Corinne Teeter

1.7k total citations
11 papers, 191 citations indexed

About

Corinne Teeter is a scholar working on Cognitive Neuroscience, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Corinne Teeter has authored 11 papers receiving a total of 191 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Cognitive Neuroscience, 5 papers in Artificial Intelligence and 5 papers in Electrical and Electronic Engineering. Recurrent topics in Corinne Teeter's work include Neural dynamics and brain function (6 papers), Neural Networks and Reservoir Computing (4 papers) and Advanced Memory and Neural Computing (4 papers). Corinne Teeter is often cited by papers focused on Neural dynamics and brain function (6 papers), Neural Networks and Reservoir Computing (4 papers) and Advanced Memory and Neural Computing (4 papers). Corinne Teeter collaborates with scholars based in United States. Corinne Teeter's co-authors include Charles F. Stevens, Nicholas Cain, Jim Berg, Aaron Szafer, Hongkui Zeng, Michael Hawrylycz, Ştefan Mihalaş, Ramakrishnan Iyer, Christof Koch and Vilas Menon and has published in prestigious journals such as Nature Communications, Current Biology and Optics Express.

In The Last Decade

Corinne Teeter

9 papers receiving 190 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Corinne Teeter United States	4	117	73	71	34	25	11	191
Nicole Voges France	11	219 1.9×	141 1.9×	45 0.6×	18 0.5×	34 1.4×	18	321
Benjamin Lansdell United States	7	150 1.3×	68 0.9×	50 0.7×	84 2.5×	14 0.6×	11	293
Kael Dai United States	7	229 2.0×	121 1.7×	73 1.0×	15 0.4×	16 0.6×	9	271
Alexandre Payeur Canada	7	164 1.4×	87 1.2×	100 1.4×	57 1.7×	28 1.1×	12	226
Matteo Cantarelli United Kingdom	4	116 1.0×	77 1.1×	34 0.5×	20 0.6×	13 0.5×	11	234
Giuseppe Chindemi Switzerland	4	177 1.5×	96 1.3×	51 0.7×	15 0.4×	55 2.2×	6	319
Zachary W. Davis United States	6	193 1.6×	98 1.3×	28 0.4×	16 0.5×	17 0.7×	12	217
Bóris Marin United Kingdom	5	91 0.8×	60 0.8×	33 0.5×	13 0.4×	18 0.7×	19	178
Kevin A. Archie United States	7	285 2.4×	149 2.0×	53 0.7×	28 0.8×	15 0.6×	10	353
Cristiano Capone Italy	10	251 2.1×	120 1.6×	60 0.8×	20 0.6×	42 1.7×	22	285

Countries citing papers authored by Corinne Teeter

Since Specialization

Citations

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

Fields of papers citing papers by Corinne Teeter

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Corinne Teeter

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

All Works

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11 of 11 papers shown

1.

Iyer, Prasad P., Gaurang R. Bhatt, Saaketh Desai, et al.. (2025). Is Computing with Light All You Need? A Perspective on Codesign for Optical Artificial Intelligence and Scientific Computing. Advanced Intelligent Systems. 8(1).

2.

Léonard, François, Elliot J. Fuller, Corinne Teeter, & Craig M. Vineyard. (2024). Role of depth in optical diffractive neural networks. Optics Express. 32(13). 23125–23125. 1 indexed citations

3.

Chapman, G. William, et al.. (2024). Biological Dynamics Enabling Training of Binary Recurrent Networks. 1–7.

4.

Teeter, Corinne, et al.. (2023). Context Modulation Enables Multi-tasking and Resource Efficiency in Liquid State Machines. 1–9. 1 indexed citations

5.

Vineyard, Craig M., Suma Cardwell, Frances S. Chance, et al.. (2022). Neural Mini-Apps as a Tool for Neuromorphic Computing Insight. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 40–49. 3 indexed citations

6.

Wang, Felix, et al.. (2022). Distributed Localization with Grid-based Representations on Digital Elevation Models. UA Campus Repository (The University of Arizona). 1–5. 2 indexed citations

7.

Teeter, Corinne, Ramakrishnan Iyer, Vilas Menon, et al.. (2018). Generalized leaky integrate-and-fire models classify multiple neuron types. Nature Communications. 9(1). 709–709. 129 indexed citations

8.

Stokes, Caleb, Corinne Teeter, & Jeffry S. Isaacson. (2014). Single dendrite-targeting interneurons generate branch-specific inhibition. Frontiers in Neural Circuits. 8. 139–139. 10 indexed citations

9.

Teeter, Corinne & Charles F. Stevens. (2011). A General Principle of Neural Arbor Branch Density. Current Biology. 21(24). 2105–2108. 35 indexed citations

10.

Teeter, Corinne. (2010). Characterizing the Spatial Density Functions of Neural Arbors. eScholarship (California Digital Library). 1 indexed citations

11.

Nieto, Michael Martin, et al.. (2005). Detection of Antineutrinos for Nonproliferation. Nuclear Science and Engineering. 149(3). 270–276. 9 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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