Vijay Shanker
- Artificial Intelligence top 10%
- Molecular Biology
- Information Systems top 10%
- Cancer Research
- Software top 10%
- Topics
- Natural Language Processing Techniques (7 papers)Topic Modeling (6 papers)Biomedical Text Mining and Ontologies (3 papers)
- Journals
- SHILAP Revista de lepidopterologíaJournal of Biomedical Materials Research Part AComputers in Biology and Medicine
- Partner nations
- United StatesIndiaSwitzerland
In The Last Decade
Vijay Shanker
19 papers receiving 300 citations
Peers
Comparison fields: 5 of 79
- Artificial Intelligence 179
- Molecular Biology 135
- Information Systems 66
- Cancer Research 31
- Software 26
Countries citing papers authored by Vijay Shanker
This map shows the geographic impact of Vijay Shanker'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 Vijay Shanker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vijay Shanker more than expected).
Fields of papers citing papers by Vijay Shanker
This network shows the impact of papers produced by Vijay Shanker. 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 Vijay Shanker. The network helps show where Vijay Shanker may publish in the future.
Co-authorship network of co-authors of Vijay Shanker
This figure shows the co-authorship network connecting the top 25 collaborators of Vijay Shanker. A scholar is included among the top collaborators of Vijay Shanker 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 Vijay Shanker. Vijay Shanker is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 36 | |
| 5 | Large Biomedical Question Answering Models with ALBERT and ELECTRA. | 1 |
| 6 | 5 | |
| 7 | 31 | |
| 8 | 15 | |
| 9 | 7 | |
| 10 | 8 | |
| 11 | 28 | |
| 12 | Automatic generation of descriptive summary comments for methods in object-oriented programs | 23 |
| 13 | 10 | |
| 14 | Integrating natural language and program structure information to improve software search and exploration | 29 |
| 15 | Active learning with support vector machines for imbalanced datasets and a method for stopping active learning based on stabilizing predictions | 1 |
| 16 | 14 | |
| 17 | Beyond information retrieval--medical question answering. | 63 |
| 18 | Towards efficient statistical parsing using lexicalized grammatical information | 33 |
| 19 | Discourse learning: an investigation of dialogue act tagging using transformation-based learning | 11 |
About Vijay Shanker
Vijay Shanker is a scholar working on Software, Artificial Intelligence and Language and Linguistics, having authored 19 papers that have together received 319 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (7 papers), Topic Modeling (6 papers) and Biomedical Text Mining and Ontologies (3 papers). The work is most often cited by research in Software (26 citations), Artificial Intelligence (179 citations) and Health Informatics (7 citations). Vijay Shanker has collaborated with scholars based in United States, India and Switzerland. Frequent co-authors include John Chen, Lori Pollock, Emily Hill, Carl Sable, Hong Yu, John Ely, James J. Cimino, Samir Gupta, Giriprasad Sridhara and Gaia Trincucci. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of Biomedical Materials Research Part A and Computers in Biology and Medicine.
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.