Chengkai Li
- Artificial Intelligence top 1%
- Information Systems top 1%
- Signal Processing top 1%
- Computer Networks and Communications top 2%
- Sociology and Political Science top 5%
- Co-authors
- Kevin Chen–Chuan ChangNaeemul HassanMark TremayneIhab F. IlyasCong YuJun YangZhen ZhangFatma Taş Arslan
- Topics
- Data Management and Algorithms (28 papers)Topic Modeling (24 papers)Advanced Database Systems and Queries (17 papers)
- Partner nations
- United StatesChinaCanada
In The Last Decade
Chengkai Li
88 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 89
- Artificial Intelligence 994
- Information Systems 775
- Signal Processing 576
- Computer Networks and Communications 560
- Sociology and Political Science 388
Countries citing papers authored by Chengkai Li
This map shows the geographic impact of Chengkai Li'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 Chengkai Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chengkai Li more than expected).
Fields of papers citing papers by Chengkai Li
This network shows the impact of papers produced by Chengkai Li. 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 Chengkai Li. The network helps show where Chengkai Li may publish in the future.
Co-authorship network of co-authors of Chengkai Li
This figure shows the co-authorship network connecting the top 25 collaborators of Chengkai Li. A scholar is included among the top collaborators of Chengkai Li 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 Chengkai Li. Chengkai Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 4 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 4 | |
| 9 | 1 | |
| 10 | 3 | |
| 11 | 1 | |
| 12 | 1 | |
| 13 | 2 | |
| 14 | 5 | |
| 15 | 3 | |
| 16 | 6 | |
| 17 | XML Query Optimization in Map-Reduce | 17 |
| 18 | Computational Journalism: A Call to Arms to Database Researchers | 66 |
| 19 | Querying for Information Integration: How to go from an Imprecise Intent to a Precise Query? | 3 |
| 20 | RankSQL: supporting ranking queries in relational database management systems | 15 |
About Chengkai Li
Chengkai Li is a scholar working on Signal Processing, Artificial Intelligence and Information Systems, having authored 97 papers that have together received 1.9k indexed citations. Recurring topics across this work include Data Management and Algorithms (28 papers), Topic Modeling (24 papers) and Advanced Database Systems and Queries (17 papers). The work is most often cited by research in Signal Processing (576 citations), Information Systems (775 citations) and Artificial Intelligence (994 citations). Chengkai Li has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Kevin Chen–Chuan Chang, Naeemul Hassan, Mark Tremayne, Ihab F. Ilyas, Cong Yu, Jun Yang, Zhen Zhang, Fatma Taş Arslan, Mitesh Patel and Bin He. Their work appears in journals such as Advanced Materials, Journal of Virology and Journal of Colloid and Interface Science.
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.