Rajan M. Lukose
- Computer Networks and Communications top 1%
- Information Systems top 0.5%
- Statistical and Nonlinear Physics top 1%
- Artificial Intelligence top 2%
- Management Science and Operations Research top 1%
- Co-authors
- Bernardo A. HubermanAmit PuniyaniLada A. AdamicY. ZhouJames E. PitkowPeter PirolliBin CaoMartin Scholz
- Topics
- Peer-to-Peer Network Technologies (5 papers)Complex Network Analysis Techniques (3 papers)Distributed and Parallel Computing Systems (3 papers)
- Partner nations
- United StatesHong KongSouth Korea
In The Last Decade
Rajan M. Lukose
15 papers receiving 2.7k citations
Hit Papers
Peers
Comparison fields: 5 of 121
- Computer Networks and Communications 1.2k
- Information Systems 1.0k
- Statistical and Nonlinear Physics 716
- Artificial Intelligence 716
- Management Science and Operations Research 449
Countries citing papers authored by Rajan M. Lukose
This map shows the geographic impact of Rajan M. Lukose'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 Rajan M. Lukose with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rajan M. Lukose more than expected).
Fields of papers citing papers by Rajan M. Lukose
This network shows the impact of papers produced by Rajan M. Lukose. 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 Rajan M. Lukose. The network helps show where Rajan M. Lukose may publish in the future.
Co-authorship network of co-authors of Rajan M. Lukose
This figure shows the co-authorship network connecting the top 25 collaborators of Rajan M. Lukose. A scholar is included among the top collaborators of Rajan M. Lukose 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 Rajan M. Lukose. Rajan M. Lukose is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | One-Class Collaborative Filteringbreakdown → | 682 |
| 2 | 112 | |
| 3 | 44 | |
| 4 | 100 | |
| 5 | 6 | |
| 6 | 4 | |
| 7 | 3 | |
| 8 | Peer-to-Peer Computingbreakdown → | 389 |
| 9 | Search in power-law networksbreakdown → | 770 |
| 10 | 5 | |
| 11 | 475 | |
| 12 | 11 | |
| 13 | 212 | |
| 14 | 131 | |
| 15 | 12 |
About Rajan M. Lukose
Rajan M. Lukose is a scholar working on General Decision Sciences, Computer Networks and Communications and Management Science and Operations Research, having authored 15 papers that have together received 3.0k indexed citations. Recurring topics across this work include Peer-to-Peer Network Technologies (5 papers), Complex Network Analysis Techniques (3 papers) and Distributed and Parallel Computing Systems (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (716 citations), Computer Networks and Communications (1.2k citations) and Information Systems (1.0k citations). Rajan M. Lukose has collaborated with scholars based in United States, Hong Kong and South Korea. Frequent co-authors include Bernardo A. Huberman, Amit Puniyani, Lada A. Adamic, Y. Zhou, James E. Pitkow, Peter Pirolli, Bin Cao, Martin Scholz, Rong Pan and Qiang Yang. Their work appears in journals such as Science, Information Systems Frontiers and Experimental Economics.
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.