Sreerama K. Murthy
- Artificial Intelligence top 2%
- AI in cancer detection 2
- Imbalanced Data Classification Techniques 2
- Machine Learning and Data Classification 2
- Neural Networks and Applications 1
- Bayesian Modeling and Causal Inference 1
- Information Systems top 2%
- Data Mining Algorithms and Applications 5
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- Rough Sets and Fuzzy Logic 3
- Signal Processing top 10%
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- Medical Imaging Techniques and Applications 1
- Co-authors
- Steven L. SalzbergSimon KasifRichard BeigelH. C. FordR. L. WhiteRupali ChandarJianZhong QianAshwani Kumar
- Journals
- The Knowledge Engineering Review (1 paper)Data Mining and Knowledge Discovery (1 paper)Journal of Artificial Intelligence Research (1 paper)
- Partner nations
- United StatesGermany
In The Last Decade
Sreerama K. Murthy
9 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 144
- Artificial Intelligence 690
- Information Systems 382
- Computational Theory and Mathematics 201
- Signal Processing 100
- Computer Vision and Pattern Recognition 138
Countries citing papers authored by Sreerama K. Murthy
This map shows the geographic impact of Sreerama K. Murthy'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 Sreerama K. Murthy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sreerama K. Murthy more than expected).
Fields of papers citing papers by Sreerama K. Murthy
This network shows the impact of papers produced by Sreerama K. Murthy. 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 Sreerama K. Murthy. The network helps show where Sreerama K. Murthy may publish in the future.
Co-authorship network
The 8 scholars most cited alongside Sreerama K. Murthy, 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 | 2015 | 2 | |
| 2 | 2002 | 1 | |
| 3 | 1998 | 1 | |
| 4 | Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Surveybreakdown → | 1998 | 635 |
| 5 | Decision tree induction: how effective is the greedy heuristic? | 1995 | 14 |
| 6 | Lookahead and pathology in decision tree induction | 1995 | 65 |
| 7 | 1995 | 44 | |
| 8 | 1994 | 358 | |
| 9 | OC1: randomized induction of oblique decision trees | 1993 | 70 |
About Sreerama K. Murthy
Sreerama K. Murthy is a scholar working on Information Systems, Artificial Intelligence, Computational Theory and Mathematics, Signal Processing and Nature and Landscape Conservation, having authored 9 papers that have together received 1.2k indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (5 papers), Rough Sets and Fuzzy Logic (3 papers), AI in cancer detection (2 papers), Imbalanced Data Classification Techniques (2 papers), Machine Learning and Data Classification (2 papers), Medical Imaging Techniques and Applications (1 paper), Neural Networks and Applications (1 paper) and Bayesian Modeling and Causal Inference (1 paper). The work is most often cited by research in Artificial Intelligence (690 citations), Information Systems (382 citations), Computational Theory and Mathematics (201 citations), Signal Processing (100 citations) and Computer Vision and Pattern Recognition (138 citations). Sreerama K. Murthy has collaborated with scholars based in United States and Germany. Frequent co-authors include Steven L. Salzberg, Simon Kasif, Richard Beigel, H. C. Ford, R. L. White, Rupali Chandar, JianZhong Qian and Ashwani Kumar. Their work appears in journals such as The Knowledge Engineering Review, Data Mining and Knowledge Discovery, Journal of Artificial Intelligence Research, Publications of the Astronomical Society of the Pacific and Knowledge Discovery and Data Mining.
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.