Sam Williamson

2.6k citations
68 papers · 1.8k indexed · h-index 21

Impact in

Papers in

Sam Williamson

65 papers receiving 1.7k citations

Peers

Sam Williamson
Comparison fields: 5 of 132
  • Energy Engineering and Power Technology 129
  • Cognitive Neuroscience 653
  • Pollution 141
  • Mechanics of Materials 295
  • Business and International Management 22
Replace Linyuan Wang with:
Linyuan Wang China
Takao Maeda Japan
Xiaowei Zhao United Kingdom
Kung‐Yen Lee Taiwan
Guillaume Crevecoeur Belgium
Dong Hwan Kim South Korea
Xin Ma China
Javier Romero Spain
Sam Williamson relative to Linyuan Wang China Linyuan Wang's profile →
Citations per field
00.5×10×20×29.5×
Linyuan Wang · 1×
Citations per year

Countries citing papers authored by Sam Williamson

Since Specialization
Citations

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

Fields of papers citing papers by Sam Williamson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20241
2 20228
3 20226
4 20201
5 20201
6 201721
7 20172
8 201614
9 201210
10 201141
11 199834
12 199646
13 19955
14 1992215
15 199020
16 198533
17 19709
18 19698
19 19687
20 19663

About Sam Williamson

Sam Williamson is a scholar working on Energy Engineering and Power Technology, Business and International Management, Pollution, Control and Systems Engineering and Cognitive Neuroscience, having authored 68 papers that have together received 1.8k indexed citations. Recurring topics across this work include Cavitation Phenomena in Pumps (11 papers), Energy and Environment Impacts (11 papers), Electric Motor Design and Analysis (9 papers), Microgrid Control and Optimization (9 papers), Smart Grid Energy Management (8 papers), Neural dynamics and brain function (7 papers), Hybrid Renewable Energy Systems (7 papers) and Water-Energy-Food Nexus Studies (6 papers). The work is most often cited by research in Energy Engineering and Power Technology (129 citations), Cognitive Neuroscience (653 citations), Pollution (141 citations), Mechanics of Materials (295 citations) and Business and International Management (22 citations). Sam Williamson has collaborated with scholars based in United Kingdom, United States and Brazil. Frequent co-authors include Lloyd Kaufman, J.D. Booker, Bernard H. Stark, Zhong‐Lin Lu, J.-Z. Wang, D. Brenner, N.G. Gençer, Paul Harper, Phil Mellor and Rafał Wróbel. Their work appears in journals such as Energy Sustainable Development, IEEE Transactions on Biomedical Engineering, Brain Topography, Science and Energies.

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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