Saurav Sahay
- Artificial Intelligence top 10%
- Information Systems
- Molecular Biology
- Computer Science Applications
- Developmental and Educational Psychology
- Co-authors
- Ashwin RamSougata MukherjeaJohn RyanEugene AgichteinGeorge G. KennedyErnest GarciaA. McColloughLama Nachman
- Topics
- Topic Modeling (8 papers)Speech and dialogue systems (7 papers)Biomedical Text Mining and Ontologies (4 papers)
- Journals
- Educational Technology Research and DevelopmentPolymer CompositesComputer Speech & Language
- Partner nations
- United StatesIndiaFrance
In The Last Decade
Saurav Sahay
19 papers receiving 115 citations
Peers
Comparison fields: 5 of 36
- Artificial Intelligence 93
- Information Systems 38
- Molecular Biology 25
- Computer Science Applications 16
- Developmental and Educational Psychology 14
Countries citing papers authored by Saurav Sahay
This map shows the geographic impact of Saurav Sahay'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 Saurav Sahay with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Saurav Sahay more than expected).
Fields of papers citing papers by Saurav Sahay
This network shows the impact of papers produced by Saurav Sahay. 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 Saurav Sahay. The network helps show where Saurav Sahay may publish in the future.
Co-authorship network of co-authors of Saurav Sahay
This figure shows the co-authorship network connecting the top 25 collaborators of Saurav Sahay. A scholar is included among the top collaborators of Saurav Sahay 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 Saurav Sahay. Saurav Sahay 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 | 1 | |
| 3 | 2 | |
| 4 | 9 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 4 | |
| 8 | 2 | |
| 9 | 2 | |
| 10 | 1 | |
| 11 | 2 | |
| 12 | 32 | |
| 13 | 5 | |
| 14 | 3 | |
| 15 | Intentional Analysis of Medical Conversations for Community Engagement. | 1 |
| 16 | Socio-Semantic Health Information Access | 12 |
| 17 | 15 | |
| 18 | Domain Ontology Construction from Biomedical Text. | 4 |
| 19 | Semantic Annotation and Inference for Medical Knowledge Discovery | 7 |
| 20 | 9 |
About Saurav Sahay
Saurav Sahay is a scholar working on Artificial Intelligence, Computer Science Applications and Information Systems, having authored 21 papers that have together received 126 indexed citations. Recurring topics across this work include Topic Modeling (8 papers), Speech and dialogue systems (7 papers) and Biomedical Text Mining and Ontologies (4 papers). The work is most often cited by research in Computer Science Applications (16 citations), Artificial Intelligence (93 citations) and Information Systems (38 citations). Saurav Sahay has collaborated with scholars based in United States, India and France. Frequent co-authors include Ashwin Ram, Sougata Mukherjea, John Ryan, Eugene Agichtein, George G. Kennedy, Ernest Garcia, A. McCollough, Lama Nachman, Hua Ai and Eda Okur. Their work appears in journals such as Educational Technology Research and Development, Polymer Composites and Computer Speech & Language.
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.