Kamesh Madduri
- Computer Networks and Communications top 2%
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Hardware and Architecture top 2%
- Statistical and Nonlinear Physics top 2%
- Co-authors
- David A. BaderGeorge M. SlotaAydın BuluçSivasankaran RajamanickamHumayun KabirKarl JiangDaniel Chavarría-MirandaDavid Ediger
- Topics
- Graph Theory and Algorithms (27 papers)Complex Network Analysis Techniques (14 papers)Advanced Graph Neural Networks (13 papers)
- Cited by
- Hardware and ArchitectureComputer Vision and Pattern RecognitionComputer Networks and Communications
- Journals
- BloodThe Journal of Physical Chemistry BIEEE Transactions on Intelligent Transportation Systems
- Partner nations
- United StatesSouth KoreaSwitzerland
In The Last Decade
Kamesh Madduri
66 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 93
- Computer Networks and Communications 675
- Computer Vision and Pattern Recognition 631
- Artificial Intelligence 456
- Hardware and Architecture 393
- Statistical and Nonlinear Physics 359
Countries citing papers authored by Kamesh Madduri
This map shows the geographic impact of Kamesh Madduri'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 Kamesh Madduri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kamesh Madduri more than expected).
Fields of papers citing papers by Kamesh Madduri
This network shows the impact of papers produced by Kamesh Madduri. 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 Kamesh Madduri. The network helps show where Kamesh Madduri may publish in the future.
Co-authorship network of co-authors of Kamesh Madduri
This figure shows the co-authorship network connecting the top 25 collaborators of Kamesh Madduri. A scholar is included among the top collaborators of Kamesh Madduri 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 Kamesh Madduri. Kamesh Madduri 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 | 1 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 31 | |
| 8 | 5 | |
| 9 | 8 | |
| 10 | Supercomputing for Web Graph Analytics. | 1 |
| 11 | 34 | |
| 12 | 67 | |
| 13 | 14 | |
| 14 | 1 | |
| 15 | 25 | |
| 16 | 1 | |
| 17 | Efficient Joins with Compressed Bitmap Indexes | 6 |
| 18 | 47 | |
| 19 | 15 | |
| 20 | 86 |
About Kamesh Madduri
Kamesh Madduri is a scholar working on Hardware and Architecture, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics, having authored 70 papers that have together received 1.5k indexed citations. Recurring topics across this work include Graph Theory and Algorithms (27 papers), Complex Network Analysis Techniques (14 papers) and Advanced Graph Neural Networks (13 papers). The work is most often cited by research in Hardware and Architecture (393 citations), Computer Vision and Pattern Recognition (631 citations) and Computer Networks and Communications (675 citations). Kamesh Madduri has collaborated with scholars based in United States, South Korea and Switzerland. Frequent co-authors include David A. Bader, George M. Slota, Aydın Buluç, Sivasankaran Rajamanickam, Humayun Kabir, Karl Jiang, Daniel Chavarría-Miranda, David Ediger, Samuel Williams and Leonid Oliker. Their work appears in journals such as Blood, The Journal of Physical Chemistry B and IEEE Transactions on Intelligent Transportation Systems.
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.