Sony Corporation (United States)
In research, Sony Corporation (United States) stands highest in Physical Sciences (#8,699 of 12,888 worldwide), 2022–2025. Relative to its size it is most specialised in Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Science — Computer Vision and Pattern Recognition is 14.4× its share of world research.
- World rank, 2022–2025
- #16,919 of 28,054 · #6,822 all time
- Rank in United States
- #2,408 of 4,192
- Research works
- 1.1k ▲ 32% vs 2013–17
- Citations
- 14k 12.2 per fractional work
- Top-10% rate
- 16.8% record average 16.5%
- Open access
- 33% world 28%
What is Sony Corporation (United States) known for in research?
The fields where it stands highest, 2022–2025, ranked among every institution above the floor in each field.
| Field | World rank | Where that sits | Top-10% rate | Works | All time |
|---|---|---|---|---|---|
| Physical SciencesDomain | #8,699 of 12,888 | 18.3% | 88 | #4142 |
Each strip is that field’s whole ranked pool, with the notch where Sony Corporation (United States) sits in it, in the colour of the band that rank falls in. The track under the rate is the rate itself: it carries no world mark, because the world rate differs by field (from about 6% to 21% in this record).
What does Sony Corporation (United States) specialise in?
Where its research is concentrated relative to its size: Computer Vision and Pattern Recognition takes 14.4× the share of its output that it takes of world research.
- Computer Vision and Pattern RecognitionSubfield · 20.7 works14×
- Artificial IntelligenceSubfield · 22.9 works8.3×
- Computer ScienceField · 57.0 works6.4×
Location quotient, a volume reading rather than an impact one. It surfaces small, lopsided specialities.
Field profile
Location quotient across every field it publishes in: outside the ring is more than an institution of this size would be expected to publish, inside it is less.
Rings at 0.5×, 1× and 2×. Widest outward: Computer Science, 6.4×. Every wedge is a field page.
- Computer Science 6.4×
- Neuroscience 1.7×
- Physics and Astronomy 1.4×
- Engineering 1.2×
- Earth and Planetary Sciences 1.1×
- Psychology 0.8×
- Biochemistry, Genetics and Molecular Biology 0.6×
- Decision Sciences 0.6×
- Mathematics 0.6×
- Materials Science 0.5×
- Economics, Econometrics and Finance 0.5×
- Environmental Science 0.4×
- Health Professions 0.4×
- Arts and Humanities 0.4×
- Business, Management and Accounting 0.3×
- Medicine 0.3×
- Social Sciences 0.2×
- Nursing 0.2×
- Immunology and Microbiology 0.1×
- Chemical Engineering 0.1×
- Chemistry 0.1×
- Agricultural and Biological Sciences 0.1×
Who are the top researchers at Sony Corporation (United States)?
Ranked on the composite score, Alice Xiang, Lingjuan Lyu and Yuichi Tokita lead among researchers whose main affiliation is Sony Corporation (United States).
- 1 Alice Xiang United States · #209,505 worldwide 174 citations · 19 works
- 2 Lingjuan Lyu United States · #349,616 worldwide 280 citations · 69 works
- 3 Yuichi Tokita United States · #563,527 worldwide 101 citations · 21 works
- 4 Yuki Mitsufuji United States · #904,650 worldwide 87 citations · 59 works
Which keywords describe research at Sony Corporation (United States)?
By fractional works in 2022–2025, weighted toward what it does more of than the world: Deep Learning, Neural Networks, Convolutional Neural Networks, Machine Learning, Unsupervised Learning, Representation Learning, Image Processing and Convolutional Networks.
- Sparse Representations
- Robustness
- Image Denoising
- Domain Adaptation
- Transfer Learning
- Distributed Systems
- Cloud Computing
- Robotics
- Semi-Supervised Learning
- Machine Vision
- Object Detection
- Microscopy
- Hyperspectral Imaging
- Image Classification
- Depth Estimation
- Artificial Intelligence
- Image Processing
- Representation Learning
- Convolutional Neural Networks
- Neural Networks
- Deep Learning
- Machine Learning
- Unsupervised Learning
- Big Data
- Convolutional Networks
- Security
- Multi-Agent Systems
- Computer Vision
- Generative Adversarial Networks
- Image Recognition
- Deep Neural Networks
- Reinforcement Learning
- Meta-Learning
- Wavelet Transform
- Differential Privacy
- Federated Learning
- Adversarial Examples
- Few-Shot Learning
- Machine Translation
- Sparse Representation
Size is fractional works in 2022–2025 in the topics tagged with each word; colour is the word's share of this institution's work against its share of the world's. The 40 words are chosen for being large and distinctive. Each links to the topic it comes from most.
