Chang Hu
- Computer Science Applications top 2%
- Artificial Intelligence top 10%
- Signal Processing top 10%
- Information Systems top 10%
- Computational Mechanics top 10%
- Co-authors
- Mingjun XiaoLiusheng HuangGuoju GaoJie WuSoo Ngee KohSusanto RahardjaBenjamin B. BedersonPhilip Resnik
- Topics
- Mobile Crowdsensing and Crowdsourcing (9 papers)Topic Modeling (5 papers)Natural Language Processing Techniques (5 papers)
- Journals
- SHILAP Revista de lepidopterologíaFrontiers in PsychologyCritical Care
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Chang Hu
37 papers receiving 541 citations
Peers
Comparison fields: 5 of 90
- Computer Science Applications 215
- Artificial Intelligence 185
- Signal Processing 98
- Information Systems 97
- Computational Mechanics 87
Countries citing papers authored by Chang Hu
This map shows the geographic impact of Chang Hu'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 Chang Hu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chang Hu more than expected).
Fields of papers citing papers by Chang Hu
This network shows the impact of papers produced by Chang Hu. 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 Chang Hu. The network helps show where Chang Hu may publish in the future.
Co-authorship network of co-authors of Chang Hu
This figure shows the co-authorship network connecting the top 25 collaborators of Chang Hu. A scholar is included among the top collaborators of Chang Hu 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 Chang Hu. Chang Hu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 4 | |
| 7 | 5 | |
| 8 | 4 | |
| 9 | 0 | |
| 10 | 6 | |
| 11 | 1 | |
| 12 | 1 | |
| 13 | 10 | |
| 14 | 14 | |
| 15 | 4 | |
| 16 | Chorus: Letting the Crowd Speak with One Voice | 4 |
| 17 | The Value of Monolingual Crowdsourcing in a Real-World Translation Scenario: Simulation using Haitian Creole Emergency SMS Messages | 13 |
| 18 | 27 | |
| 19 | Improving Translation via Targeted Paraphrasing | 26 |
| 20 | 94 |
About Chang Hu
Chang Hu is a scholar working on Computer Science Applications, Human Factors and Ergonomics and Artificial Intelligence, having authored 41 papers that have together received 564 indexed citations. Recurring topics across this work include Mobile Crowdsensing and Crowdsourcing (9 papers), Topic Modeling (5 papers) and Natural Language Processing Techniques (5 papers). The work is most often cited by research in Computer Science Applications (215 citations), Transportation (69 citations) and Signal Processing (98 citations). Chang Hu has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Mingjun Xiao, Liusheng Huang, Guoju Gao, Jie Wu, Soo Ngee Koh, Susanto Rahardja, Benjamin B. Bederson, Philip Resnik, Yakov Kronrod and Steven M. Drucker. Their work appears in journals such as SHILAP Revista de lepidopterología, Frontiers in Psychology and Critical Care.
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.