Ambrish Rawat
- Artificial Intelligence
- Computer Networks and Communications
- Information Systems
- Management Science and Operations Research
- Molecular Biology
- Co-authors
- Martin WistubaParikshit RamAdi BoteaPaulito PalmesRadu MarinescuAkihiro KishimotoWinston H. HsuHorst Samulowitz
- Topics
- Machine Learning and Data Classification (4 papers)Adversarial Robustness in Machine Learning (2 papers)Machine Learning and Algorithms (2 papers)
- Cited by
- Artificial IntelligenceInformation Systems and ManagementManagement Science and Operations Research
- Journals
- arXiv (Cornell University)CINECA IRIS Institutial Research Information System (University of Genoa)Neural Information Processing Systems
- Partner nations
- IrelandUnited StatesItaly
In The Last Decade
Ambrish Rawat
11 papers receiving 32 citations
Peers
Comparison fields: 5 of 20
- Artificial Intelligence 19
- Computer Networks and Communications 10
- Information Systems 9
- Management Science and Operations Research 6
- Molecular Biology 4
Countries citing papers authored by Ambrish Rawat
This map shows the geographic impact of Ambrish Rawat'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 Ambrish Rawat with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ambrish Rawat more than expected).
Fields of papers citing papers by Ambrish Rawat
This network shows the impact of papers produced by Ambrish Rawat. 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 Ambrish Rawat. The network helps show where Ambrish Rawat may publish in the future.
Co-authorship network of co-authors of Ambrish Rawat
This figure shows the co-authorship network connecting the top 25 collaborators of Ambrish Rawat. A scholar is included among the top collaborators of Ambrish Rawat 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 Ambrish Rawat. Ambrish Rawat is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 11 | |
| 8 | Designing for Usability: A Statistical Disclosure Control Tool for Microdata Sets | 1 |
| 9 | 2 | |
| 10 | 6 | |
| 11 | 3 | |
| 12 | Extending Knowledge Bases Using Images. | 1 |
About Ambrish Rawat
Ambrish Rawat is a scholar working on Artificial Intelligence, Software and Signal Processing, having authored 12 papers that have together received 33 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (4 papers), Adversarial Robustness in Machine Learning (2 papers) and Machine Learning and Algorithms (2 papers). The work is most often cited by research in Artificial Intelligence (19 citations), Information Systems and Management (4 citations) and Management Science and Operations Research (6 citations). Ambrish Rawat has collaborated with scholars based in Ireland, United States and Italy. Frequent co-authors include Martin Wistuba, Parikshit Ram, Adi Botea, Paulito Palmes, Radu Marinescu, Akihiro Kishimoto, Winston H. Hsu, Horst Samulowitz, I‐Hsin Chung and Calvin Ko. Their work appears in journals such as arXiv (Cornell University), CINECA IRIS Institutial Research Information System (University of Genoa) and Neural Information Processing Systems.
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.