Bhushan Mandhani
- Artificial Intelligence top 10%
- Computer Networks and Communications top 10%
- Signal Processing top 5%
- Information Systems top 10%
- Management Science and Operations Research top 10%
- Co-authors
- Dan SuciuChris RéNilesh DalviKrishna KummamuruSachindra JoshiMarina MeilăStephen Soderland
- Topics
- Semantic Web and Ontologies (3 papers)Image Retrieval and Classification Techniques (2 papers)Natural Language Processing Techniques (2 papers)
- Journals
- Very Large Data BasesNational Conference on Artificial IntelligenceInternational Conference on Artificial Intelligence and Statistics
- Partner nations
- United StatesIndiaLebanon
In The Last Decade
Bhushan Mandhani
6 papers receiving 257 citations
Peers
Comparison fields: 5 of 33
- Artificial Intelligence 191
- Computer Networks and Communications 163
- Signal Processing 154
- Information Systems 52
- Management Science and Operations Research 42
Countries citing papers authored by Bhushan Mandhani
This map shows the geographic impact of Bhushan Mandhani'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 Bhushan Mandhani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bhushan Mandhani more than expected).
Fields of papers citing papers by Bhushan Mandhani
This network shows the impact of papers produced by Bhushan Mandhani. 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 Bhushan Mandhani. The network helps show where Bhushan Mandhani may publish in the future.
Co-authorship network of co-authors of Bhushan Mandhani
This figure shows the co-authorship network connecting the top 25 collaborators of Bhushan Mandhani. A scholar is included among the top collaborators of Bhushan Mandhani 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 Bhushan Mandhani. Bhushan Mandhani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Tractable Search for Learning Exponential Models of Rankings | 25 |
| 2 | 0 | |
| 3 | Moving from Textual Relations to Ontologized Relations. | 14 |
| 4 | Query caching and view selection for XML databases | 68 |
| 5 | 129 | |
| 6 | 11 | |
| 7 | 35 |
About Bhushan Mandhani
Bhushan Mandhani is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 7 papers that have together received 282 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (3 papers), Image Retrieval and Classification Techniques (2 papers) and Natural Language Processing Techniques (2 papers). The work is most often cited by research in Signal Processing (154 citations), Computer Networks and Communications (163 citations) and Artificial Intelligence (191 citations). Bhushan Mandhani has collaborated with scholars based in United States, India and Lebanon. Frequent co-authors include Dan Suciu, Chris Ré, Nilesh Dalvi, Krishna Kummamuru, Sachindra Joshi, Marina Meilă and Stephen Soderland. Their work appears in journals such as Very Large Data Bases, National Conference on Artificial Intelligence and International Conference on Artificial Intelligence and Statistics.
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.