Kusum Lata
- Global and Planetary Change top 10%
- Public Health, Environmental and Occupational Health
- Nature and Landscape Conservation
- Endocrinology, Diabetes and Metabolism
- Modeling and Simulation top 10%
- Co-authors
- A. K. MisraJ.B. ShuklaManisha SharmaSatya Narayan PatelR. S. SangwanSudhir P. SinghUmesh SinghVinod Kumar
- Topics
- Forest Management and Policy (8 papers)Mathematical and Theoretical Epidemiology and Ecology Models (8 papers)Ecology and Vegetation Dynamics Studies (4 papers)
In The Last Decade
Kusum Lata
24 papers receiving 389 citations
Peers
Comparison fields: 5 of 95
- Global and Planetary Change 162
- Public Health, Environmental and Occupational Health 99
- Nature and Landscape Conservation 52
- Endocrinology, Diabetes and Metabolism 43
- Modeling and Simulation 38
Countries citing papers authored by Kusum Lata
This map shows the geographic impact of Kusum Lata'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 Kusum Lata with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kusum Lata more than expected).
Fields of papers citing papers by Kusum Lata
This network shows the impact of papers produced by Kusum Lata. 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 Kusum Lata. The network helps show where Kusum Lata may publish in the future.
Co-authorship network of co-authors of Kusum Lata
This figure shows the co-authorship network connecting the top 25 collaborators of Kusum Lata. A scholar is included among the top collaborators of Kusum Lata 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 Kusum Lata. Kusum Lata is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | 7 | |
| 3 | 5 | |
| 4 | 5 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | Factors Associated With Nutritional Status of Human Immunodeficiency Virus Infected Children Hawassa, Ethiopia | 2 |
| 8 | 12 | |
| 9 | 13 | |
| 10 | 13 | |
| 11 | 0 | |
| 12 | 10 | |
| 13 | 48 | |
| 14 | 53 | |
| 15 | 19 | |
| 16 | 39 | |
| 17 | 22 | |
| 18 | 28 | |
| 19 | 4 | |
| 20 | 10 |
About Kusum Lata
Kusum Lata is a scholar working on Global and Planetary Change, Modeling and Simulation and Nature and Landscape Conservation, having authored 25 papers that have together received 403 indexed citations. Recurring topics across this work include Forest Management and Policy (8 papers), Mathematical and Theoretical Epidemiology and Ecology Models (8 papers) and Ecology and Vegetation Dynamics Studies (4 papers). The work is most often cited by research in Modeling and Simulation (38 citations), Global and Planetary Change (162 citations) and Nature and Landscape Conservation (52 citations). Kusum Lata has collaborated with scholars based in India, Algeria and Iraq. Frequent co-authors include A. K. Misra, J.B. Shukla, Manisha Sharma, Satya Narayan Patel, R. S. Sangwan, Sudhir P. Singh, Umesh Singh, Vinod Kumar, Meena Krishania and Satya N. Mishra. Their work appears in journals such as Bioresource Technology, Chaos Solitons & Fractals and Applied Mathematical Modelling.
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.