Krishnateja Killamsetty
Impact in
- Artificial Intelligence top 10%
- Domain Adaptation and Few-Shot Learning
- Machine Learning and Data Classification
- Machine Learning and Algorithms
- Data Stream Mining Techniques
- Topic Modeling
- Privacy-Preserving Technologies in Data
- Stochastic Gradient Optimization Techniques
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- Advanced Neural Network Applications
Papers in
-
- Machine Learning and Algorithms 5
- Machine Learning and Data Classification 3
- Domain Adaptation and Few-Shot Learning 2
- Topic Modeling 1
- Co-authors
- Rishabh Iyer (8 shared papers)Pradeep Shenoy (1 shared paper)Ganesh Ramakrishnan (4 shared papers)Marina Danilevsky (1 shared paper)Lucian Constantin Popa (1 shared paper)Feng Chen (1 shared paper)Changbin Li (1 shared paper)Xujiang Zhao (1 shared paper)
- Journals
- Proceedings (1 paper)IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (1 paper)arXiv (Cornell University) (1 paper)IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings (1 paper)Findings of the Association for Computational Linguistics: ACL 2022 (1 paper)
- Partner nations
- United StatesIndia
In The Last Decade
Krishnateja Killamsetty
9 papers receiving 184 citations
Peers
Comparison fields: 5 of 30
- Artificial Intelligence 154
- Computer Vision and Pattern Recognition 30
- Signal Processing 5
- General Social Sciences 2
- Health Informatics 1
Countries citing papers authored by Krishnateja Killamsetty
This map shows the geographic impact of Krishnateja Killamsetty'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 Krishnateja Killamsetty with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Krishnateja Killamsetty more than expected).
Fields of papers citing papers by Krishnateja Killamsetty
This network shows the impact of papers produced by Krishnateja Killamsetty. 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 Krishnateja Killamsetty. The network helps show where Krishnateja Killamsetty may publish in the future.
Co-authors
The 13 scholars most cited alongside Krishnateja Killamsetty, 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 | 2022 | 88 | |
| 2 | 2021 | 69 | |
| 3 | 2022 | 9 | |
| 4 | 2022 | 5 | |
| 5 | 2022 | 5 | |
| 6 | 2021 | 4 | |
| 7 | 2022 | 2 | |
| 8 | 2024 | 2 | |
| 9 | 2023 | 1 |
About Krishnateja Killamsetty
Krishnateja Killamsetty is a scholar working on Artificial Intelligence, Nuclear Energy and Engineering, Waste Management and Disposal, Infectious Diseases and Organic Chemistry, having authored 9 papers that have together received 185 indexed citations. Recurring topics across this work include Machine Learning and Algorithms (5 papers), Machine Learning and Data Classification (3 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Topic Modeling (1 paper). The work is most often cited by research in Artificial Intelligence (154 citations), Computer Vision and Pattern Recognition (30 citations), Signal Processing (5 citations), General Social Sciences (2 citations) and Health Informatics (1 citation). Krishnateja Killamsetty has collaborated with scholars based in United States and India. Frequent co-authors include Rishabh Iyer, Pradeep Shenoy, Ganesh Ramakrishnan, Marina Danilevsky, Lucian Constantin Popa, Feng Chen, Changbin Li, Xujiang Zhao, Feng Chen and Chen Zhao. Their work appears in journals such as Proceedings, IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), arXiv (Cornell University), IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings and Findings of the Association for Computational Linguistics: ACL 2022.
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.