Remco Chang

117 papers receiving 3.0k citations

Peers

Remco Chang
Comparison fields: 5 of 140
  • Computer Vision and Pattern Recognition 2.1k
  • Human-Computer Interaction 272
  • Signal Processing 423
  • Information Systems and Management 269
  • Computer Graphics and Computer-Aided Design 111
Replace Michael Sedlmair with:
Michael Sedlmair Germany
Robert Kosara United States
Alex Endert United States
Nathalie Henry Riche United States
Melanie Tory Canada
Georges Grinstein United States
Pierre Dragicevic France
Petra Isenberg France
Zhicheng Liu United States
Jonathan C. Roberts United Kingdom
Remco Chang relative to Michael Sedlmair Germany Michael Sedlmair's profile →
Citations per field
00.5×1.6×
Michael Sedlmair · 1×
Citations per year

Countries citing papers authored by Remco Chang

Since Specialization
Citations

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

Fields of papers citing papers by Remco Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 122 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009172
2 2009150
3 2014146
4 2012137
5 2016115
6 2014107
7 2009102
8 2007101
9 201699
10 200996
11 201492
12 201581
13 202076
14 201175
15 201874
16 201572
17 202071
18 201371
19 201160
20 201152

About Remco Chang

Remco Chang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Cognitive Neuroscience and Sociology and Political Science, having authored 122 papers that have together received 3.1k indexed citations. Recurring topics across this work include Data Visualization and Analytics (93 papers), Video Analysis and Summarization (19 papers), Advanced Text Analysis Techniques (16 papers), Data Management and Algorithms (14 papers), Data Analysis with R (10 papers), Multimedia Communication and Technology (8 papers), Scientific Computing and Data Management (7 papers) and Time Series Analysis and Forecasting (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.1k citations), Human-Computer Interaction (272 citations), Signal Processing (423 citations), Information Systems and Management (269 citations) and Computer Graphics and Computer-Aided Design (111 citations). Remco Chang has collaborated with scholars based in United States, Germany and China. Frequent co-authors include William Ribarsky, Lane Harrison, Caroline Ziemkiewicz, Alvitta Ottley, Leilani Battle, Michael Stonebraker, Dong Hyun Jeong, Wenwen Dou, Eli T. Brown and Evan M. Peck. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, IEEE Computer Graphics and Applications, Computer Graphics Forum, Information Visualization and ACM Transactions on Interactive Intelligent 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.

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