Abhiroop Ghosh
Impact in
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- Advanced Multi-Objective Optimization Algorithms
- Artificial Intelligence top 5%
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
Papers in
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- Metaheuristic Optimization Algorithms Research 4
- Evolutionary Algorithms and Applications 2
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- Advanced Multi-Objective Optimization Algorithms 4
- Co-authors
- Krishnendu Sanyal (3 shared papers)Anupam Trivedi (1 shared paper)Dipti Srinivasan (1 shared paper)Swagatam Das (1 shared paper)Shounak Datta (1 shared paper)Kalyanmoy Deb (4 shared papers)Ronald C. Averill (3 shared papers)Erik D. Goodman (3 shared papers)
- Journals
- IEEE Transactions on Evolutionary Computation (2 papers)Econometrica (2 papers)Engineering Optimization (1 paper)Information Sciences (1 paper)Journal of the American Statistical Association (1 paper)
- Partner nations
- IndiaUnited StatesSingapore
In The Last Decade
Abhiroop Ghosh
14 papers receiving 520 citations
Abhiroop Ghosh's Hit Papers
Peers
Comparison fields: 5 of 70
- Computational Theory and Mathematics 344
- Artificial Intelligence 326
- Management Science and Operations Research 68
- Industrial and Manufacturing Engineering 47
- Statistics, Probability and Uncertainty 23
Countries citing papers authored by Abhiroop Ghosh
This map shows the geographic impact of Abhiroop 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 Abhiroop Ghosh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Abhiroop Ghosh more than expected).
Fields of papers citing papers by Abhiroop Ghosh
This network shows the impact of papers produced by Abhiroop 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 Abhiroop Ghosh. The network helps show where Abhiroop Ghosh may publish in the future.
Co-authors
The 15 scholars most cited alongside Abhiroop Ghosh, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | A Survey of Multiobjective Evolutionary Algorithms based on Decomposition Hit paper breakdown → | 2016 | 431 |
| 2 | 2016 | 22 | |
| 3 | 1966 | 19 | |
| 4 | 1970 | 15 | |
| 5 | 1960 | 14 | |
| 6 | 2020 | 7 | |
| 7 | 2023 | 6 | |
| 8 | 2022 | 5 | |
| 9 | 1981 | 4 | |
| 10 | 1965 | 3 | |
| 11 | 2021 | 3 | |
| 12 | 2022 | 3 | |
| 13 | 1985 | 2 | |
| 14 | 2016 | 2 | |
| 15 | 1965 | 1 | |
| 16 | 1985 | 0 |
About Abhiroop Ghosh
Abhiroop Ghosh is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Control and Systems Engineering, Management Science and Operations Research and Economics and Econometrics, having authored 16 papers that have together received 537 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (4 papers), Advanced Multi-Objective Optimization Algorithms (4 papers), Evolutionary Algorithms and Applications (2 papers), Advanced Control Systems Optimization (2 papers), Stock Market Forecasting Methods (1 paper), Housing Market and Economics (1 paper), Multi-Criteria Decision Making (1 paper) and Regional Economics and Spatial Analysis (1 paper). The work is most often cited by research in Computational Theory and Mathematics (344 citations), Artificial Intelligence (326 citations), Management Science and Operations Research (68 citations), Industrial and Manufacturing Engineering (47 citations) and Statistics, Probability and Uncertainty (23 citations). Abhiroop Ghosh has collaborated with scholars based in India, United States and Singapore. Frequent co-authors include Krishnendu Sanyal, Anupam Trivedi, Dipti Srinivasan, Swagatam Das, Shounak Datta, Kalyanmoy Deb, Ronald C. Averill, Erik D. Goodman, A. A. Walters and Dimitar Filev. Their work appears in journals such as IEEE Transactions on Evolutionary Computation, Econometrica, Engineering Optimization, Information Sciences and Journal of the American Statistical Association.
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.