T. Krishnan
Impact in
- Statistics and Probability top 5%
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
- Advanced Statistical Methods and Models
- Statistical Distribution Estimation and Applications
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- Digital Filter Design and Implementation
Papers in
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- Bayesian Methods and Mixture Models 6
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- Statistical Methods and Inference 9
- Advanced Statistical Methods and Models 6
- Statistical Methods and Bayesian Inference 3
- Co-authors
- James E. Gentle (1 shared paper)Geoffrey J. McLachlan (1 shared paper)Subhas C. Nandy (2 shared papers)S. Oraintara (2 shared papers)B. Mohan Reddy (1 shared paper)Mohan Delampady (4 shared papers)Suman Kumar Swarnkar (1 shared paper)Krishna B. Athreya (3 shared papers)
- Journals
- Pattern Recognition (6 papers)Annals of Human Biology (2 papers)Biometrics (1 paper)Annals of the Institute of Statistical Mathematics (1 paper)Psychometrika (1 paper)
- Partner nations
- IndiaUnited StatesAustralia
In The Last Decade
T. Krishnan
25 papers receiving 321 citations
Peers
Comparison fields: 5 of 85
- Statistics and Probability 70
- Signal Processing 42
- Artificial Intelligence 118
- Computer Vision and Pattern Recognition 54
- Anatomy 3
Countries citing papers authored by T. Krishnan
This map shows the geographic impact of T. 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 T. Krishnan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Krishnan more than expected).
Fields of papers citing papers by T. Krishnan
This network shows the impact of papers produced by T. 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 T. Krishnan. The network helps show where T. Krishnan may publish in the future.
Co-authors
The 10 scholars most cited alongside T. 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
Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1998 | 204 | |
| 2 | 2003 | 15 | |
| 3 | 1994 | 15 | |
| 4 | 1988 | 13 | |
| 5 | 1990 | 11 | |
| 6 | 1987 | 9 | |
| 7 | 2023 | 9 | |
| 8 | 2002 | 7 | |
| 9 | 1989 | 7 | |
| 10 | 1966 | 7 | |
| 11 | 2016 | 4 | |
| 12 | 1992 | 4 | |
| 13 | 2019 | 3 | |
| 14 | 1973 | 3 | |
| 15 | 2003 | 3 | |
| 16 | 2016 | 3 | |
| 17 | 2001 | 3 | |
| 18 | 1997 | 3 | |
| 19 | 2014 | 2 | |
| 20 | 2015 | 2 |
About T. Krishnan
T. Krishnan is a scholar working on Artificial Intelligence, Statistics and Probability, Computer Networks and Communications, Electrical and Electronic Engineering and Information Systems, having authored 31 papers that have together received 332 indexed citations. Recurring topics across this work include Statistical Methods and Inference (9 papers), Advanced Statistical Methods and Models (6 papers), Bayesian Methods and Mixture Models (6 papers), Energy Efficient Wireless Sensor Networks (4 papers), IoT-based Smart Home Systems (4 papers), Statistical Methods and Bayesian Inference (3 papers), Digital Filter Design and Implementation (2 papers) and Image and Signal Denoising Methods (2 papers). The work is most often cited by research in Statistics and Probability (70 citations), Signal Processing (42 citations), Artificial Intelligence (118 citations), Computer Vision and Pattern Recognition (54 citations) and Anatomy (3 citations). T. Krishnan has collaborated with scholars based in India, United States and Australia. Frequent co-authors include James E. Gentle, Geoffrey J. McLachlan, Subhas C. Nandy, S. Oraintara, B. Mohan Reddy, Mohan Delampady, Suman Kumar Swarnkar, Krishna B. Athreya, S.A.V. Satya Murty and N. V. Anil Kumar. Their work appears in journals such as Pattern Recognition, Annals of Human Biology, Biometrics, Annals of the Institute of Statistical Mathematics and Psychometrika.
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.