Amulya Yadav
- Statistical and Nonlinear Physics top 10%
- General Health Professions
- Artificial Intelligence
- Information Systems
- Sociology and Political Science
- Co-authors
- Milind TambeEric RiceBryan WilderRobin PeteringHaifeng XuJaih CraddockAlbert Xin JiangHau Chan
- Topics
- Homelessness and Social Issues (16 papers)Complex Network Analysis Techniques (8 papers)Peer-to-Peer Network Technologies (5 papers)
- Partner nations
- United StatesIndiaCanada
In The Last Decade
Amulya Yadav
33 papers receiving 222 citations
Peers
Comparison fields: 5 of 72
- Statistical and Nonlinear Physics 67
- General Health Professions 56
- Artificial Intelligence 52
- Information Systems 39
- Sociology and Political Science 36
Countries citing papers authored by Amulya Yadav
This map shows the geographic impact of Amulya Yadav'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 Amulya Yadav with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amulya Yadav more than expected).
Fields of papers citing papers by Amulya Yadav
This network shows the impact of papers produced by Amulya Yadav. 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 Amulya Yadav. The network helps show where Amulya Yadav may publish in the future.
Co-authorship network of co-authors of Amulya Yadav
This figure shows the co-authorship network connecting the top 25 collaborators of Amulya Yadav. A scholar is included among the top collaborators of Amulya Yadav 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 Amulya Yadav. Amulya Yadav is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 9 | |
| 5 | 10 | |
| 6 | 2 | |
| 7 | Improving lives of indebted farmers using deep learning: Predicting agricultural produce prices using convolutional neural networks | 1 |
| 8 | 1 | |
| 9 | 4 | |
| 10 | 1 | |
| 11 | 26 | |
| 12 | Explanation Systems for Influence Maximization Algorithms. | 1 |
| 13 | 24 | |
| 14 | 19 | |
| 15 | 0 | |
| 16 | 1 | |
| 17 | 34 | |
| 18 | 1 | |
| 19 | PSINET - An Online POMDP Solver for HIV Prevention in Homeless Populations | 1 |
| 20 | 13 |
About Amulya Yadav
Amulya Yadav is a scholar working on General Health Professions, Statistical and Nonlinear Physics and Health Information Management, having authored 35 papers that have together received 229 indexed citations. Recurring topics across this work include Homelessness and Social Issues (16 papers), Complex Network Analysis Techniques (8 papers) and Peer-to-Peer Network Technologies (5 papers). The work is most often cited by research in Statistical and Nonlinear Physics (67 citations), Health Informatics (5 citations) and Computer Science Applications (16 citations). Amulya Yadav has collaborated with scholars based in United States, India and Canada. Frequent co-authors include Milind Tambe, Eric Rice, Bryan Wilder, Robin Petering, Haifeng Xu, Jaih Craddock, Albert Xin Jiang, Hau Chan, Nicole Immorlica and Dongwon Lee. Their work appears in journals such as AI Magazine, Journal of the Society for Social Work and Research and Multiagent and Grid Systems.
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.