Nihat Ay
Impact in
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- Statistical Mechanics and Entropy
- Cognitive Neuroscience top 5%
- Neural dynamics and brain function
- Functional Brain Connectivity Studies
- Embodied and Extended Cognition
Papers in
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- Neural Networks and Applications 16
- Bayesian Modeling and Causal Inference 6
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- Statistical Mechanics and Entropy 12
- Co-authors
- Jürgen Jost (11 shared papers)Eckehard Olbrich (10 shared papers)Daniel Polani (3 shared papers)Nils Bertschinger (9 shared papers)Ralf Der (5 shared papers)Guido Montúfar (8 shared papers)Johannes Rauh (5 shared papers)Thomas Wennekers (8 shared papers)
- Journals
- Theory in Biosciences (6 papers)Neurocomputing (4 papers)Neural Computation (3 papers)Advances in Complex Systems (3 papers)Chaos An Interdisciplinary Journal of Nonlinear Science (2 papers)
- Partner nations
- GermanyUnited StatesUnited Kingdom
In The Last Decade
Nihat Ay
74 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 112
- Statistical and Nonlinear Physics 389
- Cognitive Neuroscience 450
- Artificial Intelligence 466
- Developmental Biology 25
- Computational Theory and Mathematics 180
Countries citing papers authored by Nihat Ay
This map shows the geographic impact of Nihat Ay'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 Nihat Ay with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nihat Ay more than expected).
Fields of papers citing papers by Nihat Ay
This network shows the impact of papers produced by Nihat Ay. 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 Nihat Ay. The network helps show where Nihat Ay may publish in the future.
Co-authors
The 25 scholars most cited alongside Nihat Ay, 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 79 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 157 | |
| 2 | 2014 | 145 | |
| 3 | 2017 | 119 | |
| 4 | 2008 | 95 | |
| 5 | 2007 | 61 | |
| 6 | 2007 | 55 | |
| 7 | 2011 | 53 | |
| 8 | 2015 | 42 | |
| 9 | 2013 | 36 | |
| 10 | 2011 | 35 | |
| 11 | 2015 | 26 | |
| 12 | 2003 | 25 | |
| 13 | 2006 | 24 | |
| 14 | 2011 | 24 | |
| 15 | 2015 | 22 | |
| 16 | 2002 | 21 | |
| 17 | 2009 | 19 | |
| 18 | 2010 | 18 | |
| 19 | 2015 | 17 | |
| 20 | 2010 | 17 |
About Nihat Ay
Nihat Ay is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Cognitive Neuroscience, Computational Theory and Mathematics and Molecular Biology, having authored 79 papers that have together received 1.4k indexed citations. Recurring topics across this work include Neural dynamics and brain function (22 papers), Neural Networks and Applications (16 papers), Statistical Mechanics and Entropy (12 papers), Gene Regulatory Network Analysis (8 papers), Computability, Logic, AI Algorithms (6 papers), Bayesian Modeling and Causal Inference (6 papers), Complex Systems and Time Series Analysis (6 papers) and Topological and Geometric Data Analysis (5 papers). The work is most often cited by research in Statistical and Nonlinear Physics (389 citations), Cognitive Neuroscience (450 citations), Artificial Intelligence (466 citations), Developmental Biology (25 citations) and Computational Theory and Mathematics (180 citations). Nihat Ay has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Jürgen Jost, Eckehard Olbrich, Daniel Polani, Nils Bertschinger, Ralf Der, Guido Montúfar, Johannes Rauh, Thomas Wennekers, Hông Vân Lê and David C. Krakauer. Their work appears in journals such as Theory in Biosciences, Neurocomputing, Neural Computation, Advances in Complex Systems and Chaos An Interdisciplinary Journal of Nonlinear Science.
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.