Ting Dang

670 total citations
43 papers, 361 citations indexed

About

Ting Dang is a scholar working on Signal Processing, Artificial Intelligence and Experimental and Cognitive Psychology. According to data from OpenAlex, Ting Dang has authored 43 papers receiving a total of 361 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Signal Processing, 20 papers in Artificial Intelligence and 15 papers in Experimental and Cognitive Psychology. Recurrent topics in Ting Dang's work include Emotion and Mood Recognition (14 papers), Speech and Audio Processing (13 papers) and Music and Audio Processing (12 papers). Ting Dang is often cited by papers focused on Emotion and Mood Recognition (14 papers), Speech and Audio Processing (13 papers) and Music and Audio Processing (12 papers). Ting Dang collaborates with scholars based in Australia, United Kingdom and China. Ting Dang's co-authors include Vidhyasaharan Sethu, Julien Epps, Cecilia Mascolo, Xia Tong, Jing Han, Zhaocheng Huang, Phu Ngoc Le, Brian Stasak, Eliathamby Ambikairajah and Dimitris Spathis and has published in prestigious journals such as Journal of Medical Internet Research, IEEE Journal of Biomedical and Health Informatics and World Journal of Microbiology and Biotechnology.

In The Last Decade

Ting Dang

35 papers receiving 349 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Ting Dang Australia	10	151	136	133	53	49	43	361
Adria Mallol-Ragolta Germany	11	134 0.9×	139 1.0×	160 1.2×	54 1.0×	27 0.6×	30	326
Sergey Pugachevskiy Germany	7	170 1.1×	103 0.8×	129 1.0×	56 1.1×	12 0.2×	7	320
Lukas Stappen Germany	12	117 0.8×	249 1.8×	261 2.0×	73 1.4×	19 0.4×	25	516
Asif Salekin United States	8	30 0.2×	71 0.5×	118 0.9×	26 0.5×	15 0.3×	34	345
A. Milton India	7	180 1.2×	178 1.3×	87 0.7×	76 1.4×	7 0.1×	22	312
Dale Joachim United States	10	54 0.4×	139 1.0×	87 0.7×	13 0.2×	19 0.4×	28	303
Pritam Sarkar Canada	8	51 0.3×	179 1.3×	76 0.6×	70 1.3×	20 0.4×	16	452
Theodoros Iliou Greece	11	235 1.6×	344 2.5×	185 1.4×	91 1.7×	11 0.2×	20	591
Phu Ngoc Le Australia	10	121 0.8×	122 0.9×	135 1.0×	35 0.7×	3 0.1×	25	355
Fatma Patlar Akbulut Türkiye	10	38 0.3×	82 0.6×	58 0.4×	70 1.3×	12 0.2×	40	327

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-authorship network of co-authors of Ting Dang

This figure shows the co-authorship network connecting the top 25 collaborators of Ting Dang. A scholar is included among the top collaborators of Ting Dang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ting Dang. Ting Dang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Dang, Ting, et al.. (2025). RawTFNet: A Lightweight CNN Architecture for Speech Anti-Spoofing. 1997–2001.

Dang, Ting, et al.. (2025). SQUIREDL: Sparse Sequence-to-Sequence Uncertainty Estimation in Evidential Deep Learning. 6(3). 1–21.

Hong, Xin, Yuan Gong, Vidhyasaharan Sethu, & Ting Dang. (2025). AER-LLM: Ambiguity-aware Emotion Recognition Leveraging Large Language Models. 1–5. 2 indexed citations

Tang, Xiaoyu, et al.. (2025). Speech Emotion Recognition via CNN-Transformer and multidimensional attention mechanism. Speech Communication. 171. 103242–103242. 4 indexed citations

Dang, Ting, et al.. (2024). StatioCL : Contrastive Learning for Time Series via Non-Stationary and Temporal Contrast. 2575–2584. 2 indexed citations

Spathis, Dimitris, et al.. (2024). OptiBreathe: An Earable-based PPG System for Continuous Respiration Rate, Breathing Phase, and Tidal Volume Monitoring. ePrints Soton (University of Southampton). 99–106. 6 indexed citations

Dang, Ting & Hong Jia. (2024). Multimodal Large Language Models in Human-Centered Health: Practical Insights. IEEE Pervasive Computing. 23(4). 87–93.

Tong, Xia, Ting Dang, Jing Han, Lorena Qendro, & Cecilia Mascolo. (2024). Uncertainty-Aware Health Diagnostics via Class-Balanced Evidential Deep Learning. IEEE Journal of Biomedical and Health Informatics. 28(11). 6417–6428. 4 indexed citations

Han, Jing, Marco Montagna, Andreas Grammenos, et al.. (2023). Evaluating Listening Performance for COVID-19 Detection by Clinicians and Machine Learning: Comparative Study. Journal of Medical Internet Research. 25. e44804–e44804. 3 indexed citations

10.

Dang, Ting, Jing Han, Xia Tong, et al.. (2023). Conditional Neural ODE Processes for Individual Disease Progression Forecasting: A Case Study on COVID-19. ePrints Soton (University of Southampton). 3914–3925. 4 indexed citations

11.

Ma, Dong, Ting Dang, Ming Ding, & Rajesh Krishna Balan. (2023). ClearSpeech. Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies. 7(4). 1–25. 2 indexed citations

12.

Dang, Ting, et al.. (2023). Human-centred artificial intelligence for mobile health sensing: challenges and opportunities. Royal Society Open Science. 10(11). 230806–230806. 7 indexed citations

13.

Ambikairajah, Eliathamby, et al.. (2023). DNN controlled adaptive front-end for replay attack detection systems. Speech Communication. 154. 102973–102973. 4 indexed citations

14.

Dang, Ting, Jing Han, Xia Tong, et al.. (2022). Exploring Longitudinal Cough, Breath, and Voice Data for COVID-19 Progression Prediction via Sequential Deep Learning: Model Development and Validation. Journal of Medical Internet Research. 24(6). e37004–e37004. 23 indexed citations

15.

Han, Jing, Xia Tong, Dimitris Spathis, et al.. (2022). Sounds of COVID-19: exploring realistic performance of audio-based digital testing. npj Digital Medicine. 5(1). 16–16. 59 indexed citations

16.

Li, Yudi, et al.. (2022). Characterization and mutagenesis of a novel Mycobacterium smegmatis-derived glutamate decarboxylase active at neutral pH. World Journal of Microbiology and Biotechnology. 38(5). 75–75. 10 indexed citations

17.

Dang, Ting, et al.. (2022). A Novel Sequential Monte Carlo Framework for Predicting Ambiguous Emotion States. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 11. 8567–8571. 2 indexed citations

18.

Dang, Ting, et al.. (2022). Exploring Semi-supervised Learning for Audio-based COVID-19 Detection using FixMatch. Interspeech 2022. 2468–2472. 1 indexed citations

19.

Tong, Xia, Dimitris Spathis, Andreas Grammenos, et al.. (2021). COVID-19 Sounds: A Large-Scale Audio Dataset for Digital Respiratory Screening. Neural Information Processing Systems. 28 indexed citations

20.

Dang, Ting, Brian Stasak, Zhaocheng Huang, et al.. (2017). Investigating Word Affect Features and Fusion of Probabilistic Predictions Incorporating Uncertainty in AVEC 2017. UNSWorks (University of New South Wales, Sydney, Australia). 27–35. 29 indexed citations

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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