Santosh Nannuru
About
In The Last Decade
Santosh Nannuru
35 papers receiving 804 citations
Peers
Comparison fields: 5 of 40
- Signal Processing 503
- Oceanography 258
- Electrical and Electronic Engineering 234
- Artificial Intelligence 156
- Aerospace Engineering 125
Countries citing papers authored by Santosh Nannuru
This map shows the geographic impact of Santosh Nannuru'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 Santosh Nannuru with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Santosh Nannuru more than expected).
Fields of papers citing papers by Santosh Nannuru
This network shows the impact of papers produced by Santosh Nannuru. 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 Santosh Nannuru. The network helps show where Santosh Nannuru may publish in the future.
Co-authorship network of co-authors of Santosh Nannuru
This figure shows the co-authorship network connecting the top 25 collaborators of Santosh Nannuru. A scholar is included among the top collaborators of Santosh Nannuru 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 Santosh Nannuru. Santosh Nannuru 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 | 3 | |
| 4 | 2 | |
| 5 | 69 | |
| 6 | 22 | |
| 7 | 60 | |
| 8 | 2 | |
| 9 | 10 | |
| 10 | 51 | |
| 11 | Multi-frequency sparse Bayesian learning with uncertainty models. | 4 |
| 12 | 4 | |
| 13 | 1 | |
| 14 | Multisnapshot Sparse Bayesian Learning for DOA | 190 |
| 15 | 12 | |
| 16 | 2 | |
| 17 | 6 | |
| 18 | Multi-Bernoulli filter for superpositional sensors | 6 |
| 19 | 35 | |
| 20 | Multi-target tracking for measurement models with additive contributions | 24 |
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.