I‐Chen Wu

161 papers receiving 1.6k citations

Peers

I‐Chen Wu
Comparison fields: 5 of 147
  • Building and Construction 351
  • Gastroenterology 127
  • Geology 109
  • Hardware and Architecture 85
  • Artificial Intelligence 378
Replace Francesco Calabrese with:
Francesco Calabrese Italy
Yu Cao United States
Ickjai Lee Australia
Zhe Sun China
Kenneth N. Brown Ireland
Ming Wan China
Liping Chen China
Sang-Woong Lee South Korea
Haibin Lv China
Deepika Koundal India
I‐Chen Wu relative to Francesco Calabrese Italy Francesco Calabrese's profile →
Citations per field
00.5×10×15×21.8×
Francesco Calabrese · 1×
Citations per year

Countries citing papers authored by I‐Chen Wu

Since Specialization
Citations

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

Fields of papers citing papers by I‐Chen Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by I‐Chen Wu. 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 I‐Chen Wu. The network helps show where I‐Chen Wu may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 180 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009200
2 2018108
3 200791
4 201067
5 201965
6 201951
7 201146
8 201144
9 202037
10 200737
11 201236
12 201034
13 198931
14 201028
15 201928
16 201525
17 198723
18 200220
19 201220
20 202319

About I‐Chen Wu

I‐Chen Wu is a scholar working on Artificial Intelligence, Hardware and Architecture, Developmental and Educational Psychology, Building and Construction and Computer Networks and Communications, having authored 180 papers that have together received 1.7k indexed citations. Recurring topics across this work include Artificial Intelligence in Games (55 papers), Digital Games and Media (27 papers), Reinforcement Learning in Robotics (18 papers), Sports Analytics and Performance (17 papers), Educational Games and Gamification (16 papers), BIM and Construction Integration (15 papers), Parallel Computing and Optimization Techniques (11 papers) and Optimization and Search Problems (7 papers). The work is most often cited by research in Building and Construction (351 citations), Gastroenterology (127 citations), Geology (109 citations), Hardware and Architecture (85 citations) and Artificial Intelligence (378 citations). I‐Chen Wu has collaborated with scholars based in Taiwan, United States and Canada. Frequent co-authors include Shang‐Hsien Hsieh, Shi-Jim Yen, Angela Chen, Jeng–Yih Wu, Antone R. Opekun, Sophie S.W. Wang, Ping‐I Hsu, David Y. Graham, Wen‐Chun Hung and Chen-Huan Pi. Their work appears in journals such as IEEE Transactions on Computational Intelligence and AI in Games, ICGA Journal, Theoretical Computer Science, International Journal of Cancer and Automation in Construction.

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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