Remco Chang

4.8k citations
124 papers · 3.1k indexed · h-index 33

Impact in

Papers in

Remco Chang

115 papers receiving 2.9k citations

Peers

Remco Chang
Comparison fields: 5 of 151
  • Computer Vision and Pattern Recognition 2.1k
  • Human-Computer Interaction 264
  • Signal Processing 421
  • Information Systems and Management 269
  • Computer Graphics and Computer-Aided Design 107
Replace Michael Sedlmair with:
Michael Sedlmair Germany
Robert Kosara United States
Nathalie Henry Riche United States
Christopher Collins Canada
Melanie Tory Canada
Georges Grinstein United States
Pierre Dragicevic France
Jonathan C. Roberts United Kingdom
Petra Isenberg France
Zhicheng Liu United States
Remco Chang relative to Michael Sedlmair Germany Michael Sedlmair's profile →
Citations per field
00.5×3.5×
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-authorship network

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
#Work
1 20250
2 20242
3 20241
4 20240
5 202313
6 20231
7 20231
8 20237
9 202062
10 20202
11 20205
12
NNCubes: Learned Structures for Visual Data Exploration.
20183
13 20189
14 20142
15 201242
16 201235
17 200995
18 2009100
19 200814
20 200840

About Remco Chang

Remco Chang is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Computational Mathematics, Human-Computer Interaction and Computer Graphics and Computer-Aided Design, having authored 124 papers that have together received 3.1k indexed citations. Recurring topics across this work include Data Visualization and Analytics (92 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 (264 citations), Signal Processing (421 citations), Information Systems and Management (269 citations) and Computer Graphics and Computer-Aided Design (107 citations). Remco Chang has collaborated with scholars based in United States, China and Germany. Frequent co-authors include William Ribarsky, Lane Harrison, Caroline Ziemkiewicz, Alvitta Ottley, Leilani Battle, Michael Stonebraker, Wenwen Dou, Dong Hyun Jeong, 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 Chemistry of Materials.

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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