Konda Reddy Mopuri
- Computer Vision and Pattern Recognition top 10%
- Ocean Engineering top 10%
- Mechanical Engineering
- Artificial Intelligence
- Civil and Structural Engineering
- Co-authors
- R. Venkatesh BabuHakan BilenTomoya InoueRyota WadaVenkatesh Babu RadhakrishnanAnirban ChakrabortyQiang QiuGaurav Patel
- Topics
- Drilling and Well Engineering (5 papers)Oil and Gas Production Techniques (4 papers)Adversarial Robustness in Machine Learning (3 papers)
- Journals
- Journal of Petroleum Science and EngineeringSPE JournalEdinburgh Research Explorer (University of Edinburgh)
- Partner nations
- IndiaUnited KingdomJapan
In The Last Decade
Konda Reddy Mopuri
10 papers receiving 157 citations
Peers
Comparison fields: 5 of 28
- Computer Vision and Pattern Recognition 68
- Ocean Engineering 68
- Mechanical Engineering 56
- Artificial Intelligence 52
- Civil and Structural Engineering 15
Countries citing papers authored by Konda Reddy Mopuri
This map shows the geographic impact of Konda Reddy Mopuri'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 Konda Reddy Mopuri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Konda Reddy Mopuri more than expected).
Fields of papers citing papers by Konda Reddy Mopuri
This network shows the impact of papers produced by Konda Reddy Mopuri. 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 Konda Reddy Mopuri. The network helps show where Konda Reddy Mopuri may publish in the future.
Co-authorship network of co-authors of Konda Reddy Mopuri
This figure shows the co-authorship network connecting the top 25 collaborators of Konda Reddy Mopuri. A scholar is included among the top collaborators of Konda Reddy Mopuri 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 Konda Reddy Mopuri. Konda Reddy Mopuri is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 15 | |
| 2 | 5 | |
| 3 | 1 | |
| 4 | Dataset Condensation with Gradient Matching | 3 |
| 5 | 29 | |
| 6 | 8 | |
| 7 | 7 | |
| 8 | 26 | |
| 9 | 29 | |
| 10 | 0 | |
| 11 | 38 |
About Konda Reddy Mopuri
Konda Reddy Mopuri is a scholar working on Metals and Alloys, Ocean Engineering and Computer Vision and Pattern Recognition, having authored 11 papers that have together received 161 indexed citations. Recurring topics across this work include Drilling and Well Engineering (5 papers), Oil and Gas Production Techniques (4 papers) and Adversarial Robustness in Machine Learning (3 papers). The work is most often cited by research in Ocean Engineering (68 citations), Computer Vision and Pattern Recognition (68 citations) and Artificial Intelligence (52 citations). Konda Reddy Mopuri has collaborated with scholars based in India, United Kingdom and Japan. Frequent co-authors include R. Venkatesh Babu, Hakan Bilen, Tomoya Inoue, Ryota Wada, Venkatesh Babu Radhakrishnan, Anirban Chakraborty, Qiang Qiu, Gaurav Patel, Kazuhiro Fujita and Masahiko Ozaki. Their work appears in journals such as Journal of Petroleum Science and Engineering, SPE Journal and Edinburgh Research Explorer (University of Edinburgh).
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.