Xiaohu Liu
- Artificial Intelligence top 10%
- Mechanics of Materials
- Computer Vision and Pattern Recognition
- Computational Mechanics
- Materials Chemistry
- Co-authors
- Shaofan LiRuhi SarikayaGökhan TürDilek Hakkani‐TürPascale FungYoung‐Bum KimAli ElkahkyLarry Heck
- Topics
- Topic Modeling (10 papers)Natural Language Processing Techniques (10 papers)Speech and dialogue systems (9 papers)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Xiaohu Liu
25 papers receiving 198 citations
Peers
Comparison fields: 5 of 55
- Artificial Intelligence 157
- Mechanics of Materials 34
- Computer Vision and Pattern Recognition 25
- Computational Mechanics 24
- Materials Chemistry 23
Countries citing papers authored by Xiaohu Liu
This map shows the geographic impact of Xiaohu Liu'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 Xiaohu Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaohu Liu more than expected).
Fields of papers citing papers by Xiaohu Liu
This network shows the impact of papers produced by Xiaohu Liu. 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 Xiaohu Liu. The network helps show where Xiaohu Liu may publish in the future.
Co-authorship network of co-authors of Xiaohu Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Xiaohu Liu. A scholar is included among the top collaborators of Xiaohu Liu 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 Xiaohu Liu. Xiaohu Liu 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 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 3 | |
| 7 | 0 | |
| 8 | 1 | |
| 9 | 10 | |
| 10 | 7 | |
| 11 | 2 | |
| 12 | 1 | |
| 13 | Quantum wireless communication network model and performance analysis | 3 |
| 14 | 4 | |
| 15 | Detecting topic labels for tweets by matching features from pseudo-relevance feedback | 1 |
| 16 | A Wizard-of-Oz interface to study information presentation strategies for spoken dialogue systems | 7 |
| 17 | 4 | |
| 18 | 16 | |
| 19 | 16 | |
| 20 | 6 |
About Xiaohu Liu
Xiaohu Liu is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Human-Computer Interaction, having authored 30 papers that have together received 234 indexed citations. Recurring topics across this work include Topic Modeling (10 papers), Natural Language Processing Techniques (10 papers) and Speech and dialogue systems (9 papers). The work is most often cited by research in Artificial Intelligence (157 citations), Mechanics of Materials (34 citations) and Computer Vision and Pattern Recognition (25 citations). Xiaohu Liu has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Shaofan Li, Ruhi Sarikaya, Gökhan Tür, Dilek Hakkani‐Tür, Pascale Fung, Young‐Bum Kim, Ali Elkahky, Larry Heck, Karl Stratos and Aslı Çelikyılmaz. Their work appears in journals such as The Journal of Chemical Physics, Scientific Reports and The Journal of Urology.
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.