Irani Majumder
- Electrical and Electronic Engineering
- Artificial Intelligence top 5%
- Renewable Energy, Sustainability and the Environment top 10%
- Control and Systems Engineering
- Management Science and Operations Research
- Co-authors
- Niranjan NayakManoja Kumar BeheraP.K. DashRanjeeta BisoiSnehamoy DharSthita Prajna MishraRenu SharmaPravat Kumar Rout
- Topics
- Energy Load and Power Forecasting (6 papers)Microgrid Control and Optimization (5 papers)Machine Learning and ELM (5 papers)
- Cited by
- Renewable Energy, Sustainability and the EnvironmentArtificial IntelligenceEnergy Engineering and Power Technology
- Partner nations
- IndiaMalaysiaUnited States
In The Last Decade
Irani Majumder
13 papers receiving 334 citations
Peers
Comparison fields: 5 of 45
- Electrical and Electronic Engineering 252
- Artificial Intelligence 251
- Renewable Energy, Sustainability and the Environment 171
- Control and Systems Engineering 40
- Management Science and Operations Research 31
Countries citing papers authored by Irani Majumder
This map shows the geographic impact of Irani Majumder'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 Irani Majumder with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Irani Majumder more than expected).
Fields of papers citing papers by Irani Majumder
This network shows the impact of papers produced by Irani Majumder. 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 Irani Majumder. The network helps show where Irani Majumder may publish in the future.
Co-authorship network of co-authors of Irani Majumder
This figure shows the co-authorship network connecting the top 25 collaborators of Irani Majumder. A scholar is included among the top collaborators of Irani Majumder 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 Irani Majumder. Irani Majumder is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 17 | |
| 2 | 1 | |
| 3 | 16 | |
| 4 | 14 | |
| 5 | 3 | |
| 6 | 24 | |
| 7 | 72 | |
| 8 | 163 | |
| 9 | 23 | |
| 10 | 1 | |
| 11 | 4 | |
| 12 | 3 | |
| 13 | 1 |
About Irani Majumder
Irani Majumder is a scholar working on Energy Engineering and Power Technology, Renewable Energy, Sustainability and the Environment and Artificial Intelligence, having authored 13 papers that have together received 342 indexed citations. Recurring topics across this work include Energy Load and Power Forecasting (6 papers), Microgrid Control and Optimization (5 papers) and Machine Learning and ELM (5 papers). The work is most often cited by research in Renewable Energy, Sustainability and the Environment (171 citations), Artificial Intelligence (251 citations) and Energy Engineering and Power Technology (17 citations). Irani Majumder has collaborated with scholars based in India, Malaysia and United States. Frequent co-authors include Niranjan Nayak, Manoja Kumar Behera, P.K. Dash, Ranjeeta Bisoi, Snehamoy Dhar, Sthita Prajna Mishra, Renu Sharma, Pravat Kumar Rout, Subhransu Ranjan Samantaray and Rohit Sharma. Their work appears in journals such as Energy Conversion and Management, Applied Soft Computing and Neural Computing 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.