Rishidev Chaudhuri
- Cognitive Neuroscience top 2%
- Cellular and Molecular Neuroscience top 5%
- Artificial Intelligence top 10%
- Electrical and Electronic Engineering
- Statistical and Nonlinear Physics top 10%
- Co-authors
- Xiao‐Jing WangIla FieteKenneth KnoblauchMarie-Alice GarielHenry KennedyAlexandre PougetMichael N. ShadlenAnne K. Churchland
- Topics
- Neural dynamics and brain function (8 papers)Neural Networks and Applications (4 papers)Memory and Neural Mechanisms (3 papers)
- Partner nations
- United StatesChinaSwitzerland
In The Last Decade
Rishidev Chaudhuri
11 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 81
- Cognitive Neuroscience 955
- Cellular and Molecular Neuroscience 278
- Artificial Intelligence 129
- Electrical and Electronic Engineering 90
- Statistical and Nonlinear Physics 73
Countries citing papers authored by Rishidev Chaudhuri
This map shows the geographic impact of Rishidev Chaudhuri'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 Rishidev Chaudhuri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rishidev Chaudhuri more than expected).
Fields of papers citing papers by Rishidev Chaudhuri
This network shows the impact of papers produced by Rishidev Chaudhuri. 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 Rishidev Chaudhuri. The network helps show where Rishidev Chaudhuri may publish in the future.
Co-authorship network of co-authors of Rishidev Chaudhuri
This figure shows the co-authorship network connecting the top 25 collaborators of Rishidev Chaudhuri. A scholar is included among the top collaborators of Rishidev Chaudhuri 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 Rishidev Chaudhuri. Rishidev Chaudhuri is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | 7 | |
| 3 | 5 | |
| 4 | Bipartite expander Hopfield networks as self-decoding high-capacity error correcting codes | 5 |
| 5 | 171 | |
| 6 | 36 | |
| 7 | 133 | |
| 8 | A Large-Scale Circuit Mechanism for Hierarchical Dynamical Processing in the Primate Cortexbreakdown → | 383 |
| 9 | 44 | |
| 10 | 17 | |
| 11 | 254 |
About Rishidev Chaudhuri
Rishidev Chaudhuri is a scholar working on Cognitive Neuroscience, Statistical and Nonlinear Physics and Artificial Intelligence, having authored 11 papers that have together received 1.1k indexed citations. Recurring topics across this work include Neural dynamics and brain function (8 papers), Neural Networks and Applications (4 papers) and Memory and Neural Mechanisms (3 papers). The work is most often cited by research in Cognitive Neuroscience (955 citations), Cellular and Molecular Neuroscience (278 citations) and General Decision Sciences (21 citations). Rishidev Chaudhuri has collaborated with scholars based in United States, China and Switzerland. Frequent co-authors include Xiao‐Jing Wang, Ila Fiete, Kenneth Knoblauch, Marie-Alice Gariel, Henry Kennedy, Alexandre Pouget, Michael N. Shadlen, Anne K. Churchland, Roozbeh Kiani and Berk Gerçek. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Neuron.
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.