Tommy Dang

1.5k citations
91 papers · 940 · h-index 19

Impact in

Papers in

Tommy Dang

86 papers receiving 899 citations

Peers

Tommy Dang
Comparison fields: 5 of 115
  • Computer Vision and Pattern Recognition 533
  • Signal Processing 161
  • Human-Computer Interaction 72
  • Artificial Intelligence 292
  • Information Systems and Management 45
Replace Huub van de Wetering with:
Huub van de Wetering Netherlands
Jibonananda Sanyal United States
Maria Riveiro Sweden
Harald Piringer Austria
Jiawei Zhang China
Rafael M. Martins Sweden
Harish Doraiswamy United States
Ronald A. Peterson United States
Guangyu Zhu China
Wanggen Wan China
Tommy Dang relative to Huub van de Wetering Netherlands Huub van de Wetering's profile →
Citations per field
00.5×3.4×
Huub van de Wetering · 1×
Citations per year

Countries citing papers authored by Tommy Dang

Since Specialization
Citations

This map shows the geographic impact of Tommy Dang'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 Tommy Dang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tommy Dang more than expected).

Fields of papers citing papers by Tommy Dang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tommy Dang. 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 Tommy Dang. The network helps show where Tommy Dang may publish in the future.

Co-authors

The 25 scholars most cited alongside Tommy Dang, 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 Tommy Dang Line = papers co-authored together Tommy Dang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 91 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202095
2 201055
3 201451
4 201341
5 201637
6 201736
7 200330
8 201930
9 202128
10 201226
11 201826
12 201524
13 201423
14 201123
15 201920
16 201820
17 201919
18 199419
19 201918
20 201916

About Tommy Dang

Tommy Dang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Statistical and Nonlinear Physics and Molecular Biology, having authored 91 papers that have together received 940 indexed citations. Recurring topics across this work include Data Visualization and Analytics (47 papers), Time Series Analysis and Forecasting (18 papers), Complex Network Analysis Techniques (14 papers), Anomaly Detection Techniques and Applications (10 papers), Advanced Text Analysis Techniques (8 papers), Virtual Reality Applications and Impacts (6 papers), Soil Geostatistics and Mapping (5 papers) and Video Analysis and Summarization (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (533 citations), Signal Processing (161 citations), Human-Computer Interaction (72 citations), Artificial Intelligence (292 citations) and Information Systems and Management (45 citations). Tommy Dang has collaborated with scholars based in United States, Vietnam and Canada. Frequent co-authors include Vung Pham, Leland Wilkinson, Vinh T. Nguyen, Anushka Anand, Chau Pham, Angus G. Forbes, Kwanghee Jung, David C. Weindorf, Paul Murray and Rebecca Hite. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Child s Nervous System, World Neurosurgery, Electronics and Computers and Electronics in Agriculture.

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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