J. G. Dai
- Management Information Systems top 0.1%
- Computer Networks and Communications top 1%
- Electrical and Electronic Engineering top 5%
- Management Science and Operations Research top 0.5%
- Statistics and Probability top 1%
- Co-authors
- Balaji PrabhakarSean MeynPengyi ShiTolga TezcanGideon WeissAnton BravermanJ. Michael HarrisonWuqin Lin
- Topics
- Advanced Queuing Theory Analysis (72 papers)Network Traffic and Congestion Control (21 papers)Advanced Wireless Network Optimization (19 papers)
- Cited by
- Management Information SystemsComputer Networks and CommunicationsManagement Science and Operations Research
- Partner nations
- United StatesChinaHong Kong
In The Last Decade
J. G. Dai
94 papers receiving 3.2k citations
Hit Papers
Peers
Comparison fields: 5 of 88
- Management Information Systems 2.2k
- Computer Networks and Communications 1.4k
- Electrical and Electronic Engineering 1.1k
- Management Science and Operations Research 741
- Statistics and Probability 366
Countries citing papers authored by J. G. Dai
This map shows the geographic impact of J. G. Dai'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 J. G. Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J. G. Dai more than expected).
Fields of papers citing papers by J. G. Dai
This network shows the impact of papers produced by J. G. Dai. 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 J. G. Dai. The network helps show where J. G. Dai may publish in the future.
Co-authorship network of co-authors of J. G. Dai
This figure shows the co-authorship network connecting the top 25 collaborators of J. G. Dai. A scholar is included among the top collaborators of J. G. Dai 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 J. G. Dai. J. G. Dai 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 | 1 | |
| 3 | 0 | |
| 4 | 16 | |
| 5 | 14 | |
| 6 | 1 | |
| 7 | 3 | |
| 8 | 13 | |
| 9 | 42 | |
| 10 | 5 | |
| 11 | 13 | |
| 12 | 2 | |
| 13 | 26 | |
| 14 | 11 | |
| 15 | 27 | |
| 16 | Electronics Manufacturing Service Industry | 1 |
| 17 | 41 | |
| 18 | 23 | |
| 19 | 24 | |
| 20 | 81 |
About J. G. Dai
J. G. Dai is a scholar working on Management Information Systems, Management Science and Operations Research and Statistics and Probability, having authored 99 papers that have together received 3.4k indexed citations. Recurring topics across this work include Advanced Queuing Theory Analysis (72 papers), Network Traffic and Congestion Control (21 papers) and Advanced Wireless Network Optimization (19 papers). The work is most often cited by research in Management Information Systems (2.2k citations), Computer Networks and Communications (1.4k citations) and Management Science and Operations Research (741 citations). J. G. Dai has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Balaji Prabhakar, Sean Meyn, Pengyi Shi, Tolga Tezcan, Gideon Weiss, Anton Braverman, J. Michael Harrison, Wuqin Lin, Shuangchi He and John H. Vande Vate. Their work appears in journals such as IEEE Transactions on Automatic Control, Management Science and Operations Research.
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.