B. Aditya Prakash
- Statistical and Nonlinear Physics top 0.5%
- Artificial Intelligence top 2%
- Computer Networks and Communications top 2%
- Sociology and Political Science top 5%
- Information Systems top 2%
- Co-authors
- Christos FaloutsosMichalis FaloutsosJilles VreekenHanghang TongLei LiTina Eliassi‐RadNicholas C. VallerNaren Ramakrishnan
- Topics
- Complex Network Analysis Techniques (50 papers)Opinion Dynamics and Social Influence (24 papers)COVID-19 epidemiological studies (16 papers)
- Partner nations
- United StatesIndiaJapan
In The Last Decade
B. Aditya Prakash
98 papers receiving 2.3k citations
Peers
Comparison fields: 5 of 127
- Statistical and Nonlinear Physics 1.4k
- Artificial Intelligence 627
- Computer Networks and Communications 459
- Sociology and Political Science 371
- Information Systems 318
Countries citing papers authored by B. Aditya Prakash
This map shows the geographic impact of B. Aditya Prakash'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 B. Aditya Prakash with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites B. Aditya Prakash more than expected).
Fields of papers citing papers by B. Aditya Prakash
This network shows the impact of papers produced by B. Aditya Prakash. 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 B. Aditya Prakash. The network helps show where B. Aditya Prakash may publish in the future.
Co-authorship network of co-authors of B. Aditya Prakash
This figure shows the co-authorship network connecting the top 25 collaborators of B. Aditya Prakash. A scholar is included among the top collaborators of B. Aditya Prakash 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 B. Aditya Prakash. B. Aditya Prakash is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 0 | |
| 3 | 19 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 7 | |
| 7 | 11 | |
| 8 | 3 | |
| 9 | 1 | |
| 10 | 1 | |
| 11 | 5 | |
| 12 | 16 | |
| 13 | 42 | |
| 14 | 18 | |
| 15 | 2 | |
| 16 | 147 | |
| 17 | Understanding and Managing Propagation on Large Networks -- Theory, Algorithms, and Models | 1 |
| 18 | Time Series Clustering: Complex is Simpler! | 42 |
| 19 | Genetic diversity analysis and cytogenetic profiling of Assamese buffaloes from North-East India | 11 |
| 20 | 22 |
About B. Aditya Prakash
B. Aditya Prakash is a scholar working on Statistical and Nonlinear Physics, Modeling and Simulation and Signal Processing, having authored 103 papers that have together received 2.4k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (50 papers), Opinion Dynamics and Social Influence (24 papers) and COVID-19 epidemiological studies (16 papers). The work is most often cited by research in Statistical and Nonlinear Physics (1.4k citations), Modeling and Simulation (240 citations) and Signal Processing (255 citations). B. Aditya Prakash has collaborated with scholars based in United States, India and Japan. Frequent co-authors include Christos Faloutsos, Michalis Faloutsos, Jilles Vreeken, Hanghang Tong, Lei Li, Tina Eliassi‐Rad, Nicholas C. Valler, Naren Ramakrishnan, Yasuko Matsubara and Yasushi Sakurai. Their work appears in journals such as Scientific Reports, Food Chemistry and IEEE Journal on Selected Areas in Communications.
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.