Sumit Sanghai
Impact in
- Signal Processing top 2%
- Advanced Malware Detection Techniques
- Artificial Intelligence top 2%
- Adversarial Robustness in Machine Learning
- Topic Modeling
- Anomaly Detection Techniques and Applications
- Natural Language Processing Techniques
Papers in
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- Bayesian Modeling and Causal Inference 3
- Topic Modeling 3
- Text and Document Classification Technologies 2
- Advanced Text Analysis Techniques 1
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- Advanced Database Systems and Queries 2
- Constraint Satisfaction and Optimization 2
- Co-authors
- Pedro Domingos (4 shared papers)Nilesh Dalvi (3 shared papers)Deepak Kumar Verma (1 shared paper)Mausam Mausam (1 shared paper)Yang Li (3 shared papers)Qifan Wang (3 shared papers)Prasan Roy (2 shared papers)S. Sudarshan (2 shared papers)
- Journals
- Journal of Computer and System Sciences (1 paper)Journal of Artificial Intelligence Research (1 paper)International Joint Conference on Artificial Intelligence (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesIndiaUnited Kingdom
In The Last Decade
Sumit Sanghai
10 papers receiving 868 citations
Sumit Sanghai's Hit Papers
Peers
Comparison fields: 5 of 67
- Signal Processing 258
- Artificial Intelligence 691
- Computer Networks and Communications 282
- Information Systems 207
- Management Science and Operations Research 77
Countries citing papers authored by Sumit Sanghai
This map shows the geographic impact of Sumit Sanghai'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 Sumit Sanghai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sumit Sanghai more than expected).
Fields of papers citing papers by Sumit Sanghai
This network shows the impact of papers produced by Sumit Sanghai. 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 Sumit Sanghai. The network helps show where Sumit Sanghai may publish in the future.
Co-authors
The 25 scholars most cited alongside Sumit Sanghai, 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 | Adversarial classification Hit paper breakdown → | 2004 | 519 |
| 2 | 2020 | 148 | |
| 3 | Dynamic probabilistic relational models | 2003 | 46 |
| 4 | 2020 | 46 | |
| 5 | 2001 | 44 | |
| 6 | 2003 | 43 | |
| 7 | 2005 | 34 | |
| 8 | 2022 | 28 | |
| 9 | 2012 | 12 | |
| 10 | Research on Statistical Relational Learning at the University of Washington | 2003 | 1 |
About Sumit Sanghai
Sumit Sanghai is a scholar working on Artificial Intelligence, Computer Networks and Communications, Computational Theory and Mathematics, Information Systems and Signal Processing, having authored 10 papers that have together received 921 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (3 papers), Rough Sets and Fuzzy Logic (3 papers), Topic Modeling (3 papers), Data Management and Algorithms (2 papers), Text and Document Classification Technologies (2 papers), Advanced Database Systems and Queries (2 papers), Constraint Satisfaction and Optimization (2 papers) and Advanced Text Analysis Techniques (1 paper). The work is most often cited by research in Signal Processing (258 citations), Artificial Intelligence (691 citations), Computer Networks and Communications (282 citations), Information Systems (207 citations) and Management Science and Operations Research (77 citations). Sumit Sanghai has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Pedro Domingos, Nilesh Dalvi, Deepak Kumar Verma, Mausam Mausam, Yang Li, Qifan Wang, Prasan Roy, S. Sudarshan, Anirudh Ravula and Chris Alberti. Their work appears in journals such as Journal of Computer and System Sciences, Journal of Artificial Intelligence Research, International Joint Conference on Artificial Intelligence and arXiv (Cornell University).
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.