Sutanay Choudhury
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- Complex Network Analysis Techniques 8
- Artificial Intelligence top 10%
- Advanced Graph Neural Networks 10
- Topic Modeling 6
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- Advanced Database Systems and Queries 4
- Network Security and Intrusion Detection 4
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- Graph Theory and Algorithms 12
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- Data Management and Algorithms 7
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- Machine Learning in Materials Science 5
- Co-authors
- Khushbu AgarwalLawrence B. HolderGeorge ChinChandan K. ReddyPing WangPin‐Yu ChenJohn FeoAlfred O. Hero
- Cited by
- Statistical and Nonlinear PhysicsArtificial IntelligenceComputer Networks and Communications
- Partner nations
- United StatesIndiaUnited Kingdom
In The Last Decade
Sutanay Choudhury
38 papers receiving 276 citations
Peers
Comparison fields: 5 of 69
- Statistical and Nonlinear Physics 68
- Artificial Intelligence 131
- Computer Networks and Communications 86
- Computer Vision and Pattern Recognition 72
- Signal Processing 36
Countries citing papers authored by Sutanay Choudhury
This map shows the geographic impact of Sutanay Choudhury'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 Sutanay Choudhury with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sutanay Choudhury more than expected).
Fields of papers citing papers by Sutanay Choudhury
This network shows the impact of papers produced by Sutanay Choudhury. 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 Sutanay Choudhury. The network helps show where Sutanay Choudhury may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Sutanay Choudhury, 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 | 2025 | 6 | |
| 2 | 2024 | 5 | |
| 3 | 2024 | 2 | |
| 4 | 2023 | 3 | |
| 5 | 2023 | 4 | |
| 6 | Performance and usability enhancements for continuous subgraph matching queries on graph-structured data | 2023 | 0 |
| 7 | 2023 | 1 | |
| 8 | 2023 | 5 | |
| 9 | 2022 | 12 | |
| 10 | 2021 | 2 | |
| 11 | 2021 | 43 | |
| 12 | HyperThesis: Topological Hypothesis Management in a Hypergraph Knowledgebase. | 2018 | 1 |
| 13 | 2018 | 3 | |
| 14 | 2017 | 8 | |
| 15 | 2016 | 20 | |
| 16 | 2015 | 1 | |
| 17 | Frequent subgraph discovery in large attributed streaming graphs | 2014 | 11 |
| 18 | 2013 | 2 | |
| 19 | 2011 | 2 | |
| 20 | 2010 | 11 |
About Sutanay Choudhury
Sutanay Choudhury is a scholar working on Statistical and Nonlinear Physics, Signal Processing and Artificial Intelligence, having authored 40 papers that have together received 294 indexed citations. Recurring topics across this work include Graph Theory and Algorithms (12 papers), Advanced Graph Neural Networks (10 papers), Complex Network Analysis Techniques (8 papers), Data Management and Algorithms (7 papers), Topic Modeling (6 papers), Machine Learning in Materials Science (5 papers), Advanced Database Systems and Queries (4 papers) and Network Security and Intrusion Detection (4 papers). The work is most often cited by research in Statistical and Nonlinear Physics (68 citations), Artificial Intelligence (131 citations) and Computer Networks and Communications (86 citations). Sutanay Choudhury has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Khushbu Agarwal, Lawrence B. Holder, George Chin, Chandan K. Reddy, Ping Wang, Pin‐Yu Chen, John Feo, Alfred O. Hero, Andrés Márquez and Jenna A. Bilbrey. Their work appears in journals such as The Journal of Chemical Physics, Scientific Reports and IEEE Access.
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.