Rajib Maity

3.2k total citations
114 papers, 2.2k citations indexed

About

Rajib Maity is a scholar working on Global and Planetary Change, Environmental Engineering and Atmospheric Science. According to data from OpenAlex, Rajib Maity has authored 114 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 88 papers in Global and Planetary Change, 47 papers in Environmental Engineering and 44 papers in Atmospheric Science. Recurrent topics in Rajib Maity's work include Climate variability and models (66 papers), Hydrology and Drought Analysis (44 papers) and Hydrology and Watershed Management Studies (33 papers). Rajib Maity is often cited by papers focused on Climate variability and models (66 papers), Hydrology and Drought Analysis (44 papers) and Hydrology and Watershed Management Studies (33 papers). Rajib Maity collaborates with scholars based in India, Germany and United States. Rajib Maity's co-authors include D. Nagesh Kumar, Kironmala Chanda, Riya Dutta, Mayank Suman, Aman Srivastava, Ashish Sharma, Harald Kunstmann, M. Janga Reddy, Rao S. Govindaraju and Meenu Ramadas and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Geophysical Research Atmospheres and The Science of The Total Environment.

In The Last Decade

Rajib Maity

108 papers receiving 2.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Rajib Maity India 28 1.5k 819 733 599 231 114 2.2k
Milan Gocić Serbia 24 2.1k 1.4× 742 0.9× 858 1.2× 631 1.1× 238 1.0× 57 3.0k
Turgay Partal Türkiye 15 1.3k 0.9× 971 1.2× 791 1.1× 434 0.7× 148 0.6× 36 2.0k
Deg‐Hyo Bae South Korea 24 1.6k 1.1× 695 0.8× 1.2k 1.6× 727 1.2× 155 0.7× 147 2.3k
Rasoul Mirabbasi Iran 27 1.6k 1.1× 529 0.6× 831 1.1× 332 0.6× 251 1.1× 81 2.1k
N. K. Goel India 25 1.6k 1.1× 626 0.8× 992 1.4× 617 1.0× 182 0.8× 62 2.3k
Sobri Harun Malaysia 26 1.5k 1.0× 688 0.8× 872 1.2× 543 0.9× 299 1.3× 108 2.4k
Zhiyong Liu China 32 1.8k 1.2× 606 0.7× 955 1.3× 677 1.1× 173 0.7× 101 2.8k
Yagob Dinpashoh Iran 26 2.6k 1.7× 705 0.9× 1.2k 1.6× 706 1.2× 295 1.3× 59 3.5k
Ahmad Fakheri Fard Iran 24 1.7k 1.2× 691 0.8× 887 1.2× 247 0.4× 203 0.9× 72 2.3k
Sutat Weesakul Thailand 19 1.2k 0.8× 637 0.8× 552 0.8× 456 0.8× 132 0.6× 48 1.8k

Countries citing papers authored by Rajib Maity

Since Specialization
Citations

This map shows the geographic impact of Rajib Maity'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 Rajib Maity with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rajib Maity more than expected).

Fields of papers citing papers by Rajib Maity

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rajib Maity. 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 Rajib Maity. The network helps show where Rajib Maity may publish in the future.

