H. Daniel Patiño
- Control and Systems Engineering top 5%
- Artificial Intelligence top 10%
- Cognitive Neuroscience top 10%
- Mechanical Engineering
- Electrical and Electronic Engineering
- Co-authors
- Derong LiuB. KuchenRicardo CarelliMax E. ValentinuzziAgustina Garcés CorreaEric LaciarE. CuestaJ. Barreiro
- Topics
- Advanced Measurement and Metrology Techniques (5 papers)Greenhouse Technology and Climate Control (5 papers)Neural Networks and Applications (4 papers)
- Journals
- Computers and Electronics in AgricultureIEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)Measurement Science and Technology
- Partner nations
- ArgentinaSpainUnited States
In The Last Decade
H. Daniel Patiño
26 papers receiving 524 citations
Peers
Comparison fields: 5 of 76
- Control and Systems Engineering 203
- Artificial Intelligence 121
- Cognitive Neuroscience 117
- Mechanical Engineering 88
- Electrical and Electronic Engineering 77
Countries citing papers authored by H. Daniel Patiño
This map shows the geographic impact of H. Daniel Patiño'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 H. Daniel Patiño with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites H. Daniel Patiño more than expected).
Fields of papers citing papers by H. Daniel Patiño
This network shows the impact of papers produced by H. Daniel Patiño. 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 H. Daniel Patiño. The network helps show where H. Daniel Patiño may publish in the future.
Co-authorship network of co-authors of H. Daniel Patiño
This figure shows the co-authorship network connecting the top 25 collaborators of H. Daniel Patiño. A scholar is included among the top collaborators of H. Daniel Patiño 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 H. Daniel Patiño. H. Daniel Patiño is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 13 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 7 | |
| 5 | 10 | |
| 6 | 7 | |
| 7 | 10 | |
| 8 | 2 | |
| 9 | 25 | |
| 10 | 20 | |
| 11 | Modelo auto regresivo no lineal basado en redes neuronales multicapa para pronóstico de series temporales | 1 |
| 12 | 13 | |
| 13 | 0 | |
| 14 | 4 | |
| 15 | 1 | |
| 16 | 24 | |
| 17 | 5 | |
| 18 | 113 | |
| 19 | 100 | |
| 20 | 3 |
About H. Daniel Patiño
H. Daniel Patiño is a scholar working on Modeling and Simulation, Control and Systems Engineering and Artificial Intelligence, having authored 29 papers that have together received 555 indexed citations. Recurring topics across this work include Advanced Measurement and Metrology Techniques (5 papers), Greenhouse Technology and Climate Control (5 papers) and Neural Networks and Applications (4 papers). The work is most often cited by research in Control and Systems Engineering (203 citations), Signal Processing (76 citations) and Cognitive Neuroscience (117 citations). H. Daniel Patiño has collaborated with scholars based in Argentina, Spain and United States. Frequent co-authors include Derong Liu, B. Kuchen, Ricardo Carelli, Max E. Valentinuzzi, Agustina Garcés Correa, Eric Laciar, E. Cuesta, J. Barreiro, Rodrigo A. González and Susana Martínez-Pellitero. Their work appears in journals such as Computers and Electronics in Agriculture, IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) and Measurement Science and Technology.
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.