Shalini Ghosh
- Artificial Intelligence top 5%
- Molecular Biology
- Computer Vision and Pattern Recognition top 5%
- Materials Chemistry
- Physical and Theoretical Chemistry top 5%
- Co-authors
- Nikhil GuchhaitSankar JanaSasanka DalapatiLarry HeckJunting ZhangDawei LiŞerafettin TaşcıHeming Zhang
- Topics
- Photochemistry and Electron Transfer Studies (14 papers)Protein Interaction Studies and Fluorescence Analysis (11 papers)Speech Recognition and Synthesis (7 papers)
- Cited by
- Physical and Theoretical ChemistryArtificial IntelligenceComputer Vision and Pattern Recognition
- Partner nations
- United StatesIndiaSouth Korea
In The Last Decade
Shalini Ghosh
53 papers receiving 993 citations
Peers
Comparison fields: 5 of 112
- Artificial Intelligence 360
- Molecular Biology 294
- Computer Vision and Pattern Recognition 198
- Materials Chemistry 171
- Physical and Theoretical Chemistry 150
Countries citing papers authored by Shalini Ghosh
This map shows the geographic impact of Shalini Ghosh'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 Shalini Ghosh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shalini Ghosh more than expected).
Fields of papers citing papers by Shalini Ghosh
This network shows the impact of papers produced by Shalini Ghosh. 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 Shalini Ghosh. The network helps show where Shalini Ghosh may publish in the future.
Co-authorship network of co-authors of Shalini Ghosh
This figure shows the co-authorship network connecting the top 25 collaborators of Shalini Ghosh. A scholar is included among the top collaborators of Shalini Ghosh 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 Shalini Ghosh. Shalini Ghosh 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 | 1 | |
| 3 | 4 | |
| 4 | 8 | |
| 5 | Efficient Incremental Learning for Mobile Object Detection | 4 |
| 6 | 7 | |
| 7 | Trusted Machine Learning: Model Repair and Data Repair for Probabilistic Models. | 4 |
| 8 | ATOL: A Framework for Automated Analysis and Categorization of the Darkweb Ecosystem. | 9 |
| 9 | 34 | |
| 10 | 8 | |
| 11 | 1 | |
| 12 | 27 | |
| 13 | 54 | |
| 14 | 7 | |
| 15 | 63 | |
| 16 | 19 | |
| 17 | 25 | |
| 18 | 4 | |
| 19 | 6 | |
| 20 | 35 |
About Shalini Ghosh
Shalini Ghosh is a scholar working on Physical and Theoretical Chemistry, Artificial Intelligence and Signal Processing, having authored 54 papers that have together received 1.0k indexed citations. Recurring topics across this work include Photochemistry and Electron Transfer Studies (14 papers), Protein Interaction Studies and Fluorescence Analysis (11 papers) and Speech Recognition and Synthesis (7 papers). The work is most often cited by research in Physical and Theoretical Chemistry (150 citations), Artificial Intelligence (360 citations) and Computer Vision and Pattern Recognition (198 citations). Shalini Ghosh has collaborated with scholars based in United States, India and South Korea. Frequent co-authors include Nikhil Guchhait, Sankar Jana, Sasanka Dalapati, Larry Heck, Junting Zhang, Dawei Li, Şerafettin Taşcı, Heming Zhang, C.‐C. Jay Kuo and Jie Zhang. Their work appears in journals such as The Journal of Physical Chemistry B, Biopolymers and IEEE/ACM Transactions on Networking.
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.