Fábio Miranda
Impact in
- Transportation top 5%
- Human Mobility and Location-Based Analysis
- Urban Transport and Accessibility
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- Data Visualization and Analytics
Papers in
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- Computer Graphics and Visualization Techniques 5
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- Data Visualization and Analytics 19
- Co-authors
- Claudio SilvaMarcos LageHarish DoraiswamyJianzhe LinKai ZhaoBruno GonçalvesJunyan YangZhicheng Liu
- Journals
- IEEE Transactions on Visualization and Computer Graphics (8 papers)Computer Graphics Forum (2 papers)Computers & Graphics (2 papers)The Visual Computer (1 paper)Computers Environment and Urban Systems (1 paper)
- Partner nations
- United StatesBrazilAustria
In The Last Decade
Fábio Miranda
33 papers receiving 395 citations
Peers
Comparison fields: 5 of 73
- Transportation 143
- Computer Vision and Pattern Recognition 173
- Geography, Planning and Development 40
- Building and Construction 86
- Signal Processing 64
Countries citing papers authored by Fábio Miranda
This map shows the geographic impact of Fábio Miranda'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 Fábio Miranda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fábio Miranda more than expected).
Fields of papers citing papers by Fábio Miranda
This network shows the impact of papers produced by Fábio Miranda. 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 Fábio Miranda. The network helps show where Fábio Miranda may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Fábio Miranda, 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 | 2025 | 1 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 3 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 8 | |
| 6 | 2023 | 26 | |
| 7 | 2023 | 0 | |
| 8 | 2023 | 0 | |
| 9 | 2023 | 5 | |
| 10 | 2022 | 10 | |
| 11 | 2022 | 13 | |
| 12 | 2022 | 36 | |
| 13 | 2021 | 1 | |
| 14 | 2021 | 20 | |
| 15 | 2021 | 5 | |
| 16 | 2020 | 4 | |
| 17 | 2020 | 2 | |
| 18 | 2018 | 29 | |
| 19 | 2018 | 20 | |
| 20 | 2012 | 4 |
About Fábio Miranda
Fábio Miranda is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition, Transportation, Geography, Planning and Development and Signal Processing, having authored 35 papers that have together received 404 indexed citations. Recurring topics across this work include Data Visualization and Analytics (19 papers), Data Management and Algorithms (6 papers), Computer Graphics and Visualization Techniques (5 papers), Human Mobility and Location-Based Analysis (5 papers), Remote Sensing and LiDAR Applications (4 papers), Impact of Light on Environment and Health (3 papers), Urban Transport and Accessibility (3 papers) and Geographic Information Systems Studies (3 papers). The work is most often cited by research in Transportation (143 citations), Computer Vision and Pattern Recognition (173 citations), Geography, Planning and Development (40 citations), Building and Construction (86 citations) and Signal Processing (64 citations). Fábio Miranda has collaborated with scholars based in United States, Brazil and Austria. Frequent co-authors include Claudio Silva, Marcos Lage, Harish Doraiswamy, Jianzhe Lin, Kai Zhao, Bruno Gonçalves, Junyan Yang, Zhicheng Liu, James T. Klosowski and Lauro Lins. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Computer Graphics Forum, Computers & Graphics, The Visual Computer and Computers Environment and Urban Systems.
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.