Nivan Ferreira

1.2k citations
27 papers · 769 indexed · 1 hit paper · h-index 12
Topics
Data Visualization and Analytics (20 papers)Data Management and Algorithms (9 papers)Human Mobility and Location-Based Analysis (8 papers)

In The Last Decade

Nivan Ferreira

23 papers receiving 739 citations

Hit Papers

Visual Exploration of Big Spatio-Temporal Urban Data: A S...20132026201720212013100200300

Peers

Nivan Ferreira
Comparison fields: 5 of 86
  • Computer Vision and Pattern Recognition 419
  • Transportation 282
  • Signal Processing 256
  • Building and Construction 136
  • Artificial Intelligence 95
Replace Jorge Poco with:
Jorge Poco Brazil
Min Lü China
Harish Doraiswamy United States
Adam C. Winstanley Ireland
Aidan Slingsby United Kingdom
Bart Kuijpers Belgium
Hansi Senaratne Germany
Doantam Phan United States
Jizhou Huang China
Maria Luisa Damiani Italy
Nivan Ferreira relative to Jorge Poco Brazil Jorge Poco's profile →
Citations per field
00.5×1.5×
Jorge Poco · 1×
Citations per year

Countries citing papers authored by Nivan Ferreira

Since Specialization
Citations

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

Fields of papers citing papers by Nivan Ferreira

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nivan Ferreira

This figure shows the co-authorship network connecting the top 25 collaborators of Nivan Ferreira. A scholar is included among the top collaborators of Nivan Ferreira based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Nivan Ferreira. Nivan Ferreira is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 1
3 1
4 8
5 2
6 1
7 0
8 1
9 2
10 20
11 27
12 13
13 10
14 40
15 43
16 17
17
Riding from Urban Data to Insight Using New York City Taxis
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18 51
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Visual Exploration of Big Spatio-Temporal Urban Data: A Study of New York City Taxi Tripsbreakdown →
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20 49

About Nivan Ferreira

Nivan Ferreira is a scholar working on Transportation, Geography, Planning and Development and Computer Vision and Pattern Recognition, having authored 27 papers that have together received 769 indexed citations. Recurring topics across this work include Data Visualization and Analytics (20 papers), Data Management and Algorithms (9 papers) and Human Mobility and Location-Based Analysis (8 papers). The work is most often cited by research in Transportation (282 citations), Signal Processing (256 citations) and Computer Vision and Pattern Recognition (419 citations). Nivan Ferreira has collaborated with scholars based in Brazil, United States and Austria. Frequent co-authors include Claudio Silva, Juliana Freire, Huy T. Vo, Jorge Poco, Carlos Scheidegger, Harish Doraiswamy, James T. Klosowski, Marcos Lage, Theodoros Damoulas and Z. Wang. Their work appears in journals such as ACM Transactions on Graphics, Applied Soft Computing and Sustainable Cities and Society.

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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