Jia-Chen Gu

829 citations
34 papers · 290 · h-index 9

Impact in

Papers in

Jia-Chen Gu

25 papers receiving 280 citations

Peers

Jia-Chen Gu
Comparison fields: 5 of 43
  • Artificial Intelligence 251
  • Human-Computer Interaction 21
  • Health Informatics 3
  • Information Systems 31
  • Computer Vision and Pattern Recognition 28
Replace Natalie B. Steinhauser with:
Natalie B. Steinhauser United States
Ben Eisner United States
Pascale Fung Hong Kong
Michael A. Hedderich Germany
Junji Tomita Japan
Masahiro Araki Japan
Cheongjae Lee South Korea
Jatin Sharma India
Yogarshi Vyas United States
Peter Poller Germany
Jia-Chen Gu relative to Natalie B. Steinhauser United States Natalie B. Steinhauser's profile →
Citations per field
00.5×5.5×
Natalie B. Steinhauser · 1×
Citations per year

Countries citing papers authored by Jia-Chen Gu

Since Specialization
Citations

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

Fields of papers citing papers by Jia-Chen Gu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jia-Chen Gu. 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 Jia-Chen Gu. The network helps show where Jia-Chen Gu may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202086
2 201939
3 201926
4 202122
5 202018
6 201917
7 202216
8 202111
9 202110
10 20208
11 20245
12 20215
13 20104
14 20243
15 20223
16 20193
17 20242
18 20222
19 20232
20 20142

About Jia-Chen Gu

Jia-Chen Gu is a scholar working on Artificial Intelligence, Information Systems, Electrical and Electronic Engineering, Molecular Biology and Computer Vision and Pattern Recognition, having authored 34 papers that have together received 290 indexed citations. Recurring topics across this work include Topic Modeling (21 papers), Natural Language Processing Techniques (16 papers), Speech and dialogue systems (10 papers), Mechanical Behavior of Composites (2 papers), Sentiment Analysis and Opinion Mining (2 papers), Music and Audio Processing (2 papers), Semantic Web and Ontologies (2 papers) and Video Analysis and Summarization (2 papers). The work is most often cited by research in Artificial Intelligence (251 citations), Human-Computer Interaction (21 citations), Health Informatics (3 citations), Information Systems (31 citations) and Computer Vision and Pattern Recognition (28 citations). Jia-Chen Gu has collaborated with scholars based in China, Canada and United Kingdom. Frequent co-authors include Zhen-Hua Ling, Quan Liu, Xiaodan Zhu, Quan Liu, Si Wei, Tianda Li, Chongyang Tao, Xiubo Geng, Zhigang Chen and Daxin Jiang. Their work appears in journals such as IEEE/ACM Transactions on Audio Speech and Language Processing, Journal of Alloys and Compounds, Journal of Manufacturing Processes, Computer Speech & Language and Geotechnical and Geological 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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