M. C. Deo
- Environmental Engineering top 0.5%
- Oceanography top 0.5%
- Electrical and Electronic Engineering top 5%
- Water Science and Technology top 2%
- Atmospheric Science top 5%
- Co-authors
- P. B. DeolalikarAnkit JhaKalpesh PatilShreenivas LondheV. Sanil KumarHazi Mohammad AzamathullaM. RavichandranVijay K. Agarwal
- Topics
- Hydrological Forecasting Using AI (52 papers)Ocean Waves and Remote Sensing (40 papers)Oceanographic and Atmospheric Processes (23 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Biomedical EngineeringIEEE Transactions on Microwave Theory and Techniques
- Partner nations
- IndiaUnited StatesCanada
In The Last Decade
M. C. Deo
95 papers receiving 3.4k citations
Peers
Comparison fields: 5 of 106
- Environmental Engineering 1.8k
- Oceanography 1.4k
- Electrical and Electronic Engineering 799
- Water Science and Technology 639
- Atmospheric Science 579
Countries citing papers authored by M. C. Deo
This map shows the geographic impact of M. C. Deo'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 M. C. Deo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. C. Deo more than expected).
Fields of papers citing papers by M. C. Deo
This network shows the impact of papers produced by M. C. Deo. 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 M. C. Deo. The network helps show where M. C. Deo may publish in the future.
Co-authorship network of co-authors of M. C. Deo
This figure shows the co-authorship network connecting the top 25 collaborators of M. C. Deo. A scholar is included among the top collaborators of M. C. Deo 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 M. C. Deo. M. C. Deo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 33 | |
| 2 | 21 | |
| 3 | 50 | |
| 4 | 26 | |
| 5 | 6 | |
| 6 | 1 | |
| 7 | 21 | |
| 8 | Genetic Programming to Predict Spillway Scour | 6 |
| 9 | Genetic Programming to Estimate Coastal Waves from Deep Water Measurements | 7 |
| 10 | 13 | |
| 11 | 23 | |
| 12 | 15 | |
| 13 | 1 | |
| 14 | Neural Networks to Predict Scour of Piles in the Sea. | 1 |
| 15 | 1 | |
| 16 | 129 | |
| 17 | 5 | |
| 18 | 20 | |
| 19 | WAVE FORCE COEFFICIENTS FOR INCLINED ROUGH CYLINDERS | 2 |
| 20 | Spectral Analysis of Ocean Waves — A Study | 11 |
About M. C. Deo
M. C. Deo is a scholar working on Oceanography, Environmental Engineering and Earth-Surface Processes, having authored 98 papers that have together received 3.6k indexed citations. Recurring topics across this work include Hydrological Forecasting Using AI (52 papers), Ocean Waves and Remote Sensing (40 papers) and Oceanographic and Atmospheric Processes (23 papers). The work is most often cited by research in Environmental Engineering (1.8k citations), Oceanography (1.4k citations) and Earth-Surface Processes (429 citations). M. C. Deo has collaborated with scholars based in India, United States and Canada. Frequent co-authors include P. B. Deolalikar, Ankit Jha, Kalpesh Patil, Shreenivas Londhe, V. Sanil Kumar, Hazi Mohammad Azamathulla, M. Ravichandran, Vijay K. Agarwal, Raj Kumar and Jianjun Xu. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Biomedical Engineering and IEEE Transactions on Microwave Theory and Techniques.
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.