Hans Roubos
Impact in
- Artificial Intelligence top 2%
- Fuzzy Logic and Control Systems
- Neural Networks and Applications
- Evolutionary Algorithms and Applications
- Metaheuristic Optimization Algorithms Research
- Statistics and Probability top 5%
- Fuzzy Systems and Optimization
Papers in
-
- Neural Networks and Applications 6
- Fuzzy Logic and Control Systems 6
-
- Fault Detection and Control Systems 2
- Advanced Control Systems Optimization 1
- Co-authors
- M. Setnes (4 shared papers)Antonio Skármeta (2 shared papers)Robert Babuška (3 shared papers)Fernando Jiménez (2 shared papers)János Abonyi (2 shared papers)Ferenc Szeifert (1 shared paper)Gracia Sánchez (1 shared paper)Preben Krabben (1 shared paper)
- Journals
- IEEE Transactions on Fuzzy Systems (2 papers)Industrial & Engineering Chemistry Research (1 paper)
- Partner nations
- NetherlandsSpainHungary
In The Last Decade
Hans Roubos
8 papers receiving 584 citations
Peers
Comparison fields: 5 of 65
- Artificial Intelligence 533
- Statistics and Probability 89
- Computational Theory and Mathematics 107
- Control and Systems Engineering 118
- Management Science and Operations Research 56
Countries citing papers authored by Hans Roubos
This map shows the geographic impact of Hans Roubos'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 Hans Roubos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hans Roubos more than expected).
Fields of papers citing papers by Hans Roubos
This network shows the impact of papers produced by Hans Roubos. 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 Hans Roubos. The network helps show where Hans Roubos may publish in the future.
Co-authors
The 9 scholars most cited alongside Hans Roubos, 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 | 2000 | 337 | |
| 2 | 2001 | 194 | |
| 3 | 2002 | 38 | |
| 4 | 2002 | 19 | |
| 5 | 2003 | 17 | |
| 6 | 2003 | 16 | |
| 7 | 2003 | 5 | |
| 8 | Hybrid modeling of fed-batch bioprocesses: Combination of physical equations with metabolic networks and black-box kinetics | 2000 | 2 |
| 9 | Structure Identification of Fuzzy Classifiers | 2000 | 1 |
About Hans Roubos
Hans Roubos is a scholar working on Artificial Intelligence, Control and Systems Engineering, Statistics and Probability, Molecular Biology and General Health Professions, having authored 9 papers that have together received 629 indexed citations. Recurring topics across this work include Neural Networks and Applications (6 papers), Fuzzy Logic and Control Systems (6 papers), Fuzzy Systems and Optimization (3 papers), Fault Detection and Control Systems (2 papers), Probabilistic and Robust Engineering Design (1 paper), Hermeneutics and Narrative Identity (1 paper), Microbial Metabolic Engineering and Bioproduction (1 paper) and Advanced Control Systems Optimization (1 paper). The work is most often cited by research in Artificial Intelligence (533 citations), Statistics and Probability (89 citations), Computational Theory and Mathematics (107 citations), Control and Systems Engineering (118 citations) and Management Science and Operations Research (56 citations). Hans Roubos has collaborated with scholars based in Netherlands, Spain and Hungary. Frequent co-authors include M. Setnes, Antonio Skármeta, Robert Babuška, Fernando Jiménez, János Abonyi, Ferenc Szeifert, Gracia Sánchez, Preben Krabben and Joseph J. Heijnen. Their work appears in journals such as IEEE Transactions on Fuzzy Systems and Industrial & Engineering Chemistry Research.
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.