Ranganath Krishnan
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 10%
- Explainable Artificial Intelligence (XAI)
- Adversarial Robustness in Machine Learning
- Anomaly Detection Techniques and Applications
- Machine Learning and Data Classification
- Domain Adaptation and Few-Shot Learning
Papers in
-
- Adversarial Robustness in Machine Learning 3
- Machine Learning and Data Classification 3
- Domain Adaptation and Few-Shot Learning 3
- Anomaly Detection Techniques and Applications 2
- Explainable Artificial Intelligence (XAI) 2
-
- Generative Adversarial Networks and Image Synthesis 1
- Co-authors
- Omesh Tickoo (6 shared papers)Riccardo Fogliato (1 shared paper)Prasanna Sattigeri (1 shared paper)Adrian Weller (1 shared paper)Jason Stanley (1 shared paper)Alice Xiang (1 shared paper)Umang Bhatt (1 shared paper)Q. Vera Liao (1 shared paper)
- Journals
- 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesUnited KingdomIndia
In The Last Decade
Ranganath Krishnan
7 papers receiving 192 citations
Peers
Comparison fields: 5 of 76
- Health Informatics 12
- Artificial Intelligence 124
- Safety Research 29
- General Decision Sciences 3
- Computer Vision and Pattern Recognition 28
Countries citing papers authored by Ranganath Krishnan
This map shows the geographic impact of Ranganath 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 Ranganath Krishnan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ranganath Krishnan more than expected).
Fields of papers citing papers by Ranganath Krishnan
This network shows the impact of papers produced by Ranganath 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 Ranganath Krishnan. The network helps show where Ranganath Krishnan may publish in the future.
Co-authors
The 15 scholars most cited alongside Ranganath 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 | 2021 | 138 | |
| 2 | 2020 | 24 | |
| 3 | 2020 | 17 | |
| 4 | 2019 | 8 | |
| 5 | 2019 | 6 | |
| 6 | 2022 | 4 | |
| 7 | 2023 | 2 | |
| 8 | 2025 | 0 | |
| 9 | 2024 | 0 |
About Ranganath Krishnan
Ranganath Krishnan is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Mechanics of Materials, Signal Processing and Safety Research, having authored 9 papers that have together received 199 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (3 papers), Machine Learning and Data Classification (3 papers), Domain Adaptation and Few-Shot Learning (3 papers), Anomaly Detection Techniques and Applications (2 papers), Explainable Artificial Intelligence (XAI) (2 papers), Fatigue and fracture mechanics (1 paper), Generative Adversarial Networks and Image Synthesis (1 paper) and Industrial Vision Systems and Defect Detection (1 paper). The work is most often cited by research in Health Informatics (12 citations), Artificial Intelligence (124 citations), Safety Research (29 citations), General Decision Sciences (3 citations) and Computer Vision and Pattern Recognition (28 citations). Ranganath Krishnan has collaborated with scholars based in United States, United Kingdom and India. Frequent co-authors include Omesh Tickoo, Riccardo Fogliato, Prasanna Sattigeri, Adrian Weller, Jason Stanley, Alice Xiang, Umang Bhatt, Q. Vera Liao, Yunfeng Zhang and Lama Nachman. Their work appears in journals such as 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 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.