Ting-Hao Huang
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Computer Science Applications top 5%
- Human-Computer Interaction top 5%
- Information Systems top 10%
- Co-authors
- Jeffrey P. BighamLun‐Wei KuAmos AzariaHsin‐Hsi ChenIllah NourbakhshWalter S. LaseckiBing‐Yu ChenHua Shen
- Topics
- Topic Modeling (17 papers)Multimodal Machine Learning Applications (11 papers)Natural Language Processing Techniques (11 papers)
- Journals
- IEEE Transactions on Consumer ElectronicsPatternsACM Transactions on Interactive Intelligent Systems
- Partner nations
- United StatesTaiwanIsrael
In The Last Decade
Ting-Hao Huang
54 papers receiving 592 citations
Peers
Comparison fields: 5 of 93
- Artificial Intelligence 302
- Computer Vision and Pattern Recognition 228
- Computer Science Applications 71
- Human-Computer Interaction 68
- Information Systems 46
Countries citing papers authored by Ting-Hao Huang
This map shows the geographic impact of Ting-Hao Huang'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-Hao Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ting-Hao Huang more than expected).
Fields of papers citing papers by Ting-Hao Huang
This network shows the impact of papers produced by Ting-Hao Huang. 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-Hao Huang. The network helps show where Ting-Hao Huang may publish in the future.
Co-authorship network of co-authors of Ting-Hao Huang
This figure shows the co-authorship network connecting the top 25 collaborators of Ting-Hao Huang. A scholar is included among the top collaborators of Ting-Hao Huang 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-Hao Huang. Ting-Hao Huang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 6 | |
| 5 | 20 | |
| 6 | 7 | |
| 7 | 13 | |
| 8 | 14 | |
| 9 | 3 | |
| 10 | 4 | |
| 11 | 38 | |
| 12 | RISE Video Dataset: Recognizing Industrial Smoke Emissions | 2 |
| 13 | 16 | |
| 14 | 13 | |
| 15 | 138 | |
| 16 | On Available Corpora for Empirical Methods in Vision & Language. | 1 |
| 17 | Social Metaphor Detection via Topical Analysis | 5 |
| 18 | Modeling Pollyanna Phenomena in Chinese Sentiment Analysis | 1 |
| 19 | Predicting Opinion Dependency Relations for Opinion Analysis | 4 |
| 20 | 11 |
About Ting-Hao Huang
Ting-Hao Huang is a scholar working on Computer Science Applications, Artificial Intelligence and Information Systems and Management, having authored 56 papers that have together received 616 indexed citations. Recurring topics across this work include Topic Modeling (17 papers), Multimodal Machine Learning Applications (11 papers) and Natural Language Processing Techniques (11 papers). The work is most often cited by research in Health Informatics (22 citations), Computer Science Applications (71 citations) and Human-Computer Interaction (68 citations). Ting-Hao Huang has collaborated with scholars based in United States, Taiwan and Israel. Frequent co-authors include Jeffrey P. Bigham, Lun‐Wei Ku, Amos Azaria, Hsin‐Hsi Chen, Illah Nourbakhsh, Walter S. Lasecki, Bing‐Yu Chen, Hua Shen, Ishan Misra and Aishwarya Agrawal. Their work appears in journals such as IEEE Transactions on Consumer Electronics, Patterns and ACM Transactions on Interactive Intelligent Systems.
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.