Medha Atre
- Artificial Intelligence top 10%
- Computer Networks and Communications top 10%
- Computer Vision and Pattern Recognition top 10%
- Hardware and Architecture top 10%
- Electrical and Electronic Engineering
- Co-authors
- James HendlerMohammed J. ZakiVineet ChaojiVishwani D. AgrawalJagannathan SrinivasanGregory Todd WilliamsSandeep K. ShuklaZhe Wu
- Topics
- Semantic Web and Ontologies (9 papers)Advanced Database Systems and Queries (9 papers)Data Management and Algorithms (6 papers)
- Journals
- Journal of Web SemanticsarXiv (Cornell University)Proceedings of the ACM Web Conference 2022
- Partner nations
- United StatesIndia
In The Last Decade
Medha Atre
13 papers receiving 209 citations
Peers
Comparison fields: 5 of 19
- Artificial Intelligence 126
- Computer Networks and Communications 118
- Computer Vision and Pattern Recognition 72
- Hardware and Architecture 68
- Electrical and Electronic Engineering 67
Countries citing papers authored by Medha Atre
This map shows the geographic impact of Medha Atre'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 Medha Atre with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Medha Atre more than expected).
Fields of papers citing papers by Medha Atre
This network shows the impact of papers produced by Medha Atre. 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 Medha Atre. The network helps show where Medha Atre may publish in the future.
Co-authorship network of co-authors of Medha Atre
This figure shows the co-authorship network connecting the top 25 collaborators of Medha Atre. A scholar is included among the top collaborators of Medha Atre 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 Medha Atre. Medha Atre 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 | 4 | |
| 3 | 3 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 3 | |
| 7 | 9 | |
| 8 | 8 | |
| 9 | 100 | |
| 10 | 7 | |
| 11 | 2 | |
| 12 | BitMat: a main-memory bit matrix of RDF triples for conjunctive triple pattern queries | 25 |
| 13 | 30 | |
| 14 | 39 |
About Medha Atre
Medha Atre is a scholar working on Signal Processing, Computer Networks and Communications and Artificial Intelligence, having authored 14 papers that have together received 233 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (9 papers), Advanced Database Systems and Queries (9 papers) and Data Management and Algorithms (6 papers). The work is most often cited by research in Hardware and Architecture (68 citations), Computer Networks and Communications (118 citations) and Signal Processing (48 citations). Medha Atre has collaborated with scholars based in United States and India. Frequent co-authors include James Hendler, Mohammed J. Zaki, Vineet Chaoji, Vishwani D. Agrawal, Jagannathan Srinivasan, Gregory Todd Williams, Sandeep K. Shukla, Zhe Wu, Vladimir Kolovski and Souripriya Das. Their work appears in journals such as Journal of Web Semantics, arXiv (Cornell University) and Proceedings of the ACM Web Conference 2022.
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.