Sayan Ranu
- Signal Processing top 2%
- Artificial Intelligence top 5%
- Statistical and Nonlinear Physics top 5%
- Computer Vision and Pattern Recognition top 5%
- Computer Networks and Communications top 5%
- Co-authors
- Ambuj K. SinghAkhil AroraSainyam GalhotraP DeepakAditya TelangSriram RaghavanVineet ChaojiRushi Bhatt
- Topics
- Data Management and Algorithms (19 papers)Graph Theory and Algorithms (12 papers)Advanced Graph Neural Networks (10 papers)
- Partner nations
- IndiaUnited StatesUnited Kingdom
In The Last Decade
Sayan Ranu
59 papers receiving 928 citations
Peers
Comparison fields: 5 of 94
- Signal Processing 306
- Artificial Intelligence 267
- Statistical and Nonlinear Physics 226
- Computer Vision and Pattern Recognition 204
- Computer Networks and Communications 192
Countries citing papers authored by Sayan Ranu
This map shows the geographic impact of Sayan Ranu'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 Sayan Ranu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sayan Ranu more than expected).
Fields of papers citing papers by Sayan Ranu
This network shows the impact of papers produced by Sayan Ranu. 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 Sayan Ranu. The network helps show where Sayan Ranu may publish in the future.
Co-authorship network of co-authors of Sayan Ranu
This figure shows the co-authorship network connecting the top 25 collaborators of Sayan Ranu. A scholar is included among the top collaborators of Sayan Ranu 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 Sayan Ranu. Sayan Ranu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 18 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 8 | |
| 6 | 1 | |
| 7 | 30 | |
| 8 | 2 | |
| 9 | 2 | |
| 10 | NeuroMLR: Robust & Reliable Route Recommendation on Road Networks | 6 |
| 11 | 4 | |
| 12 | GCOMB: Learning Budget-constrained Combinatorial Algorithms over Billion-sized Graphs | 12 |
| 13 | 5 | |
| 14 | 46 | |
| 15 | 10 | |
| 16 | 10 | |
| 17 | 94 | |
| 18 | 12 | |
| 19 | 10 | |
| 20 | 14 |
About Sayan Ranu
Sayan Ranu is a scholar working on Signal Processing, Transportation and Statistical and Nonlinear Physics, having authored 63 papers that have together received 944 indexed citations. Recurring topics across this work include Data Management and Algorithms (19 papers), Graph Theory and Algorithms (12 papers) and Advanced Graph Neural Networks (10 papers). The work is most often cited by research in Signal Processing (306 citations), Transportation (167 citations) and Statistical and Nonlinear Physics (226 citations). Sayan Ranu has collaborated with scholars based in India, United States and United Kingdom. Frequent co-authors include Ambuj K. Singh, Akhil Arora, Sainyam Galhotra, P Deepak, Aditya Telang, Sriram Raghavan, Vineet Chaoji, Rushi Bhatt, Rajeev Rastogi and Prasad Deshpande. Their work appears in journals such as Bioinformatics, Physical Chemistry Chemical Physics and The Journal of Physical Chemistry Letters.
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.