M.C. Roubaud
Impact in
- Oceanography top 5%
- Oceanographic and Atmospheric Processes
- Atmospheric Science top 10%
- Meteorological Phenomena and Simulations
- Arctic and Antarctic ice dynamics
Papers in
-
- Target Tracking and Data Fusion in Sensor Networks 11
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- EEG and Brain-Computer Interfaces 3
- Co-authors
- Dinh-Tuan Pham (1 shared paper)Jacques Verron (1 shared paper)Alain Breton (5 shared papers)Marina L'vovna Kleptsyna (4 shared papers)Bruno Torrésani (5 shared papers)P. Chiappetta (2 shared papers)Borı́s Burle (2 shared papers)Paula Milheiro–Oliveira (2 shared papers)
In The Last Decade
M.C. Roubaud
17 papers receiving 593 citations
Peers
Comparison fields: 5 of 63
- Oceanography 236
- Atmospheric Science 164
- Finance 81
- Artificial Intelligence 90
- Modeling and Simulation 11
Countries citing papers authored by M.C. Roubaud
This map shows the geographic impact of M.C. Roubaud'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. Roubaud 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. Roubaud more than expected).
Fields of papers citing papers by M.C. Roubaud
This network shows the impact of papers produced by M.C. Roubaud. 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. Roubaud. The network helps show where M.C. Roubaud may publish in the future.
Co-authors
The 20 scholars most cited alongside M.C. Roubaud, 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 | 1998 | 420 | |
| 2 | 2004 | 67 | |
| 3 | 2000 | 54 | |
| 4 | 2000 | 29 | |
| 5 | 2005 | 15 | |
| 6 | 2015 | 11 | |
| 7 | 1999 | 9 | |
| 8 | 1995 | 6 | |
| 9 | 2014 | 4 | |
| 10 | Filtrage Lineaire par Morceaux Avec Petit Bruit d'Observation (Piecewise Linear Filtering with Small Observation Noise) | 1990 | 3 |
| 11 | 2000 | 3 | |
| 12 | 1999 | 2 | |
| 13 | 1991 | 1 | |
| 14 | 1993 | 1 | |
| 15 | 1995 | 1 | |
| 16 | 2003 | 1 | |
| 17 | 2018 | 1 | |
| 18 | 2002 | 0 | |
| 19 | Approche variationnelle pour la fusion de jeux de données d'expression génique | 2009 | 0 |
About M.C. Roubaud
M.C. Roubaud is a scholar working on Artificial Intelligence, Cognitive Neuroscience, Finance, Control and Systems Engineering and Computational Mechanics, having authored 19 papers that have together received 628 indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (11 papers), Control Systems and Identification (3 papers), EEG and Brain-Computer Interfaces (3 papers), Stochastic processes and financial applications (2 papers), Gene expression and cancer classification (2 papers), Advanced Adaptive Filtering Techniques (2 papers), Oceanographic and Atmospheric Processes (1 paper) and Numerical methods in inverse problems (1 paper). The work is most often cited by research in Oceanography (236 citations), Atmospheric Science (164 citations), Finance (81 citations), Artificial Intelligence (90 citations) and Modeling and Simulation (11 citations). M.C. Roubaud has collaborated with scholars based in France, Portugal and Russia. Frequent co-authors include Dinh-Tuan Pham, Jacques Verron, Alain Breton, Marina L'vovna Kleptsyna, Bruno Torrésani, P. Chiappetta, Borı́s Burle, Paula Milheiro–Oliveira, Hérvè Chambost and Chantal Fossat. Their work appears in journals such as SIAM Journal on Control and Optimization, Journal of Neural Engineering, IEEE Transactions on Automatic Control, Leukemia Research and Journal of Computational Biology.
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.