Vijay Krishnan
- Artificial Intelligence top 5%
- Topic Modeling 3
- Natural Language Processing Techniques 3
- Speech and dialogue systems 1
- Information Systems top 5%
- Spam and Phishing Detection 1
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- MRI in cancer diagnosis 1
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- scientometrics and bibliometrics research 1
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- Biomedical Text Mining and Ontologies 1
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- Caching and Content Delivery 1
- Co-authors
- Christopher D. ManningSoumen ChakrabartiAtul J. ButteJoel T. DudleyDavid RuauKedar SharbidreAshish ChawlaWcg Peh
- Journals
- Journal of Biomedical Informatics (1 paper)Current Problems in Diagnostic Radiology (1 paper)International journal of intelligent engineering and systems (1 paper)
- Partner nations
- United StatesIndiaSingapore
In The Last Decade
Vijay Krishnan
8 papers receiving 237 citations
Peers
Comparison fields: 5 of 42
- Artificial Intelligence 202
- Information Systems 130
- Management Science and Operations Research 30
- Statistical and Nonlinear Physics 23
- Signal Processing 19
Countries citing papers authored by Vijay Krishnan
This map shows the geographic impact of Vijay Krishnan'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 Vijay Krishnan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vijay Krishnan more than expected).
Fields of papers citing papers by Vijay Krishnan
This network shows the impact of papers produced by Vijay Krishnan. 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 Vijay Krishnan. The network helps show where Vijay Krishnan may publish in the future.
Co-authorship network
The 9 scholars most cited alongside Vijay Krishnan, 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 | 2023 | 1 | |
| 2 | 2020 | 0 | |
| 3 | 2017 | 5 | |
| 4 | Research Data Analysis with Power BI | 2017 | 6 |
| 5 | Citation Analysis on Current Science Publications: A Global Perspective | 2014 | 1 |
| 6 | 2011 | 8 | |
| 7 | Web Spam Detection with Anti-Trust Rank | 2006 | 101 |
| 8 | 2006 | 110 | |
| 9 | 2005 | 2 | |
| 10 | 2005 | 37 |
About Vijay Krishnan
Vijay Krishnan is a scholar working on Architecture, Statistics, Probability and Uncertainty and Artificial Intelligence, having authored 10 papers that have together received 271 indexed citations. Recurring topics across this work include Topic Modeling (3 papers), Natural Language Processing Techniques (3 papers), Spam and Phishing Detection (1 paper), MRI in cancer diagnosis (1 paper), scientometrics and bibliometrics research (1 paper), Speech and dialogue systems (1 paper), Biomedical Text Mining and Ontologies (1 paper) and Caching and Content Delivery (1 paper). The work is most often cited by research in Artificial Intelligence (202 citations), Information Systems (130 citations) and Management Science and Operations Research (30 citations). Vijay Krishnan has collaborated with scholars based in United States, India and Singapore. Frequent co-authors include Christopher D. Manning, Soumen Chakrabarti, Atul J. Butte, Joel T. Dudley, David Ruau, Kedar Sharbidre, Ashish Chawla, Wcg Peh and Ajit D. Kelkar. Their work appears in journals such as Journal of Biomedical Informatics, Current Problems in Diagnostic Radiology and International journal of intelligent engineering and systems.
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.