Science Explorer Interactive view Map
Topic · Artificial Intelligence

Neural Networks and Reservoir Computing

Neural Networks and Reservoir Computing is a research topic within Artificial Intelligence. Science Explorer counts 18k research works in it since 1955. 21.5% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the application of photonic reservoir computing for neural computation, machine learning, and information processing. It explores the use of semiconductor lasers, neuromorphic photonics, and optical neural networks, as well as the implementation of echo state networks and nonlinear dynamics in photonic systems.

  • Photonic Reservoir Computing
  • Neuromorphic Photonics
  • Optical Neural Networks
  • Machine Learning
  • Semiconductor Lasers
  • Echo State Networks
  • Nonlinear Dynamics
  • Optoelectronic Reservoir Computing
  • Diffractive Optical Neural Networks
  • Neural Network Training
Research works
18k
fractional, since 1955
In the world top 10%
3.9k
per year above
Top-10% rate
21.5%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+116%
the tick is no change

Which countries lead Neural Networks and Reservoir Computing research?

By volume, China and the United States publish the most (2k and 1.2k works in 2022–2025).

By volume, 2022–2025

  1. 1 China 2k works
  2. 2 United States 1.2k works
  3. 3 Japan 407 works
  4. 4 India 310 works
  5. 5 Germany 294 works
  6. 6 United Kingdom 234 works
  7. 7 South Korea 211 works
  8. 8 Italy 209 works
  9. 9 France 182 works
  10. 10 Canada 149 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 39.3%United States: 22.2%Japan: 7.9%India: 6.0%6 others listed: 24.7%39%largest
China2,036 · 39.3%United States1,150 · 22.2%Japan407 · 7.9%India310 · 6.0%6 others listed1,279 · 24.7%

Shares of the rows listed above, not of the whole node.

Which institutions lead Neural Networks and Reservoir Computing research?

By volume in 2022–2025, The University of Tokyo publishes the most Neural Networks and Reservoir Computing research, followed by Tsinghua University and Shanghai Jiao Tong University.

By volume, 2022–2025

  1. 1 The University of TokyoJapan 65 works
  2. 2 Tsinghua UniversityChina 59 works
  3. 3 Shanghai Jiao Tong UniversityChina 55 works
  4. 4 Beijing University of Posts and TelecommunicationsChina 54 works
  5. 5 University of Electronic Science and Technology of ChinaChina 53 works
  6. 6 Zhejiang UniversityChina 46 works
  7. 7 Huazhong University of Science and TechnologyChina 44 works
  8. 8 Chinese Academy of SciencesChina 41 works
  9. 9 Peking UniversityChina 36 works
  10. 10 Xidian UniversityChina 30 works

Who are the leading researchers in Neural Networks and Reservoir Computing?

The most-cited researchers publishing on Neural Networks and Reservoir Computing include Kenji Watanabe, Takashi Taniguchi and Guanrong Chen.

  1. 1 Kenji Watanabe Japan 6.4k citations
  2. 2 Takashi Taniguchi Japan 6.2k citations
  3. 3 Guanrong Chen Hong Kong 5.4k citations
  4. 4 Lei Zhang Hong Kong 5.3k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

Where is Neural Networks and Reservoir Computing research done?

The largest centres of Neural Networks and Reservoir Computing research in 2022–2025 are Beijing (China), Shanghai (China), Tokyo (Japan) and Nanjing (China). Among places with at least 20 works in it, it is an unusually large share of all research in Eindhoven.

Largest cities, 2022–2025

  1. 1 Beijing China 449 works
  2. 2 Shanghai China 196 works
  3. 3 Tokyo Japan 174 works
  4. 4 Nanjing China 129 works
  5. 5 Seoul South Korea 113 works
  6. 6 Hangzhou China 104 works
  7. 7 Chengdu China 104 works
  8. 8 Wuhan China 94 works
  9. 9 Xi'an China 88 works
  10. 10 Singapore Singapore 79 works

Where it is the local speciality

  1. EindhovenNL · 24.9 works8.7×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Neural Networks and Reservoir Computing than the world average.

See Neural Networks and Reservoir Computing on the map

Where is the best place to study Neural Networks and Reservoir Computing?

Among universities, judged by research, The University of Tokyo, Dongguk University and Korea Advanced Institute of Science and Technology score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%60%mean 31.38%fractional works in this node (log) →share in the world top 10% →The University of Tokyo: 65, 21.9%Dongguk University: 14, 49.8%Korea Advanced Institute of Science and Technology: 22, 32.7%École Polytechnique Fédérale de Lausanne: 19, 31.5%Nanjing University of Posts and Telecommunications: 27, 19.4%Beijing University of Posts and Telecommunications: 54, 15.3%University of Shanghai for Science and Technology: 24, 39.2%Technische Universität Ilmenau: 10, 43.0%Massachusetts Institute of Technology: 27, 31.2%Tsinghua University: 59, 29.8%Dongguk UniversityKorea Advanced Insti…École Polytechnique …The University of To…
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 The University of TokyoJapan 68.421.9%8.7×65 +157.4%
2 Dongguk UniversitySouth Korea 67.549.8%13.0×14 —
3 Korea Advanced Institute of Science and TechnologySouth Korea 64.732.7%7.7×22 +314.1%
4 École Polytechnique Fédérale de LausanneSwitzerland 64.631.5%7.3×19 +192.4%
5 Nanjing University of Posts and TelecommunicationsChina 63.119.4%10.0×27 +265.3%
6 Beijing University of Posts and TelecommunicationsChina 63.015.3%13.9×54 +130.3%
7 University of Shanghai for Science and TechnologyChina 61.439.2%8.7×24 —
8 Technische Universität IlmenauGermany 60.143.0%16.7×10 —
9 Massachusetts Institute of TechnologyUnited States 59.031.2%7.0×27 +96.6%
10 Tsinghua UniversityChina 58.829.8%4.8×59 +114.8%

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Neural Networks and Reservoir Computing research growing?

Output in 2018–2022 was 116% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Neural Networks and Reservoir Computing.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.