Manish Aggarwal
-
- Multi-Criteria Decision Making 40
- Forecasting Techniques and Applications 4
- Statistics and Probability top 5%
- Fuzzy Systems and Optimization 18
-
- Rough Sets and Fuzzy Logic 12
- Artificial Intelligence top 10%
- Fuzzy Logic and Control Systems 8
- Bayesian Modeling and Causal Inference 5
-
- Economic and Environmental Valuation 7
-
- Optimization and Mathematical Programming 6
- Co-authors
- M. HanmandluAli Fallah TehraniR. KrishankumarK. S. RavichandranDragan PamučarMuhammet DeveciSanjay Kumar TyagiWitold Pedrycz
- Cited by
- Management Science and Operations ResearchStatistics and ProbabilityComputational Theory and Mathematics
- Partner nations
- IndiaUnited StatesChina
In The Last Decade
Manish Aggarwal
50 papers receiving 518 citations
Peers
Comparison fields: 5 of 93
- Management Science and Operations Research 335
- Statistics and Probability 87
- Computational Theory and Mathematics 140
- Artificial Intelligence 183
- General Decision Sciences 9
Countries citing papers authored by Manish Aggarwal
This map shows the geographic impact of Manish Aggarwal'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 Manish Aggarwal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Manish Aggarwal more than expected).
Fields of papers citing papers by Manish Aggarwal
This network shows the impact of papers produced by Manish Aggarwal. 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 Manish Aggarwal. The network helps show where Manish Aggarwal may publish in the future.
Co-authorship network
The 20 scholars most cited alongside Manish Aggarwal, 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 | 2025 | 8 | |
| 2 | 2023 | 2 | |
| 3 | 2023 | 3 | |
| 4 | 2022 | 5 | |
| 5 | 2022 | 2 | |
| 6 | 2022 | 2 | |
| 7 | 2020 | 1 | |
| 8 | 2020 | 3 | |
| 9 | 2020 | 1 | |
| 10 | 2019 | 1 | |
| 11 | 2019 | 54 | |
| 12 | 2019 | 10 | |
| 13 | 2019 | 16 | |
| 14 | 2019 | 1 | |
| 15 | 2018 | 14 | |
| 16 | 2018 | 8 | |
| 17 | 2018 | 2 | |
| 18 | 2018 | 4 | |
| 19 | 2018 | 0 | |
| 20 | 2016 | 8 |
About Manish Aggarwal
Manish Aggarwal is a scholar working on Management Science and Operations Research, Statistics and Probability and Computational Theory and Mathematics, having authored 52 papers that have together received 534 indexed citations. Recurring topics across this work include Multi-Criteria Decision Making (40 papers), Fuzzy Systems and Optimization (18 papers), Rough Sets and Fuzzy Logic (12 papers), Fuzzy Logic and Control Systems (8 papers), Economic and Environmental Valuation (7 papers), Optimization and Mathematical Programming (6 papers), Bayesian Modeling and Causal Inference (5 papers) and Forecasting Techniques and Applications (4 papers). The work is most often cited by research in Management Science and Operations Research (335 citations), Statistics and Probability (87 citations) and Computational Theory and Mathematics (140 citations). Manish Aggarwal has collaborated with scholars based in India, United States and China. Frequent co-authors include M. Hanmandlu, Ali Fallah Tehrani, R. Krishankumar, K. S. Ravichandran, Dragan Pamučar, Muhammet Deveci, Sanjay Kumar Tyagi, K. S. Ravichandran, Witold Pedrycz and Guanrong Chen. Their work appears in journals such as Expert Systems with Applications, IEEE Access and Renewable Energy.
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.