Daniel Neil
Impact in
- Cognitive Neuroscience top 2%
- 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
- CCD and CMOS Imaging Sensors 9
- Ferroelectric and Negative Capacitance Devices 6
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- Neural dynamics and brain function 9
- Co-authors
- Shih‐Chii Liu (19 shared papers)Michael Pfeiffer (7 shared papers)Tobi Delbrück (10 shared papers)Jonathan Binas (3 shared papers)Matthew Cook (1 shared paper)Peter U. Diehl (1 shared paper)Peter O’Connor (1 shared paper)Alix M.B. Lacoste (2 shared papers)
- Journals
- Frontiers in Neuroscience (3 papers)IEEE Transactions on Very Large Scale Integration (VLSI) Systems (1 paper)Scientific Reports (1 paper)Nature Reviews Neurology (1 paper)Open MIND (3 papers)
- Partner nations
- SwitzerlandUnited KingdomFrance
In The Last Decade
Daniel Neil
26 papers receiving 2.5k citations
Daniel Neil's Hit Papers
Peers
Comparison fields: 5 of 143
- Cognitive Neuroscience 1.1k
- Electrical and Electronic Engineering 1.6k
- Health Informatics 33
- Artificial Intelligence 831
- Cellular and Molecular Neuroscience 403
Countries citing papers authored by Daniel Neil
This map shows the geographic impact of Daniel Neil'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 Daniel Neil with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Neil more than expected).
Fields of papers citing papers by Daniel Neil
This network shows the impact of papers produced by Daniel Neil. 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 Daniel Neil. The network helps show where Daniel Neil may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Neil, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing Hit paper breakdown → | 2015 | 683 |
| 2 | Applications of machine learning to diagnosis and treatment of neurodegenerative diseases Hit paper breakdown → | 2020 | 408 |
| 3 | 2013 | 325 | |
| 4 | 2014 | 197 | |
| 5 | 2016 | 122 | |
| 6 | 2018 | 110 | |
| 7 | 2018 | 82 | |
| 8 | 2015 | 74 | |
| 9 | 2016 | 63 | |
| 10 | 2015 | 62 | |
| 11 | 2016 | 60 | |
| 12 | 2020 | 56 | |
| 13 | 2017 | 55 | |
| 14 | 2016 | 53 | |
| 15 | 2017 | 36 | |
| 16 | 2020 | 35 | |
| 17 | Exploring Deep Recurrent Models with Reinforcement Learning for Molecule Design | 2018 | 35 |
| 18 | 2016 | 29 | |
| 19 | 2016 | 18 | |
| 20 | 2018 | 16 |
About Daniel Neil
Daniel Neil is a scholar working on Electrical and Electronic Engineering, Cognitive Neuroscience, Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 27 papers that have together received 2.6k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (14 papers), Neural dynamics and brain function (9 papers), CCD and CMOS Imaging Sensors (9 papers), Ferroelectric and Negative Capacitance Devices (6 papers), Music and Audio Processing (6 papers), Speech and Audio Processing (6 papers), Neural Networks and Applications (3 papers) and Advanced Neural Network Applications (2 papers). The work is most often cited by research in Cognitive Neuroscience (1.1k citations), Electrical and Electronic Engineering (1.6k citations), Health Informatics (33 citations), Artificial Intelligence (831 citations) and Cellular and Molecular Neuroscience (403 citations). Daniel Neil has collaborated with scholars based in Switzerland, United Kingdom and France. Frequent co-authors include Shih‐Chii Liu, Michael Pfeiffer, Tobi Delbrück, Jonathan Binas, Matthew Cook, Peter U. Diehl, Peter O’Connor, Alix M.B. Lacoste, Guillaume M. Hautbergue and Amir Saffari. Their work appears in journals such as Frontiers in Neuroscience, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Scientific Reports, Nature Reviews Neurology and Open MIND.
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.