Aditya Devarakonda
Impact in
- Information Systems top 5%
- Cloud Computing and Resource Management
- Cloud Data Security Solutions
- Blockchain Technology Applications and Security
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- IoT and Edge/Fog Computing
- Distributed and Parallel Computing Systems
- Caching and Content Delivery
- Advanced Data Storage Technologies
Papers in ⓘ
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- Stochastic Gradient Optimization Techniques 2
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- Distributed and Parallel Computing Systems 3
- Co-authors
- Iván Rodero (2 shared papers)Manish Parashar (2 shared papers)David Villegas (1 shared paper)Yanbin Liu (1 shared paper)Liana Fong (1 shared paper)S. Masoud Sadjadi (1 shared paper)Javier Delgado (1 shared paper)Norman Bobroff (1 shared paper)
- Journals
- Journal of Computer and System Sciences (1 paper)SIAM Journal on Scientific Computing (1 paper)Computing in Science & Engineering (1 paper)
- Partner nations
- United StatesNetherlands
In The Last Decade
Aditya Devarakonda
7 papers receiving 209 citations
Peers
Comparison fields: 5 of 41
- Information Systems 157
- Computer Networks and Communications 146
- Information Systems and Management 31
- Hardware and Architecture 13
- Computational Mathematics 1
Countries citing papers authored by Aditya Devarakonda
This map shows the geographic impact of Aditya Devarakonda'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 Aditya Devarakonda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aditya Devarakonda more than expected).
Fields of papers citing papers by Aditya Devarakonda
This network shows the impact of papers produced by Aditya Devarakonda. 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 Aditya Devarakonda. The network helps show where Aditya Devarakonda may publish in the future.
Co-authors
The 25 scholars most cited alongside Aditya Devarakonda, 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 | 2012 | 128 | |
| 2 | 2013 | 51 | |
| 3 | 2016 | 26 | |
| 4 | 2019 | 6 | |
| 5 | 2014 | 3 | |
| 6 | 2018 | 2 | |
| 7 | 2025 | 1 |
About Aditya Devarakonda
Aditya Devarakonda is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems and Management, Numerical Analysis and Computational Mechanics, having authored 7 papers that have together received 217 indexed citations. Recurring topics across this work include Scientific Computing and Data Management (3 papers), Distributed and Parallel Computing Systems (3 papers), Advanced Optimization Algorithms Research (2 papers), Stochastic Gradient Optimization Techniques (2 papers), Sparse and Compressive Sensing Techniques (2 papers), Parallel Computing and Optimization Techniques (1 paper), Face and Expression Recognition (1 paper) and Cloud Computing and Resource Management (1 paper). The work is most often cited by research in Information Systems (157 citations), Computer Networks and Communications (146 citations), Information Systems and Management (31 citations), Hardware and Architecture (13 citations) and Computational Mathematics (1 citation). Aditya Devarakonda has collaborated with scholars based in United States and Netherlands. Frequent co-authors include Iván Rodero, Manish Parashar, David Villegas, Yanbin Liu, Liana Fong, S. Masoud Sadjadi, Javier Delgado, Norman Bobroff, Moustafa AbdelBaky and James Demmel. Their work appears in journals such as Journal of Computer and System Sciences, SIAM Journal on Scientific Computing and Computing in Science & Engineering.
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.