Kaixiang Mo
Impact in
- Computer Science Applications top 10%
- Mobile Crowdsensing and Crowdsourcing
- Transportation top 10%
- Human Mobility and Location-Based Analysis
Papers in
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- Speech and dialogue systems 2
- Topic Modeling 2
- Machine Learning and Data Classification 1
- Domain Adaptation and Few-Shot Learning 1
- Advanced Text Analysis Techniques 1
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- Human Mobility and Location-Based Analysis 2
- Co-authors
- Qiang Yang (4 shared papers)Erheng Zhong (3 shared papers)Ben Tan (2 shared papers)Shuangyin Li (2 shared papers)Yu Zhang (1 shared paper)Jiajun Li (1 shared paper)Yong Li (1 shared paper)Lei Xiao (1 shared paper)
- Journals
- Pervasive and Mobile Computing (1 paper)Rare & Special e-Zone (The Hong Kong University of Science and Technology) (4 papers)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
In The Last Decade
Kaixiang Mo
7 papers receiving 214 citations
Peers
Comparison fields: 5 of 44
- Computer Science Applications 46
- Transportation 37
- Artificial Intelligence 134
- Computer Vision and Pattern Recognition 40
- Management Science and Operations Research 22
Countries citing papers authored by Kaixiang Mo
This map shows the geographic impact of Kaixiang Mo'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 Kaixiang Mo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kaixiang Mo more than expected).
Fields of papers citing papers by Kaixiang Mo
This network shows the impact of papers produced by Kaixiang Mo. 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 Kaixiang Mo. The network helps show where Kaixiang Mo may publish in the future.
Co-authors
The 16 scholars most cited alongside Kaixiang Mo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 67 | |
| 2 | 2013 | 47 | |
| 3 | 2013 | 46 | |
| 4 | Image feature learning for cold start problem in display advertising | 2015 | 25 |
| 5 | Report of Task 3: Your Phone Understands You | 2012 | 14 |
| 6 | 2020 | 12 | |
| 7 | 2020 | 8 |
About Kaixiang Mo
Kaixiang Mo is a scholar working on Artificial Intelligence, Transportation, Information Systems, Computer Vision and Pattern Recognition and Computer Science Applications, having authored 7 papers that have together received 219 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (3 papers), Speech and dialogue systems (2 papers), Topic Modeling (2 papers), Human Mobility and Location-Based Analysis (2 papers), Advanced Image and Video Retrieval Techniques (1 paper), Machine Learning and Data Classification (1 paper), Domain Adaptation and Few-Shot Learning (1 paper) and Advanced Text Analysis Techniques (1 paper). The work is most often cited by research in Computer Science Applications (46 citations), Transportation (37 citations), Artificial Intelligence (134 citations), Computer Vision and Pattern Recognition (40 citations) and Management Science and Operations Research (22 citations). Kaixiang Mo has collaborated with scholars based in Hong Kong and China. Frequent co-authors include Qiang Yang, Erheng Zhong, Ben Tan, Shuangyin Li, Yu Zhang, Jiajun Li, Yong Li, Lei Xiao, Jie Jiang and Yu Zhang. Their work appears in journals such as Pervasive and Mobile Computing, Rare & Special e-Zone (The Hong Kong University of Science and Technology) and Proceedings of the AAAI Conference on Artificial Intelligence.
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.