Michael Burch

4.3k citations
184 papers · 3.3k · h-index 30

Impact in

Papers in

Michael Burch

167 papers receiving 3.1k citations

Peers

Michael Burch
Comparison fields: 5 of 124
  • Human-Computer Interaction 867
  • Computer Vision and Pattern Recognition 2.5k
  • Statistical and Nonlinear Physics 593
  • Signal Processing 490
  • Geography, Planning and Development 222
Replace Nathalie Henry Riche with:
Nathalie Henry Riche United States
Benjamin Bach United Kingdom
Pierre Dragicevic France
Tim Dwyer Australia
Petra Isenberg France
Michael Sedlmair Germany
Remco Chang United States
Niklas Elmqvist United States
Alex Endert United States
Kim Marriott Australia
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Citations per field
00.5×1.5×1.9×
Nathalie Henry Riche · 1×
Citations per year

Countries citing papers authored by Michael Burch

Since Specialization
Citations

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

Fields of papers citing papers by Michael Burch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 184 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016234
2 2017203
3 2014171
4 2012167
5 2014154
6 2011135
7 2011113
8 201576
9 201673
10 200866
11 200964
12 201463
13 200862
14 201561
15 201360
16 202257
17 201351
18 200949
19 201348
20 200539

About Michael Burch

Michael Burch is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction, Signal Processing, Artificial Intelligence and Statistical and Nonlinear Physics, having authored 184 papers that have together received 3.3k indexed citations. Recurring topics across this work include Data Visualization and Analytics (157 papers), Gaze Tracking and Assistive Technology (48 papers), Data Management and Algorithms (35 papers), Video Analysis and Summarization (26 papers), Advanced Text Analysis Techniques (26 papers), Complex Network Analysis Techniques (24 papers), Multimedia Communication and Technology (19 papers) and Geographic Information Systems Studies (17 papers). The work is most often cited by research in Human-Computer Interaction (867 citations), Computer Vision and Pattern Recognition (2.5k citations), Statistical and Nonlinear Physics (593 citations), Signal Processing (490 citations) and Geography, Planning and Development (222 citations). Michael Burch has collaborated with scholars based in Germany, Netherlands and Switzerland. Frequent co-authors include Daniel Weiskopf, Stephan Diehl, Fabian Beck, Kuno Kurzhals, Tanja Blascheck, Michael Raschke, Thomas Ertl, Gennady Andrienko, Natalia Andrienko and Corinna Vehlow. Their work appears in journals such as Computer Graphics Forum, IEEE Transactions on Visualization and Computer Graphics, Information Visualization, Lecture notes in computer science 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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