Virat Shejwalkar
- Artificial Intelligence top 5%
- Computer Networks and Communications
- Information Systems
- Sociology and Political Science
- Electrical and Electronic Engineering
- Co-authors
- Amir HoumansadrPeter KairouzDaniel RamageMilad NasrSaeed MahloujifarDennis GoeckelLingjuan LyuHossein Pishro-Nik
- Topics
- Privacy-Preserving Technologies in Data (9 papers)Adversarial Robustness in Machine Learning (8 papers)Internet Traffic Analysis and Secure E-voting (3 papers)
- Journals
- arXiv (Cornell University)Proceedings on Privacy Enhancing TechnologiesProceedings of the AAAI Conference on Artificial Intelligence
- Partner nations
- United StatesFranceCanada
In The Last Decade
Virat Shejwalkar
11 papers receiving 493 citations
Hit Papers
Peers
Comparison fields: 5 of 34
- Artificial Intelligence 458
- Computer Networks and Communications 53
- Information Systems 40
- Sociology and Political Science 27
- Electrical and Electronic Engineering 24
Countries citing papers authored by Virat Shejwalkar
This map shows the geographic impact of Virat Shejwalkar'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 Virat Shejwalkar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Virat Shejwalkar more than expected).
Fields of papers citing papers by Virat Shejwalkar
This network shows the impact of papers produced by Virat Shejwalkar. 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 Virat Shejwalkar. The network helps show where Virat Shejwalkar may publish in the future.
Co-authorship network of co-authors of Virat Shejwalkar
This figure shows the co-authorship network connecting the top 25 collaborators of Virat Shejwalkar. A scholar is included among the top collaborators of Virat Shejwalkar 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 Virat Shejwalkar. Virat Shejwalkar 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 | 4 | |
| 3 | 7 | |
| 4 | 1 | |
| 5 | Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Production Federated Learningbreakdown → | 133 |
| 6 | 10 | |
| 7 | 6 | |
| 8 | Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses for Federated Learningbreakdown → | 291 |
| 9 | 45 | |
| 10 | 3 | |
| 11 | 1 |
About Virat Shejwalkar
Virat Shejwalkar is a scholar working on Artificial Intelligence, Computer Science Applications and Hardware and Architecture, having authored 11 papers that have together received 502 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (9 papers), Adversarial Robustness in Machine Learning (8 papers) and Internet Traffic Analysis and Secure E-voting (3 papers). The work is most often cited by research in Artificial Intelligence (458 citations), Health Informatics (7 citations) and Computer Science Applications (20 citations). Virat Shejwalkar has collaborated with scholars based in United States, France and Canada. Frequent co-authors include Amir Houmansadr, Peter Kairouz, Daniel Ramage, Milad Nasr, Saeed Mahloujifar, Dennis Goeckel, Lingjuan Lyu, Hossein Pishro-Nik, Liwei Song and Antoine Boutet. Their work appears in journals such as arXiv (Cornell University), Proceedings on Privacy Enhancing Technologies and Proceedings of the AAAI Conference on Artificial Intelligence.
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.