Shibani Ghosh
- Electrical and Electronic Engineering top 10%
- Control and Systems Engineering top 5%
- Renewable Energy, Sustainability and the Environment
- Artificial Intelligence
- Automotive Engineering
- Co-authors
- Saifur RahmanManisa PipattanasompornSantosh VedaMichael BlonskyBenjamin KroposkiKillian McKennaAdarsh NagarajanJal Desai
- Topics
- Optimal Power Flow Distribution (7 papers)Smart Grid Energy Management (7 papers)Microgrid Control and Optimization (6 papers)
- Cited by
- Energy Engineering and Power TechnologyControl and Systems EngineeringElectrical and Electronic Engineering
- Journals
- IEEE Transactions on Sustainable EnergyIBM Journal of Research and DevelopmentInternational Journal of Advanced Computer Science and Applications
- Partner nations
- United StatesBangladeshSweden
In The Last Decade
Shibani Ghosh
16 papers receiving 406 citations
Peers
Comparison fields: 5 of 42
- Electrical and Electronic Engineering 363
- Control and Systems Engineering 247
- Renewable Energy, Sustainability and the Environment 75
- Artificial Intelligence 44
- Automotive Engineering 43
Countries citing papers authored by Shibani Ghosh
This map shows the geographic impact of Shibani Ghosh'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 Shibani Ghosh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shibani Ghosh more than expected).
Fields of papers citing papers by Shibani Ghosh
This network shows the impact of papers produced by Shibani Ghosh. 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 Shibani Ghosh. The network helps show where Shibani Ghosh may publish in the future.
Co-authorship network of co-authors of Shibani Ghosh
This figure shows the co-authorship network connecting the top 25 collaborators of Shibani Ghosh. A scholar is included among the top collaborators of Shibani Ghosh 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 Shibani Ghosh. Shibani Ghosh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 2 | |
| 3 | 26 | |
| 4 | 24 | |
| 5 | 1 | |
| 6 | 8 | |
| 7 | 5 | |
| 8 | 3 | |
| 9 | 45 | |
| 10 | 9 | |
| 11 | 13 | |
| 12 | 227 | |
| 13 | 37 | |
| 14 | 5 | |
| 15 | 4 | |
| 16 | 7 |
About Shibani Ghosh
Shibani Ghosh is a scholar working on Control and Systems Engineering, Energy Engineering and Power Technology and Automotive Engineering, having authored 16 papers that have together received 421 indexed citations. Recurring topics across this work include Optimal Power Flow Distribution (7 papers), Smart Grid Energy Management (7 papers) and Microgrid Control and Optimization (6 papers). The work is most often cited by research in Energy Engineering and Power Technology (34 citations), Control and Systems Engineering (247 citations) and Electrical and Electronic Engineering (363 citations). Shibani Ghosh has collaborated with scholars based in United States, Bangladesh and Sweden. Frequent co-authors include Saifur Rahman, Manisa Pipattanasomporn, Santosh Veda, Michael Blonsky, Benjamin Kroposki, Killian McKenna, Adarsh Nagarajan, Jal Desai, Fei Ding and Ajoy Kumar. Their work appears in journals such as IEEE Transactions on Sustainable Energy, IBM Journal of Research and Development and International Journal of Advanced Computer Science and Applications.
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.