Jorge Poco

1.5k citations
44 papers · 944 indexed · 1 hit paper · h-index 13

Jorge Poco

37 papers receiving 912 citations

Hit Papers

Visual Exploration of Big Spatio-Temporal Urban Data: A S...3692013202620172021100200300

Peers

Jorge Poco
Comparison fields: 5 of 89
  • Transportation 237
  • Computer Vision and Pattern Recognition 595
  • Signal Processing 206
  • Computer Graphics and Computer-Aided Design 44
  • Geography, Planning and Development 66
Replace Nivan Ferreira with:
Nivan Ferreira Brazil
Harish Doraiswamy United States
Aidan Slingsby United Kingdom
Florian Mansmann Germany
Çağatay Turkay United Kingdom
Halldór Janetzko Germany
Mikael Jern Sweden
Jiazhi Xia China
Zhiguang Zhou China
Jie Liang China
Jorge Poco relative to Nivan Ferreira Brazil Nivan Ferreira's profile →
Citations per field
00.5×1.5×2.1×
Nivan Ferreira · 1×
Citations per year

Countries citing papers authored by Jorge Poco

Since Specialization
Citations

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

Fields of papers citing papers by Jorge Poco

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20250
3 20251
4 20250
5 20250
6 20241
7 20240
8 20240
9 20233
10 20231
11 20224
12 20225
13 20216
14 20218
15 201927
16
Riding from Urban Data to Insight Using New York City Taxis
20141
17 201423
18
Global net land carbon sink: Results from the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP)
20130
19
Visual Exploration of Big Spatio-Temporal Urban Data: A Study of New York City Taxi Tripsbreakdown →
2013369
20 201323

About Jorge Poco

Jorge Poco is a scholar working on Ecological Modeling, Computer Vision and Pattern Recognition and Transportation, having authored 44 papers that have together received 944 indexed citations. Recurring topics across this work include Data Visualization and Analytics (16 papers), Data Management and Algorithms (8 papers), Human Mobility and Location-Based Analysis (6 papers), Video Analysis and Summarization (5 papers), Species Distribution and Climate Change (5 papers), Image Retrieval and Classification Techniques (5 papers), Online Learning and Analytics (4 papers) and Impact of Light on Environment and Health (3 papers). The work is most often cited by research in Transportation (237 citations), Computer Vision and Pattern Recognition (595 citations) and Signal Processing (206 citations). Jorge Poco has collaborated with scholars based in Brazil, United States and Peru. Frequent co-authors include Claudio Silva, Jeffrey Heer, Huy T. Vo, Juliana Freire, Nivan Ferreira, Aritra Dasgupta, Luís Gustavo Nonato, Rosane Minghim, Yaxing Wei and Fernando V. Paulovich. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Computer Graphics Forum, Computers & Graphics, Data Mining and Knowledge Discovery and Computing in Science & Engineering.

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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