Senjuti Basu Roy
- Information Systems top 2%
- Artificial Intelligence top 5%
- Computer Networks and Communications top 5%
- Signal Processing top 5%
- Computer Science Applications top 2%
- Co-authors
- Gautam DasSihem Amer-YahiaCong YuSaravanan ThirumuruganathanKiyana ZolfagharAnkur TeredesaiUllas NambiarMukesh Mohania
- Topics
- Data Management and Algorithms (16 papers)Mobile Crowdsensing and Crowdsourcing (10 papers)Machine Learning in Healthcare (9 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Knowledge and Data EngineeringLaboratory Investigation
- Partner nations
- United StatesFranceIndia
In The Last Decade
Senjuti Basu Roy
52 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 86
- Information Systems 454
- Artificial Intelligence 429
- Computer Networks and Communications 244
- Signal Processing 234
- Computer Science Applications 200
Countries citing papers authored by Senjuti Basu Roy
This map shows the geographic impact of Senjuti Basu Roy'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 Senjuti Basu Roy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Senjuti Basu Roy more than expected).
Fields of papers citing papers by Senjuti Basu Roy
This network shows the impact of papers produced by Senjuti Basu Roy. 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 Senjuti Basu Roy. The network helps show where Senjuti Basu Roy may publish in the future.
Co-authorship network of co-authors of Senjuti Basu Roy
This figure shows the co-authorship network connecting the top 25 collaborators of Senjuti Basu Roy. A scholar is included among the top collaborators of Senjuti Basu Roy 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 Senjuti Basu Roy. Senjuti Basu Roy is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 13 | |
| 2 | 3 | |
| 3 | 8 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 6 | |
| 7 | 19 | |
| 8 | Predicting 30-Day Risk and Cost of "All-Cause" Hospital Readmissions | 14 |
| 9 | 4 | |
| 10 | 39 | |
| 11 | 16 | |
| 12 | 5 | |
| 13 | 62 | |
| 14 | 32 | |
| 15 | 6 | |
| 16 | 55 | |
| 17 | 32 | |
| 18 | TRANS: Top-k Implementation Techniques of Minimum Effort Driven Faceted Search For Databases. | 0 |
| 19 | 267 | |
| 20 | 63 |
About Senjuti Basu Roy
Senjuti Basu Roy is a scholar working on Computer Science Applications, Signal Processing and Health Information Management, having authored 55 papers that have together received 1.1k indexed citations. Recurring topics across this work include Data Management and Algorithms (16 papers), Mobile Crowdsensing and Crowdsourcing (10 papers) and Machine Learning in Healthcare (9 papers). The work is most often cited by research in Computer Science Applications (200 citations), Signal Processing (234 citations) and Information Systems (454 citations). Senjuti Basu Roy has collaborated with scholars based in United States, France and India. Frequent co-authors include Gautam Das, Sihem Amer-Yahia, Cong Yu, Saravanan Thirumuruganathan, Kiyana Zolfaghar, Ankur Teredesai, Ullas Nambiar, Mukesh Mohania, Ioanna Lykourentzou and Kaushik Chakrabarti. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Knowledge and Data Engineering and Laboratory Investigation.
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.