Thomas Suesse

1.1k citations
45 papers · 439 · h-index 11

Impact in

Papers in

Thomas Suesse

43 papers receiving 420 citations

Peers

Thomas Suesse
Comparison fields: 5 of 119
  • Speech and Hearing 56
  • Statistics and Probability 63
  • Health, Toxicology and Mutagenesis 88
  • Architecture 6
  • Health Informatics 5
Replace C. D. Kershaw with:
C. D. Kershaw United Kingdom
Mohd Bakri Adam Malaysia
Jari Metsämuuronen Finland
Chloe Perkins United Kingdom
Carla Moreira Portugal
Ben Derrick United Kingdom
Yeonseung Chung South Korea
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Suril Mehta United States
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Citations per field
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C. D. Kershaw · 1×
Citations per year

Countries citing papers authored by Thomas Suesse

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Suesse

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021115
2 202067
3 200819
4 201819
5 200418
6 202017
7 202115
8 202215
9 201713
10 202112
11 202210
12 202310
13 201710
14 20177
15 20176
16 20086
17
Relationship between learning in the engineering laboratory and student evaluations
20156
18 20175
19 20135
20 20135

About Thomas Suesse

Thomas Suesse is a scholar working on Statistics and Probability, Economics and Econometrics, Media Technology, Sociology and Political Science and Artificial Intelligence, having authored 45 papers that have together received 439 indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (11 papers), Spatial and Panel Data Analysis (9 papers), Economic and Environmental Valuation (7 papers), Experimental Learning in Engineering (7 papers), Statistical Methods and Inference (5 papers), Engineering Education and Curriculum Development (5 papers), Bayesian Methods and Mixture Models (4 papers) and Urban Green Space and Health (3 papers). The work is most often cited by research in Speech and Hearing (56 citations), Statistics and Probability (63 citations), Health, Toxicology and Mutagenesis (88 citations), Architecture (6 citations) and Health Informatics (5 citations). Thomas Suesse has collaborated with scholars based in Australia, Germany and New Zealand. Frequent co-authors include Bin Jalaludin, Thomas Astell‐Burt, Xiaoqi Feng, Johan Barthélemy, Ivy Liu, Sasha Nikolic, Anthony D. Okely, Rok Blagus, Mirko Brandes and Viktória Kovács. Their work appears in journals such as European Journal of Engineering Education, Computational Statistics & Data Analysis, Biometrical Journal, Spatial Statistics and Clinical Neurophysiology.

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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