Rohan Varma
Impact in
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- Complex Network Analysis Techniques
- Computational Mathematics top 10%
Papers in
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- Advanced Graph Neural Networks 9
- Bayesian Modeling and Causal Inference 3
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- Complex Network Analysis Techniques 7
- Co-authors
- Siheng Chen (7 shared papers)Jelena Kovačević (9 shared papers)Aliaksei Sandryhaila (1 shared paper)Jeff Smith (1 shared paper)Li Shen (1 shared paper)Teng Li (1 shared paper)Adam Paszke (1 shared paper)Soumith Chintala (1 shared paper)
- Journals
- Proceedings of the VLDB Endowment (2 papers)BMC Systems Biology (1 paper)PLoS Computational Biology (1 paper)IEEE Transactions on Signal and Information Processing over Networks (1 paper)IEEE Transactions on Signal Processing (1 paper)
- Partner nations
- United StatesIndiaNetherlands
In The Last Decade
Rohan Varma
19 papers receiving 878 citations
Rohan Varma's Hit Papers
Peers
Comparison fields: 5 of 100
- Statistical and Nonlinear Physics 262
- Computational Mathematics 12
- Artificial Intelligence 582
- Computer Vision and Pattern Recognition 205
- Hardware and Architecture 58
Countries citing papers authored by Rohan Varma
This map shows the geographic impact of Rohan Varma'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 Rohan Varma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rohan Varma more than expected).
Fields of papers citing papers by Rohan Varma
This network shows the impact of papers produced by Rohan Varma. 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 Rohan Varma. The network helps show where Rohan Varma may publish in the future.
Co-authors
The 25 scholars most cited alongside Rohan Varma, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Discrete Signal Processing on Graphs: Sampling Theory Hit paper breakdown → | 2015 | 424 |
| 2 | PyTorch distributed Hit paper breakdown → | 2020 | 257 |
| 3 | PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel Hit paper breakdown → | 2023 | 89 |
| 4 | 2020 | 22 | |
| 5 | 2015 | 22 | |
| 6 | 2016 | 21 | |
| 7 | 2015 | 11 | |
| 8 | 2018 | 8 | |
| 9 | 2021 | 7 | |
| 10 | 2025 | 6 | |
| 11 | 2016 | 6 | |
| 12 | 2015 | 5 | |
| 13 | 2017 | 5 | |
| 14 | 2019 | 4 | |
| 15 | 2019 | 4 | |
| 16 | 2024 | 2 | |
| 17 | 2017 | 2 | |
| 18 | 2019 | 1 | |
| 19 | 2019 | 1 | |
| 20 | 2018 | 0 |
About Rohan Varma
Rohan Varma is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Computational Mechanics, Computer Networks and Communications and Signal Processing, having authored 20 papers that have together received 897 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (9 papers), Complex Network Analysis Techniques (7 papers), Sparse and Compressive Sensing Techniques (6 papers), Advanced Neural Network Applications (3 papers), Bayesian Modeling and Causal Inference (3 papers), Blind Source Separation Techniques (2 papers), IoT and Edge/Fog Computing (2 papers) and Cloud Computing and Resource Management (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (262 citations), Computational Mathematics (12 citations), Artificial Intelligence (582 citations), Computer Vision and Pattern Recognition (205 citations) and Hardware and Architecture (58 citations). Rohan Varma has collaborated with scholars based in United States, India and Netherlands. Frequent co-authors include Siheng Chen, Jelena Kovačević, Aliaksei Sandryhaila, Jeff Smith, Li Shen, Teng Li, Adam Paszke, Soumith Chintala, Aarti Singh and Jelena Kovačević. Their work appears in journals such as Proceedings of the VLDB Endowment, BMC Systems Biology, PLoS Computational Biology, IEEE Transactions on Signal and Information Processing over Networks and IEEE Transactions on Signal Processing.
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.