futoshi Naya Japan
Elena Vildjiounaite Finland
Luan Tran relative to Vigneshwaran Subbaraju Singapore Vigneshwaran Subbaraju's profile →
Citations per field
00.5×5.7×
Vigneshwaran Subbaraju · 1×
Citations per year

Countries citing papers authored by Luan Tran

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Luan Tran Line = papers co-authored together Luan Tran links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 201683
2 201682
3 199464
4 201854
5 199939
6 202039
7 202031
8 202222
9
MultiFusionNet: Atrial Fibrillation Detection With Deep Neural Networks.
202018
10 202014
11 20199
12 20197
13 20197
14 20236
15 20194
16 19991
17 20211

About Luan Tran

Luan Tran is a scholar working on Artificial Intelligence, Computer Networks and Communications, Clinical Psychology, Management Science and Operations Research and Civil and Structural Engineering, having authored 17 papers that have together received 481 indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (4 papers), Anomaly Detection Techniques and Applications (4 papers), Optimal Experimental Design Methods (2 papers), Statistical Methods and Bayesian Inference (2 papers), Mindfulness and Compassion Interventions (2 papers), Water Systems and Optimization (2 papers), Mobile Crowdsensing and Crowdsourcing (2 papers) and Data Stream Mining Techniques (2 papers). The work is most often cited by research in Computer Science Applications (127 citations), Transportation (79 citations), Sensory Systems (34 citations), Developmental Biology (14 citations) and Signal Processing (67 citations). Luan Tran has collaborated with scholars based in United States, Vietnam and Australia. Frequent co-authors include Cyrus Shahabi, Liyue Fan, Hien To, Lindsay Aitkin, Josef Syka, Min Mun, Allen R. Kunselman, Luciano Nocera, Li Xiong and Yanfang Li. Their work appears in journals such as Proceedings of the VLDB Endowment, Statistics in Medicine, JMIR mhealth and uhealth, Experimental Brain Research 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.

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