Houping Xiao
- Artificial Intelligence top 2%
- Computer Science Applications top 0.5%
- Transportation top 5%
- Information Systems top 5%
- Health Information Management top 1%
- Topics
- Mobile Crowdsensing and Crowdsourcing (13 papers)Privacy-Preserving Technologies in Data (11 papers)Anomaly Detection Techniques and Applications (6 papers)
- Journals
- Journal of Financial EconomicsIEEE Transactions on Knowledge and Data EngineeringIEEE/ACM Transactions on Networking
- Partner nations
- United StatesChinaSwitzerland
In The Last Decade
Houping Xiao
34 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 77
- Artificial Intelligence 730
- Computer Science Applications 525
- Transportation 141
- Information Systems 131
- Health Information Management 123
Countries citing papers authored by Houping Xiao
This map shows the geographic impact of Houping Xiao'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 Houping Xiao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Houping Xiao more than expected).
Fields of papers citing papers by Houping Xiao
This network shows the impact of papers produced by Houping Xiao. 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 Houping Xiao. The network helps show where Houping Xiao may publish in the future.
Co-authorship network of co-authors of Houping Xiao
This figure shows the co-authorship network connecting the top 25 collaborators of Houping Xiao. A scholar is included among the top collaborators of Houping Xiao 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 Houping Xiao. Houping Xiao 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 | 5 | |
| 4 | 1 | |
| 5 | 10 | |
| 6 | Power of deep learning: Quantifying language to explain cross-sectional returns | 2 |
| 7 | 17 | |
| 8 | 15 | |
| 9 | 2 | |
| 10 | 63 | |
| 11 | 121 | |
| 12 | 17 | |
| 13 | 21 | |
| 14 | 59 | |
| 15 | 28 | |
| 16 | 18 | |
| 17 | 19 | |
| 18 | 1 | |
| 19 | 126 | |
| 20 | 11 |
About Houping Xiao
Houping Xiao is a scholar working on Computational Mathematics, Computer Science Applications and Health Information Management, having authored 37 papers that have together received 1.0k indexed citations. Recurring topics across this work include Mobile Crowdsensing and Crowdsourcing (13 papers), Privacy-Preserving Technologies in Data (11 papers) and Anomaly Detection Techniques and Applications (6 papers). The work is most often cited by research in Computer Science Applications (525 citations), Health Information Management (123 citations) and Computational Mathematics (14 citations). Houping Xiao has collaborated with scholars based in United States, China and Switzerland. Frequent co-authors include Lü Su, Jing Gao, Klara Nahrstedt, Haiming Jin, Fenglong Ma, Chenglin Miao, Wenjun Jiang, Yaliang Li, Radha Chitta and Jing Zhou. Their work appears in journals such as Journal of Financial Economics, IEEE Transactions on Knowledge and Data Engineering and IEEE/ACM Transactions on Networking.
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.