Soojin Park

658 citations
48 papers · 346 indexed · h-index 8
Topics
Advanced Software Engineering Methodologies (14 papers)Software System Performance and Reliability (9 papers)Software Engineering Techniques and Practices (9 papers)
Partner nations
South KoreaUnited States

In The Last Decade

Soojin Park

37 papers receiving 332 citations

Peers

Soojin Park
Comparison fields: 5 of 71
  • Cognitive Neuroscience 183
  • Information Systems 72
  • Computer Vision and Pattern Recognition 71
  • Artificial Intelligence 46
  • Computer Networks and Communications 42
Replace Zohreh Sharafi with:
Zohreh Sharafi Canada
Mingyu Park South Korea
Julie Porteous United Kingdom
Anders Bouwer Netherlands
Mohamed Kholief Egypt
Piero Mussio Italy
Leonidas Deligiannidis United States
Chris Roast United Kingdom
Jinlong Wang China
Miguel A. Teruel Spain
Soojin Park relative to Zohreh Sharafi Canada Zohreh Sharafi's profile →
Citations per field
00.5×3.5×
Zohreh Sharafi · 1×
Citations per year

Countries citing papers authored by Soojin Park

Since Specialization
Citations

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

Fields of papers citing papers by Soojin Park

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Soojin Park

This figure shows the co-authorship network connecting the top 25 collaborators of Soojin Park. A scholar is included among the top collaborators of Soojin Park based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Soojin Park. Soojin Park is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 2
2 0
3 7
4 1
5 1
6 2
7 3
8 2
9 11
10 1
11 1
12 1
13 2
14 1
15
WanderingData: Data Visualization Techniques for Neurocritical Intensive Care.
1
16 10
17
A Gray-Box based Software Requirements Specification Method for Embedded Systems
1
18 0
19
A Study on the Interface Design of Touch Screen Newspaper in Public Space
1
20
A Process Tailoring Method Based on Artificial Neural Network
1

About Soojin Park

Soojin Park is a scholar working on Software, Information Systems and Leadership and Management, having authored 48 papers that have together received 346 indexed citations. Recurring topics across this work include Advanced Software Engineering Methodologies (14 papers), Software System Performance and Reliability (9 papers) and Software Engineering Techniques and Practices (9 papers). The work is most often cited by research in Cognitive Neuroscience (183 citations), Software (29 citations) and Computer Vision and Pattern Recognition (71 citations). Soojin Park has collaborated with scholars based in South Korea and United States. Frequent co-authors include Aude Oliva, Timothy F. Brady, Michelle R. Greene, Vijayan Sugumaran, Sungyong Park, Sooyong Park, JaeSeung Song, Shraddha Mainali, Sarah Furlong and Jaechang Lim. Their work appears in journals such as Journal of Neuroscience, Expert Systems with Applications and Sensors.

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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