Grace Chung

1.1k citations
30 papers · 744 · h-index 14

Impact in

Papers in

    • Speech and dialogue systems 13
    • Topic Modeling 13
    • Natural Language Processing Techniques 12
    • Speech Recognition and Synthesis 5
    • Multi-Agent Systems and Negotiation 4
    • Biomedical Text Mining and Ontologies 4

Grace Chung

28 papers receiving 651 citations

Peers

Grace Chung
Comparison fields: 5 of 97
  • Artificial Intelligence 386
  • Psychiatry and Mental health 146
  • Cellular and Molecular Neuroscience 170
  • Developmental Neuroscience 20
  • Pediatrics, Perinatology and Child Health 91
Replace Stanley F. Nelson with:
Stanley F. Nelson United States
Dominique Duncan United States
David Willé Germany
Ahmed Radwan Belgium
J. Meier Netherlands
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Citations per field
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Stanley F. Nelson · 1×
Citations per year

Countries citing papers authored by Grace Chung

Since Specialization
Citations

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

Fields of papers citing papers by Grace Chung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006224
2 200985
3 200956
4 200453
5 200337
6 199434
7 200432
8 199325
9 200323
10 200921
11 200821
12 201517
13 200715
14 200413
15 200512
16 199812
17 199711
18 20029
19 20008
20 19997

About Grace Chung

Grace Chung is a scholar working on Artificial Intelligence, Molecular Biology, Signal Processing, Experimental and Cognitive Psychology and Dermatology, having authored 30 papers that have together received 744 indexed citations. Recurring topics across this work include Speech and dialogue systems (13 papers), Topic Modeling (13 papers), Natural Language Processing Techniques (12 papers), Speech Recognition and Synthesis (5 papers), Biomedical Text Mining and Ontologies (4 papers), Multi-Agent Systems and Negotiation (4 papers), Phonetics and Phonology Research (3 papers) and Speech and Audio Processing (3 papers). The work is most often cited by research in Artificial Intelligence (386 citations), Psychiatry and Mental health (146 citations), Cellular and Molecular Neuroscience (170 citations), Developmental Neuroscience (20 citations) and Pediatrics, Perinatology and Child Health (91 citations). Grace Chung has collaborated with scholars based in United States, Australia and Denmark. Frequent co-authors include Stephanie Seneff, Cristina Richichi, Céline Dubé, Tallie Z. Baram, Roland A. Bender, Brian Litt, Gerard Ellis, Casey Whitelaw, Ben Hutchinson and Chao Wang. Their work appears in journals such as BMC Medical Informatics and Decision Making, Stem Cells, British Journal of Haematology, Journal of Telemedicine and Telecare and BMC Bioinformatics.

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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