Aran Nayebi

1.9k total citations
14 papers, 360 citations indexed

About

Aran Nayebi is a scholar working on Cognitive Neuroscience, Artificial Intelligence and Cellular and Molecular Neuroscience. According to data from OpenAlex, Aran Nayebi has authored 14 papers receiving a total of 360 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Cognitive Neuroscience, 4 papers in Artificial Intelligence and 3 papers in Cellular and Molecular Neuroscience. Recurrent topics in Aran Nayebi's work include Neural dynamics and brain function (9 papers), Face Recognition and Perception (4 papers) and Visual perception and processing mechanisms (4 papers). Aran Nayebi is often cited by papers focused on Neural dynamics and brain function (9 papers), Face Recognition and Perception (4 papers) and Visual perception and processing mechanisms (4 papers). Aran Nayebi collaborates with scholars based in United States, Belgium and Latvia. Aran Nayebi's co-authors include Daniel Yamins, James J. DiCarlo, Martin Schrimpf, Chengxu Zhuang, Siming Yan, Michael C. Frank, Surya Ganguli, Stephen A. Baccus, Niru Maheswaranathan and Lane McIntosh and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Neuron and Cell Reports.

In The Last Decade

Aran Nayebi

14 papers receiving 357 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Aran Nayebi United States	8	290	73	63	61	41	14	360
Kei Majima Japan	11	391 1.3×	114 1.6×	54 0.9×	127 2.1×	41 1.0×	27	570
Edgar Y. Walker United States	8	349 1.2×	51 0.7×	46 0.7×	71 1.2×	32 0.8×	12	424
Till S. Hartmann United States	6	202 0.7×	36 0.5×	19 0.3×	38 0.6×	24 0.6×	11	231
Kailyn Schmidt United States	4	444 1.5×	143 2.0×	95 1.5×	41 0.7×	11 0.3×	8	544
Eizaburo Doi United States	9	180 0.6×	36 0.5×	31 0.5×	47 0.8×	78 1.9×	10	245
Darragh Smyth United Kingdom	9	377 1.3×	39 0.5×	59 0.9×	205 3.4×	82 2.0×	14	457
Matthias Nau Germany	10	435 1.5×	84 1.2×	48 0.8×	87 1.4×	17 0.4×	17	538
Makoto Nishizaki Japan	5	261 0.9×	36 0.5×	39 0.6×	71 1.2×	41 1.0×	9	360
Corey M. Ziemba United States	10	452 1.6×	93 1.3×	19 0.3×	71 1.2×	30 0.7×	17	506
Shreya Saxena United States	10	260 0.9×	19 0.3×	60 1.0×	114 1.9×	22 0.5×	25	368

Countries citing papers authored by Aran Nayebi

Since Specialization

Citations

This map shows the geographic impact of Aran Nayebi'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 Aran Nayebi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aran Nayebi more than expected).

Fields of papers citing papers by Aran Nayebi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Aran Nayebi. 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 Aran Nayebi. The network helps show where Aran Nayebi may publish in the future.

Co-authorship network of co-authors of Aran Nayebi

This figure shows the co-authorship network connecting the top 25 collaborators of Aran Nayebi. A scholar is included among the top collaborators of Aran Nayebi 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 Aran Nayebi. Aran Nayebi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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14 of 14 papers shown

Maheswaranathan, Niru, Lane McIntosh, David B. Kastner, et al.. (2023). Interpreting the retinal neural code for natural scenes: From computations to neurons. Neuron. 111(17). 2742–2755.e4. 16 indexed citations

Nayebi, Aran, et al.. (2023). Mouse visual cortex as a limited resource system that self-learns an ecologically-general representation. PLoS Computational Biology. 19(10). e1011506–e1011506. 14 indexed citations

Nayebi, Aran, Daniel M. Bear, Kohitij Kar, et al.. (2022). Recurrent Connections in the Primate Ventral Visual Stream Mediate a Trade-Off Between Task Performance and Network Size During Core Object Recognition. Neural Computation. 34(8). 1652–1675. 9 indexed citations

Zhuang, Chengxu, Siming Yan, Aran Nayebi, et al.. (2021). Unsupervised neural network models of the ventral visual stream. Proceedings of the National Academy of Sciences. 118(3). 169 indexed citations

Nayebi, Aran, Bart C. Jongbloets, Dale A. Fortin, et al.. (2021). Distinct in vivo dynamics of excitatory synapses onto cortical pyramidal neurons and parvalbumin-positive interneurons. Cell Reports. 37(6). 109972–109972. 10 indexed citations

Nayebi, Aran, Bart C. Jongbloets, Dale A. Fortin, et al.. (2021). Distinct <i>in vivo</i> Dynamics of Excitatory Synapses Onto Cortical Pyramidal Neurons and Inhibitory Interneurons. SSRN Electronic Journal. 1 indexed citations

Kunin, Daniel, et al.. (2020). Two Routes to Scalable Credit Assignment without Weight Symmetry. International Conference on Machine Learning. 1. 5511–5521. 2 indexed citations

Zhuang, Chengxu, Siming Yan, Aran Nayebi, & Daniel Yamins. (2019). Self-supervised Neural Network Models of Higher Visual Cortex Development. 2 indexed citations

Kubilius, Jonas, Martin Schrimpf, Kohitij Kar, et al.. (2019). Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs. Lirias (KU Leuven). 32. 12785–12796. 35 indexed citations

10.

Nayebi, Aran, Daniel M. Bear, Jonas Kubilius, et al.. (2018). Task-driven convolutional recurrent models of the visual system. Lirias (KU Leuven). 31. 5290–5301. 16 indexed citations

11.

Nayebi, Aran, Jonas Kubilius, Daniel M. Bear, et al.. (2018). Convolutional recurrent neural network models of dynamics in higher visual cortex. Journal of Vision. 18(10). 717–717. 2 indexed citations

12.

McIntosh, Lane, Niru Maheswaranathan, Aran Nayebi, Surya Ganguli, & Stephen A. Baccus. (2016). Deep Learning Models of the Retinal Response to Natural Scenes.. PubMed. 29. 1369–1377. 78 indexed citations

13.

Nayebi, Aran, Scott Aaronson, Aleksandrs Belovs, & Luca Trevisan. (2015). Quantum lower bound for inverting a permutation with advice. Quantum Information and Computation. 15(11&12). 901–913. 5 indexed citations

14.

Nayebi, Aran. (2012). Plausible hypercomputability. arXiv (Cornell University). 1 indexed citations

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.

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