Hai Won Chang

1.6k citations
43 papers · 1.3k · h-index 21

Impact in

Papers in

Hai Won Chang

43 papers receiving 1.2k citations

Peers

Hai Won Chang
Comparison fields: 5 of 96
  • Organic Chemistry 485
  • Cellular and Molecular Neuroscience 222
  • Physical and Theoretical Chemistry 109
  • Electrochemistry 60
  • Neurology 123
Replace Catherine Foulon with:
Catherine Foulon France
Jürgen Engel Germany
Anny Slama‐Schwok France
Sara M. Butterfield United States
Marco Bortolus Italy
Ralph G. Yount United States
H.‐J. Galla Germany
Francesca Peccati Spain
M. ROBBA France
Fengtian Xue United States
Hai Won Chang relative to Catherine Foulon France Catherine Foulon's profile →
Citations per field
00.5×4.0×
Catherine Foulon · 1×
Citations per year

Countries citing papers authored by Hai Won Chang

Since Specialization
Citations

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

Fields of papers citing papers by Hai Won Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hai Won Chang. 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 Hai Won Chang. The network helps show where Hai Won Chang may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1977157
2 198096
3 196296
4 197293
5 196790
6 196179
7 196567
8 197957
9 197449
10 198343
11 197741
12 197640
13 196138
14 198134
15 198231
16 197431
17 202130
18 197924
19 199323
20 199123

About Hai Won Chang

Hai Won Chang is a scholar working on Organic Chemistry, Molecular Biology, Cellular and Molecular Neuroscience, Spectroscopy and Neurology, having authored 43 papers that have together received 1.3k indexed citations. Recurring topics across this work include Myasthenia Gravis and Thymoma (6 papers), Muscle Physiology and Disorders (5 papers), Neurobiology and Insect Physiology Research (4 papers), Cyclopropane Reaction Mechanisms (3 papers), Neuroscience and Neural Engineering (3 papers), Electrochemical Analysis and Applications (3 papers), Cholinesterase and Neurodegenerative Diseases (3 papers) and Genetic Neurodegenerative Diseases (3 papers). The work is most often cited by research in Organic Chemistry (485 citations), Cellular and Molecular Neuroscience (222 citations), Physical and Theoretical Chemistry (109 citations), Electrochemistry (60 citations) and Neurology (123 citations). Hai Won Chang has collaborated with scholars based in United States, Italy and Germany. Frequent co-authors include Ernest Bock, Ronald Breslow, Ronald Breslow, Terrone L. Rosenberry, Audrey S. Penn, Roger R. Hill, E. Wasserman, Henry A. Lester, Péter Gál and Lawrence J. Altman. Their work appears in journals such as Journal of the American Chemical Society, Annals of the New York Academy of Sciences, Neurology, Biochemistry and European Journal of Pediatrics.

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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