Andrés Upegui
- Hardware and Architecture top 10%
- Embedded Systems Design Techniques 8
- Parallel Computing and Optimization Techniques 4
- Artificial Intelligence top 10%
- Evolutionary Algorithms and Applications 9
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- Neural dynamics and brain function 4
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- Modular Robots and Swarm Intelligence 13
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- Interconnection Networks and Systems 6
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- Advanced Memory and Neural Computing 11
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- Cellular Automata and Applications 7
- Co-authors
- Eduardo García SánchezCarlos Andrés Peña-ReyesRico MoeckelAuke Jan IjspeertJorge PeñaYann ThomaAndrés Pérez-UribeQuentin Berthet
- Partner nations
- SwitzerlandFranceNetherlands
In The Last Decade
Andrés Upegui
32 papers receiving 309 citations
Peers
Comparison fields: 5 of 53
- Hardware and Architecture 52
- Artificial Intelligence 150
- Cognitive Neuroscience 57
- Mechanical Engineering 97
- Computer Networks and Communications 58
Countries citing papers authored by Andrés Upegui
This map shows the geographic impact of Andrés Upegui'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 Andrés Upegui with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrés Upegui more than expected).
Fields of papers citing papers by Andrés Upegui
This network shows the impact of papers produced by Andrés Upegui. 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 Andrés Upegui. The network helps show where Andrés Upegui may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Andrés Upegui, 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 | 2023 | 1 | |
| 2 | 2023 | 2 | |
| 3 | 2022 | 7 | |
| 4 | 2022 | 0 | |
| 5 | 2021 | 23 | |
| 6 | 2021 | 3 | |
| 7 | 2020 | 1 | |
| 8 | 2020 | 4 | |
| 9 | 2019 | 11 | |
| 10 | 2018 | 1 | |
| 11 | 2017 | 2 | |
| 12 | 2017 | 2 | |
| 13 | 2012 | 5 | |
| 14 | 2008 | 3 | |
| 15 | 2008 | 5 | |
| 16 | 2007 | 33 | |
| 17 | 2006 | 3 | |
| 18 | 2006 | 3 | |
| 19 | 2006 | 9 | |
| 20 | 2005 | 13 |
About Andrés Upegui
Andrés Upegui is a scholar working on Hardware and Architecture, Artificial Intelligence, Computational Theory and Mathematics, Computer Networks and Communications and Mechanical Engineering, having authored 35 papers that have together received 340 indexed citations. Recurring topics across this work include Modular Robots and Swarm Intelligence (13 papers), Advanced Memory and Neural Computing (11 papers), Evolutionary Algorithms and Applications (9 papers), Embedded Systems Design Techniques (8 papers), Cellular Automata and Applications (7 papers), Interconnection Networks and Systems (6 papers), Neural dynamics and brain function (4 papers) and Parallel Computing and Optimization Techniques (4 papers). The work is most often cited by research in Hardware and Architecture (52 citations), Artificial Intelligence (150 citations), Cognitive Neuroscience (57 citations), Mechanical Engineering (97 citations) and Computer Networks and Communications (58 citations). Andrés Upegui has collaborated with scholars based in Switzerland, France and Netherlands. Frequent co-authors include Eduardo García Sánchez, Carlos Andrés Peña-Reyes, Rico Moeckel, Auke Jan Ijspeert, Jorge Peña, Yann Thoma, Andrés Pérez-Uribe, Quentin Berthet, Jordi Madrenas and Alexandre Duc. Their work appears in journals such as Electronics, Frontiers in Neuroscience, Memetic Computing, Industrial Robot the international journal of robotics research and application and Microprocessors and Microsystems.
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.