Simon M. Su

1.3k citations
64 papers · 905 · h-index 13

Impact in

Papers in

Simon M. Su

59 papers receiving 867 citations

Peers

Simon M. Su
Comparison fields: 5 of 98
  • Automotive Engineering 386
  • Computer Vision and Pattern Recognition 389
  • Human-Computer Interaction 96
  • Computational Mathematics 9
  • Computer Graphics and Computer-Aided Design 52
Replace Masao Sakauchi with:
Masao Sakauchi Japan
Bo Dai China
Xu Xie China
Miguel Ángel Bautista Spain
Zheng Wu China
Chih‐Hsien Hsia Taiwan
Zhengyuan Yang United States
Heedong Ko South Korea
Yuliang Liu China
Siyuan Qi United States
Simon M. Su relative to Masao Sakauchi Japan Masao Sakauchi's profile →
Citations per field
00.5×10×20×33.7×
Masao Sakauchi · 1×
Citations per year

Countries citing papers authored by Simon M. Su

Since Specialization
Citations

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

Fields of papers citing papers by Simon M. Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Simon M. Su. 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 Simon M. Su. The network helps show where Simon M. Su may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 64 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019295
2 2021142
3 202363
4 201939
5 202031
6 202031
7 202227
8 202323
9 201618
10 202117
11 200717
12 202214
13 201814
14 201912
15 201111
16 201611
17 20139
18 20248
19 20227
20
Force reflection and manipulation for a VR-based telerobotic system
20007

About Simon M. Su

Simon M. Su is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction, Computer Graphics and Computer-Aided Design, Automotive Engineering and Artificial Intelligence, having authored 64 papers that have together received 905 indexed citations. Recurring topics across this work include Data Visualization and Analytics (17 papers), Virtual Reality Applications and Impacts (14 papers), Computer Graphics and Visualization Techniques (11 papers), Augmented Reality Applications (11 papers), Autonomous Vehicle Technology and Safety (7 papers), Interactive and Immersive Displays (5 papers), Human-Automation Interaction and Safety (5 papers) and Scientific Computing and Data Management (4 papers). The work is most often cited by research in Automotive Engineering (386 citations), Computer Vision and Pattern Recognition (389 citations), Human-Computer Interaction (96 citations), Computational Mathematics (9 citations) and Computer Graphics and Computer-Aided Design (52 citations). Simon M. Su has collaborated with scholars based in United States, Canada and Myanmar. Frequent co-authors include Raquel Urtasun, Sergio Casas, Wenjie Luo, Abbas Sadat, Bin Yang, Wenyuan Zeng, Ang Li, Kelvin Wong, Sue E. Kase and William R. Sherman. Their work appears in journals such as Atomization and Sprays, ACS Medicinal Chemistry Letters, IEEE Computer Graphics and Applications, Computing in Science & Engineering and Lecture notes in computer science.

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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