Raghavendra Chalapathy
- Artificial Intelligence top 5%
- Computer Networks and Communications top 10%
- Signal Processing top 10%
- Control and Systems Engineering
- Computer Vision and Pattern Recognition
- Co-authors
- Nguyen Lu Dang KhoaSanjay ChawlaSubbu SethuvenkatramanMassimo PiccardiEhsan Zare Borzeshi
- Topics
- Building Energy and Comfort Optimization (1 paper)Structural Health Monitoring Techniques (1 paper)Energy Load and Power Forecasting (1 paper)
- Journals
- Sustainable Energy Grids and NetworksProceedings of the Institution of Civil Engineers - Bridge EngineeringarXiv (Cornell University)
In The Last Decade
Raghavendra Chalapathy
3 papers receiving 376 citations
Hit Papers
Peers
Comparison fields: 5 of 79
- Artificial Intelligence 272
- Computer Networks and Communications 121
- Signal Processing 80
- Control and Systems Engineering 57
- Computer Vision and Pattern Recognition 56
Countries citing papers authored by Raghavendra Chalapathy
This map shows the geographic impact of Raghavendra Chalapathy'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 Raghavendra Chalapathy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raghavendra Chalapathy more than expected).
Fields of papers citing papers by Raghavendra Chalapathy
This network shows the impact of papers produced by Raghavendra Chalapathy. 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 Raghavendra Chalapathy. The network helps show where Raghavendra Chalapathy may publish in the future.
Co-authorship network of co-authors of Raghavendra Chalapathy
This figure shows the co-authorship network connecting the top 25 collaborators of Raghavendra Chalapathy. A scholar is included among the top collaborators of Raghavendra Chalapathy based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Raghavendra Chalapathy. Raghavendra Chalapathy is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 48 | |
| 2 | 0 | |
| 3 | Robust Deep Learning Methods for Anomaly Detectionbreakdown → | 321 |
| 4 | 23 |
About Raghavendra Chalapathy
Raghavendra Chalapathy is a scholar working on Building and Construction, Environmental Engineering and Artificial Intelligence, having authored 4 papers that have together received 392 indexed citations. Recurring topics across this work include Building Energy and Comfort Optimization (1 paper), Structural Health Monitoring Techniques (1 paper) and Energy Load and Power Forecasting (1 paper). The work is most often cited by research in Artificial Intelligence (272 citations), Signal Processing (80 citations) and Computer Networks and Communications (121 citations). Raghavendra Chalapathy has collaborated with scholars based in Australia and Qatar. Frequent co-authors include Nguyen Lu Dang Khoa, Sanjay Chawla, Subbu Sethuvenkatraman, Massimo Piccardi and Ehsan Zare Borzeshi. Their work appears in journals such as Sustainable Energy Grids and Networks, Proceedings of the Institution of Civil Engineers - Bridge Engineering 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.