Vikram Aditya

494 citations
24 papers · 187 indexed · h-index 7

Impact in

Papers in

Vikram Aditya

17 papers receiving 149 citations

Peers

Vikram Aditya
Comparison fields: 5 of 70
  • Signal Processing 25
  • Artificial Intelligence 69
  • Ecological Modeling 9
  • Computer Networks and Communications 47
  • Computer Vision and Pattern Recognition 35
Replace Debarun Kar with:
Debarun Kar United States
Gang He China
Mayank Lahiri United States
Yudong Li China
Daniel Moraes Brazil
Frederick Maier United States
Klaus Meyer-Wegener Germany
David Sánchez-Rodríguez Spain
Mathematisch-Naturwissenschaftlichen Fakultät
Yongsu Park South Korea
Vikram Aditya relative to Debarun Kar United States Debarun Kar's profile →
Citations per field
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Citations per year

Countries citing papers authored by Vikram Aditya

Since Specialization
Citations

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

Fields of papers citing papers by Vikram Aditya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 17 scholars most cited alongside Vikram Aditya, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Vikram Aditya Line = papers co-authored together Vikram Aditya links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20240
4 20221
5 20221
6 20226
7
Occurrence of Indian Giant Flying Squirrel in the northern Eastern Ghats of Andhra Pradesh, India
20212
8 202116
9 20201
10 202046
11 20207
12 202059
13 201811
14 20176
15 20162
16 20163
17 20166
18 19690
19 19692
20
Histopathology and histochemistry of insects treated with chemosterilants. II. On the studies of DNA in active testes of Poicelocerus pictus (Orthoptera: Acrididae) treated with apholate.
19690

About Vikram Aditya

Vikram Aditya is a scholar working on Ecology, Nature and Landscape Conservation, Ecological Modeling, Modeling and Simulation and Ecology, Evolution, Behavior and Systematics, having authored 24 papers that have together received 187 indexed citations. Recurring topics across this work include Wildlife Ecology and Conservation (9 papers), Animal Ecology and Behavior Studies (4 papers), Insect Pest Control Strategies (3 papers), Ecology and Vegetation Dynamics Studies (3 papers), Conservation, Biodiversity, and Resource Management (2 papers), Agricultural Practices and Plant Genetics (2 papers), Bat Biology and Ecology Studies (2 papers) and Anomaly Detection Techniques and Applications (2 papers). The work is most often cited by research in Signal Processing (25 citations), Artificial Intelligence (69 citations), Ecological Modeling (9 citations), Computer Networks and Communications (47 citations) and Computer Vision and Pattern Recognition (35 citations). Vikram Aditya has collaborated with scholars based in India, Germany and United States. Frequent co-authors include Mohana, T. Ganesh, Ayush Jain, Harsh Jain, Shailendra Ratre, Jennifer Solomon, Mukesh Sharma, Vijay Parihar, Chhavi Chauhan and S. C. Saxena. Their work appears in journals such as Biotropica, AMBIO, Scientific Reports, Operative Neurosurgery and Current Science.

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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