All 40 words, with their numbers
- Deep Learning33▲ 8.4×46 topics
- Neural Networks18▲ 10.0×19 topics
- Machine Learning13▲ 3.6×31 topics
- Convolutional Neural Networks10▲ 11×11 topics
- Unsupervised Learning6▲ 38×3 topics
- Representation Learning5▲ 29×3 topics
- Big Data4▲ 4.3×10 topics
- Image Processing4▲ 8.3×5 topics
- Convolutional Networks4▲ 26×3 topics
- Artificial Intelligence4▲ 2.5×11 topics
- Security4▲ 5.2×6 topics
- Depth Estimation4▲ 38×2 topics
- Multi-Agent Systems4▲ 16×4 topics
- Image Classification3▲ 17×2 topics
- Computer Vision3▲ 11×2 topics
- Hyperspectral Imaging3▲ 10×3 topics
- Generative Adversarial Networks3▲ 34×2 topics
- Microscopy3▲ 39×2 topics
- Image Recognition3▲ 20×1 topic
- Object Detection3▲ 21×1 topic
- Deep Neural Networks3▲ 23×3 topics
- Machine Vision3▲ 11×2 topics
- Reinforcement Learning3▲ 23×3 topics
- Semi-Supervised Learning3▲ 23×3 topics
- Meta-Learning3▲ 29×2 topics
- Robotics2▲ 9.1×3 topics
- Wavelet Transform2▲ 9.0×2 topics
- Cloud Computing2▲ 7.4×4 topics
- Differential Privacy2▲ 27×1 topic
- Distributed Systems2▲ 12×3 topics
- Federated Learning2▲ 27×1 topic
- Transfer Learning2▲ 10×2 topics
- Adversarial Examples2▲ 38×1 topic
- Domain Adaptation2▲ 37×1 topic
- Few-Shot Learning2▲ 37×1 topic
- Image Denoising2▲ 41×1 topic
- Machine Translation2▲ 11×1 topic
- Robustness2▲ 38×1 topic
- Sparse Representation2▲ 9.7×6 topics
- Sparse Representations2▲ 41×1 topic
Which research topics does Sony Corporation (United States) publish most on?
By volume in 2022–2025: Advanced Neural Network Applications, Privacy-Preserving Technologies in Data, Domain Adaptation and Few-Shot Learning and Image and Signal Denoising Methods.
Area is fractional works; colour is the subfield each topic belongs to.
- 1 Advanced Neural Network Applications Computer Vision and Pattern Recognition 3 works
- 2 Privacy-Preserving Technologies in Data Artificial Intelligence 2 works
- 3 Domain Adaptation and Few-Shot Learning Artificial Intelligence 2 works
- 4 Image and Signal Denoising Methods Computer Vision and Pattern Recognition 2 works
- 5 Adversarial Robustness in Machine Learning Artificial Intelligence 2 works
- 6 Topic Modeling Artificial Intelligence 2 works
- 7 Generative Adversarial Networks and Image Synthesis Computer Vision and Pattern Recognition 2 works
- 8 Advanced Vision and Imaging Computer Vision and Pattern Recognition 2 works
- 9 Reinforcement Learning in Robotics Artificial Intelligence 2 works
- 10 Multimodal Machine Learning Applications Computer Vision and Pattern Recognition 2 works
How open and international is its research?
Against the world’s own shares — the tick on each track. Both are shares of its output, so they sit on one scale and can be read against each other as well as against the world.
World: 28% of research is openly available.
World: 19% is written across borders.
How has Sony Corporation (United States)'s research output changed?
Output in 2018–2022 was 32% higher than in 2013–2017.
The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.
Other research institutions in New York
- Columbia University
- New York University
- Icahn School of Medicine at Mount Sinai
- Memorial Sloan Kettering Cancer Center
- City University of New York
- Human Growth Foundation
- Columbia University Irving Medical Center
- Rockefeller University
Research measures only: rankings here say nothing about teaching, admissions or student experience. Comparable institutions and collaboration partners are in the interactive view on the map.