Ting Dang

670 citations
43 papers · 361 · h-index 10

Impact in

Papers in

    • Speech and Audio Processing 13
    • Music and Audio Processing 12
    • Time Series Analysis and Forecasting 6
    • Speech Recognition and Synthesis 8
    • Sentiment Analysis and Opinion Mining 5

Ting Dang

35 papers receiving 349 citations

Peers

Ting Dang
Comparison fields: 5 of 81
  • Signal Processing 151
  • Experimental and Cognitive Psychology 136
  • Artificial Intelligence 133
  • Computer Vision and Pattern Recognition 53
  • Health Informatics 3
Replace Sergey Pugachevskiy with:
Sergey Pugachevskiy Germany
Lukas Stappen Germany
Adria Mallol-Ragolta Germany
Pritam Sarkar Canada
Eugene Laksana United States
Dale Joachim United States
A. Milton India
Theodoros Iliou Greece
Monorama Swain India
Phu Ngoc Le Australia
Ting Dang relative to Sergey Pugachevskiy Germany Sergey Pugachevskiy's profile →
Citations per field
00.5×10.3×
Sergey Pugachevskiy · 1×
Citations per year

Countries citing papers authored by Ting Dang

Since Specialization
Citations

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

Fields of papers citing papers by Ting Dang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ting Dang, 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 Ting Dang Line = papers co-authored together Ting Dang 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 202259
2 201554
3 201729
4
COVID-19 Sounds: A Large-Scale Audio Dataset for Digital Respiratory Screening
202128
5 202223
6 201621
7 202116
8 201713
9 202210
10 201810
11 20238
12 20248
13 20237
14 20246
15 20166
16 20196
17 20245
18 20235
19 20185
20 20245

About Ting Dang

Ting Dang is a scholar working on Signal Processing, Artificial Intelligence, Experimental and Cognitive Psychology, Social Psychology and Pulmonary and Respiratory Medicine, having authored 43 papers that have together received 361 indexed citations. Recurring topics across this work include Emotion and Mood Recognition (14 papers), Speech and Audio Processing (13 papers), Music and Audio Processing (12 papers), Speech Recognition and Synthesis (8 papers), Time Series Analysis and Forecasting (6 papers), COVID-19 diagnosis using AI (5 papers), Sentiment Analysis and Opinion Mining (5 papers) and Phonocardiography and Auscultation Techniques (4 papers). The work is most often cited by research in Signal Processing (151 citations), Experimental and Cognitive Psychology (136 citations), Artificial Intelligence (133 citations), Computer Vision and Pattern Recognition (53 citations) and Health Informatics (3 citations). Ting Dang has collaborated with scholars based in Australia, United Kingdom and China. Frequent co-authors include Vidhyasaharan Sethu, Julien Epps, Cecilia Mascolo, Phu Ngoc Le, Brian Stasak, Zhaocheng Huang, Jing Han, Xia Tong, Dimitris Spathis and Eliathamby Ambikairajah. Their work appears in journals such as Speech Communication, Journal of Medical Internet Research, IEEE Transactions on Affective Computing, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies and IEEE Journal of Biomedical and Health Informatics.

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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