Niru Maheswaranathan

3.3k total citations
17 papers, 566 citations indexed

About

Niru Maheswaranathan is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Computer Vision and Pattern Recognition. According to data from OpenAlex, Niru Maheswaranathan has authored 17 papers receiving a total of 566 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 6 papers in Cognitive Neuroscience and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Niru Maheswaranathan's work include Neural dynamics and brain function (5 papers), Advanced Neural Network Applications (3 papers) and Machine Learning and Data Classification (3 papers). Niru Maheswaranathan is often cited by papers focused on Neural dynamics and brain function (5 papers), Advanced Neural Network Applications (3 papers) and Machine Learning and Data Classification (3 papers). Niru Maheswaranathan collaborates with scholars based in United States, Canada and United Kingdom. Niru Maheswaranathan's co-authors include Surya Ganguli, Lisa M. Giocomo, Kiah Hardcastle, Stephen A. Baccus, Aran Nayebi, Lane McIntosh, Jascha Sohl‐Dickstein, David B. Kastner, Taehong Yang and Michael Chiang and has published in prestigious journals such as Neuron, PLoS Computational Biology and Review of Scientific Instruments.

In The Last Decade

Niru Maheswaranathan

17 papers receiving 556 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Niru Maheswaranathan United States 10 372 243 91 74 68 17 566
Dirk Jancke Germany 18 817 2.2× 426 1.8× 53 0.6× 130 1.8× 69 1.0× 36 1.0k
Denis Sheynikhovich France 12 324 0.9× 157 0.6× 47 0.5× 33 0.4× 31 0.5× 19 455
Tony Vladusich Australia 14 485 1.3× 88 0.4× 98 1.1× 46 0.6× 145 2.1× 29 730
Choongkil Lee South Korea 11 679 1.8× 181 0.7× 27 0.3× 68 0.9× 52 0.8× 23 827
Thomas Akam United Kingdom 15 839 2.3× 485 2.0× 62 0.7× 115 1.6× 50 0.7× 27 1.0k
Julija Krupic United Kingdom 9 759 2.0× 542 2.2× 61 0.7× 64 0.9× 24 0.4× 14 895
Alon Rubin Israel 12 862 2.3× 697 2.9× 73 0.8× 66 0.9× 50 0.7× 17 1.1k
Benjamin Dunn Norway 12 907 2.4× 696 2.9× 52 0.6× 51 0.7× 52 0.8× 18 1.1k
Mototaka Suzuki Germany 13 898 2.4× 265 1.1× 40 0.4× 47 0.6× 50 0.7× 23 1.0k
Marius Bauža United Kingdom 8 554 1.5× 366 1.5× 45 0.5× 43 0.6× 22 0.3× 15 677

Countries citing papers authored by Niru Maheswaranathan

Since Specialization
Citations

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

Fields of papers citing papers by Niru Maheswaranathan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Niru Maheswaranathan

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

All Works

17 of 17 papers shown
1.
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
2.
Stein, Heike, et al.. (2021). A mechanistically interpretable model of the retinal neural code for natural scenes with multiscale adaptive dynamics. 2021 55th Asilomar Conference on Signals, Systems, and Computers. 32. 287–291. 1 indexed citations
3.
Williams, Alex H., Ben Poole, Niru Maheswaranathan, et al.. (2019). Discovering Precise Temporal Patterns in Large-Scale Neural Recordings through Robust and Interpretable Time Warping. Neuron. 105(2). 246–259.e8. 47 indexed citations
4.
Maheswaranathan, Niru, David B. Kastner, Stephen A. Baccus, & Surya Ganguli. (2018). Inferring hidden structure in multilayered neural circuits. PLoS Computational Biology. 14(8). e1006291–e1006291. 42 indexed citations
5.
Metz, Luke, Niru Maheswaranathan, Brian Cheung, & Jascha Sohl‐Dickstein. (2018). Learning Unsupervised Learning Rules. arXiv (Cornell University). 9 indexed citations
6.
Metz, Luke, Niru Maheswaranathan, Brian Cheung, & Jascha Sohl‐Dickstein. (2018). Meta-Learning Update Rules for Unsupervised Representation Learning. International Conference on Learning Representations. 4 indexed citations
7.
Metz, Luke, et al.. (2018). Learned optimizers that outperform SGD on wall-clock and validation loss. arXiv (Cornell University). 3 indexed citations
8.
Metz, Luke, et al.. (2018). Understanding and correcting pathologies in the training of learned optimizers. arXiv (Cornell University). 4556–4565. 12 indexed citations
9.
Maheswaranathan, Niru, Luke Metz, George Tucker, Dami Choi, & Jascha Sohl‐Dickstein. (2018). Guided Evolutionary Strategies: Escaping the curse of dimensionality in random search. 7 indexed citations
10.
Maheswaranathan, Niru, Luke Metz, George Tucker, Dami Choi, & Jascha Sohl‐Dickstein. (2018). Guided evolutionary strategies: Augmenting random search with surrogate gradients. arXiv (Cornell University). 4264–4273. 6 indexed citations
11.
Hardcastle, Kiah, Niru Maheswaranathan, Surya Ganguli, & Lisa M. Giocomo. (2017). A Multiplexed, Heterogeneous, and Adaptive Code for Navigation in Medial Entorhinal Cortex. Neuron. 94(2). 375–387.e7. 176 indexed citations
12.
Yang, Taehong, Cindy F. Yang, Niru Maheswaranathan, et al.. (2017). Social Control of Hypothalamus-Mediated Male Aggression. Neuron. 95(4). 955–970.e4. 106 indexed citations
13.
Maheswaranathan, Niru, Matthew W. Hoffman, Sergio Gómez Colmenarejo, et al.. (2017). Learned Optimizers that Scale and Generalize. arXiv (Cornell University). 3751–3760. 38 indexed citations
14.
Maheswaranathan, Niru, et al.. (2017). Pyret: A Python package for analysis of neurophysiology data. The Journal of Open Source Software. 2(9). 137–137. 2 indexed citations
15.
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
16.
Maheswaranathan, Niru. (2012). Emergent bursting and synchrony in computer simulations of neuronal cultures. Frontiers in Computational Neuroscience. 6. 15–15. 18 indexed citations
17.
Lake, Russell E., et al.. (2008). Vacancy island creation and coalescence using automated scanning tunneling microscopy. Review of Scientific Instruments. 79(1). 13703–13703. 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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