Co-authorship network of co-authors of Rajib Maity

This figure shows the co-authorship network connecting the top 25 collaborators of Rajib Maity. A scholar is included among the top collaborators of Rajib Maity 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 Rajib Maity. Rajib Maity is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Srivastava, Aman, Avinash C. Pandey, & Rajib Maity. (2025). Comparative multi-index analysis of existing drought typology and environmental droughts in a climate-stressed region. Scientific Reports. 15(1). 34349–34349. 1 indexed citations
2.
Hamid, Saima, et al.. (2025). Unfolding extreme precipitation and flood events in the Kashmir Himalaya. International Journal of River Basin Management. 1–18.
3.
Srivastava, Aman, et al.. (2025). High-resolution agricultural drought hazard mapping using the potential of geospatial data and machine learning approaches. Environmental Monitoring and Assessment. 197(11). 1195–1195.
4.
Maity, Rajib, et al.. (2025). Short-term satellite soil moisture for agricultural drought characterization over Godavari basin, India. Environmental Monitoring and Assessment. 197(5). 606–606.
5.
Maity, Rajib, et al.. (2024). Revolutionizing the future of hydrological science: Impact of machine learning and deep learning amidst emerging explainable AI and transfer learning. SHILAP Revista de lepidopterología. 24. 100206–100206. 20 indexed citations
6.
Maity, Rajib, et al.. (2024). Coastal vulnerability considering combined effect of tropical cyclones and future sea level rise. Journal of Coastal Conservation. 28(3).
7.
Maity, Rajib, et al.. (2023). Unfolding unique features of precipitation-temperature scaling across India. Atmospheric Research. 284. 106601–106601. 11 indexed citations
8.
Maity, Rajib, et al.. (2023). Precipitation-based climate change hotspots across India through a Multi-model assessment from CMIP6. Journal of Hydrology. 623. 129805–129805. 22 indexed citations
9.
Maity, Rajib, et al.. (2023). Future projection of climate extremes across contiguous northeast India and Bangladesh. Scientific Reports. 13(1). 15616–15616. 26 indexed citations
10.
Srivastava, Aman, et al.. (2023). Modeling climate change impacts on vector-borne disease using machine learning models: Case study of Visceral leishmaniasis (Kala-azar) from Indian state of Bihar. Expert Systems with Applications. 237. 121490–121490. 20 indexed citations
11.
Srivastava, Aman & Rajib Maity. (2023). Assessing the Potential of AI–ML in Urban Climate Change Adaptation and Sustainable Development. Sustainability. 15(23). 16461–16461. 31 indexed citations
12.
Maity, Rajib, et al.. (2023). Climate change may cause oasification or desertification both: an analysis based on the spatio-temporal change in aridity across India. Theoretical and Applied Climatology. 155(2). 1167–1184. 7 indexed citations
13.
Maity, Rajib, et al.. (2023). Impacts of hydrometeorological factors on discharge simulation in the North West Himalayas: a SUFI-2 algorithm-driven investigation using the SWAT model. Environmental Monitoring and Assessment. 195(11). 1366–1366. 5 indexed citations
14.
Dutta, Riya, Kironmala Chanda, & Rajib Maity. (2022). Future of solar energy potential in a changing climate across the world: A CMIP6 multi-model ensemble analysis. Renewable Energy. 188. 819–829. 114 indexed citations
15.
Maity, Rajib, et al.. (2021). Changing spectral patterns of long‐term drought propensity in Iran through reliability–resilience–vulnerability‐based Drought Management Index. International Journal of Climatology. 42(8). 4147–4163. 3 indexed citations
16.
Maity, Rajib, et al.. (2020). High-resolution one-day probable maximum precipitation dataset across India and its future-projected changes over India. SHILAP Revista de lepidopterología. 30. 105525–105525. 5 indexed citations
17.
Maity, Rajib, et al.. (2020). Estimation of Probable Maximum Precipitation in the context of climate change. MethodsX. 7. 100904–100904. 16 indexed citations
18.
Maity, Rajib, et al.. (2020). Long-lead Prediction of ENSO Modoki Index using Machine Learning algorithms. Scientific Reports. 10(1). 365–365. 33 indexed citations
19.
Reddy, M. Janga & Rajib Maity. (2007). Regional Rainfall Forecasting using Large Scale Climate Teleconnections and Artificial Intelligence Techniques. Journal of Intelligent Systems. 16(4). 307–322. 39 indexed citations
20.
Kumar, D. Nagesh, M. Janga Reddy, & Rajib Maity. (2005). Regional Rainfall Forecasting using Large Scale Climate Teleconnections and Evolutionary Algorithms. Indian International Conference on Artificial Intelligence. 1169–1182. 2 indexed citations

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.

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