Robert Pienta
Impact in
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- Data Visualization and Analytics
- Graph Theory and Algorithms
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- Complex Network Analysis Techniques
Papers in
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- Data Visualization and Analytics 6
- Graph Theory and Algorithms 4
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- Complex Network Analysis Techniques 4
- Co-authors
- Duen Horng ChauAcar TamersoyMinsuk KahngHanghang TongJames AbelloAlex EndertShamkant B. NavatheFred Hohman
- Journals
- IEEE Transactions on Visualization and Computer Graphics (1 paper)View (1 paper)PubMed (4 papers)SMARTech Repository (Georgia Institute of Technology) (1 paper)
- Partner nations
- United StatesNetherlands
In The Last Decade
Robert Pienta
11 papers receiving 185 citations
Peers
Comparison fields: 5 of 36
- Computer Vision and Pattern Recognition 119
- Statistical and Nonlinear Physics 65
- Signal Processing 27
- Artificial Intelligence 76
- Information Systems and Management 15
Countries citing papers authored by Robert Pienta
This map shows the geographic impact of Robert Pienta'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 Robert Pienta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert Pienta more than expected).
Fields of papers citing papers by Robert Pienta
This network shows the impact of papers produced by Robert Pienta. 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 Robert Pienta. The network helps show where Robert Pienta may publish in the future.
Co-authorship network
The 18 scholars most cited alongside Robert Pienta, 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 | 2017 | 20 | |
| 2 | 2017 | 30 | |
| 3 | 2016 | 11 | |
| 4 | 2016 | 4 | |
| 5 | 2016 | 24 | |
| 6 | 2015 | 6 | |
| 7 | 2015 | 50 | |
| 8 | 2015 | 7 | |
| 9 | 2014 | 4 | |
| 10 | 2014 | 24 | |
| 11 | Mage: Expressive Pattern Matching in Richly-Attributed Graphs | 2013 | 0 |
| 12 | 2013 | 11 |
About Robert Pienta
Robert Pienta is a scholar working on Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Signal Processing, Geography, Planning and Development and Artificial Intelligence, having authored 12 papers that have together received 191 indexed citations. Recurring topics across this work include Data Visualization and Analytics (6 papers), Graph Theory and Algorithms (4 papers), Complex Network Analysis Techniques (4 papers), Advanced Graph Neural Networks (3 papers), Cellular Automata and Applications (1 paper), Spam and Phishing Detection (1 paper), Geographic Information Systems Studies (1 paper) and Cloud Computing and Resource Management (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (119 citations), Statistical and Nonlinear Physics (65 citations), Signal Processing (27 citations), Artificial Intelligence (76 citations) and Information Systems and Management (15 citations). Robert Pienta has collaborated with scholars based in United States and Netherlands. Frequent co-authors include Duen Horng Chau, Acar Tamersoy, Minsuk Kahng, Hanghang Tong, James Abello, Alex Endert, Shamkant B. Navathe, Fred Hohman, Richard M. Fujimoto and Chris Gates. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, View, PubMed and SMARTech Repository (Georgia Institute of 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.