Thomas Mesquida
Impact in
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- Neural dynamics and brain function
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- Advanced Memory and Neural Computing
- Ferroelectric and Negative Capacitance Devices
- CCD and CMOS Imaging Sensors
Papers in
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- Advanced Memory and Neural Computing 14
- Ferroelectric and Negative Capacitance Devices 6
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- Neural dynamics and brain function 8
- Co-authors
- Alexandre Valentian (9 shared papers)Lorena Anghel (5 shared papers)Elisa Vianello (4 shared papers)C. Reita (2 shared papers)Olivier Bichler (2 shared papers)Thomas Dalgaty (6 shared papers)Jérôme Casas (1 shared paper)Melika Payvand (2 shared papers)
- Journals
- Nature Communications (1 paper)IEEE Transactions on Emerging Topics in Computational Intelligence (1 paper)IEEE Transactions on Neural Networks and Learning Systems (1 paper)Lecture notes in computer science (2 papers)2022 International Electron Devices Meeting (IEDM) (1 paper)
- Partner nations
- FranceSwitzerlandItaly
In The Last Decade
Thomas Mesquida
17 papers receiving 260 citations
Peers
Comparison fields: 5 of 42
- Cognitive Neuroscience 73
- Electrical and Electronic Engineering 198
- Cellular and Molecular Neuroscience 52
- Artificial Intelligence 91
- Signal Processing 16
Countries citing papers authored by Thomas Mesquida
This map shows the geographic impact of Thomas Mesquida'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 Thomas Mesquida with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Mesquida more than expected).
Fields of papers citing papers by Thomas Mesquida
This network shows the impact of papers produced by Thomas Mesquida. 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 Thomas Mesquida. The network helps show where Thomas Mesquida may publish in the future.
Co-authors
The 23 scholars most cited alongside Thomas Mesquida, 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 | 2019 | 65 | |
| 2 | 2023 | 53 | |
| 3 | 2022 | 43 | |
| 4 | 2022 | 35 | |
| 5 | 2022 | 12 | |
| 6 | 2022 | 10 | |
| 7 | 2023 | 10 | |
| 8 | 2023 | 7 | |
| 9 | 2023 | 6 | |
| 10 | 2020 | 6 | |
| 11 | 2024 | 5 | |
| 12 | 2023 | 4 | |
| 13 | 2016 | 2 | |
| 14 | 2025 | 1 | |
| 15 | 2022 | 1 | |
| 16 | 2025 | 1 | |
| 17 | 2022 | 1 | |
| 18 | 2025 | 0 |
About Thomas Mesquida
Thomas Mesquida is a scholar working on Electrical and Electronic Engineering, Cognitive Neuroscience, Artificial Intelligence, Cellular and Molecular Neuroscience and Signal Processing, having authored 18 papers that have together received 262 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (14 papers), Neural dynamics and brain function (8 papers), Ferroelectric and Negative Capacitance Devices (6 papers), Neuroscience and Neural Engineering (4 papers), Neural Networks and Applications (3 papers), Neural Networks and Reservoir Computing (3 papers), Underwater Vehicles and Communication Systems (1 paper) and Multisensory perception and integration (1 paper). The work is most often cited by research in Cognitive Neuroscience (73 citations), Electrical and Electronic Engineering (198 citations), Cellular and Molecular Neuroscience (52 citations), Artificial Intelligence (91 citations) and Signal Processing (16 citations). Thomas Mesquida has collaborated with scholars based in France, Switzerland and Italy. Frequent co-authors include Alexandre Valentian, Lorena Anghel, Elisa Vianello, C. Reita, Olivier Bichler, Thomas Dalgaty, Jérôme Casas, Melika Payvand, C. Posch and N. Castellani. Their work appears in journals such as Nature Communications, IEEE Transactions on Emerging Topics in Computational Intelligence, IEEE Transactions on Neural Networks and Learning Systems, Lecture notes in computer science and 2022 International Electron Devices Meeting (IEDM).
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.