Research in Cupertino
Science Explorer records 10 research institutions in Cupertino, United States. The highest-ranked on research quality in 2022–2025 are Apple (United States) and Seagate (United States).
- Research institutions
- 10 2 of them ranked worldwide
- Research works
- 3.9k ▲ 15% vs 2013–17
- Top-10% rate, 2022–2025
- 19.2% record average 16.5%
A city carries no overall standing here. The composite score is built for institutions and countries, the units its floors and field normalisation were designed around. An empty rank on this page is a statement about the measure, not about the place.
Which research institutions are in Cupertino?
| # | Institution | Works | Against the largest here | World rank |
|---|---|---|---|---|
| 1 | Seagate (United States)Company | 2,044 | #23,075 | |
| 2 | Apple (United States)Company | 1,230 | #4,665 | |
| 3 | Affymax (United States)Company | 324 | #6,913 all time | |
| 4 | De Anza CollegeUniversity | 202 | #37,344 all time | |
| 5 | Cellular Biomedicine Group (United States)Company | 53 | not ranked | |
| 6 | Integrated Optical Circuit Consultants (United States)Company | 48 | not ranked | |
| 7 | Durect (United States)Company | 17 | not ranked | |
| 8 | CRC Health GroupHospital / health system | 15 | not ranked | |
| 9 | Silicon Mitus (United States)Company | 10 | not ranked | |
| 10 | Northern California DX FoundationNonprofit | 0 | not ranked |
By fractional works over the whole record; world rank on research quality in 2022–2025. Bars are scaled to the largest institution in this city, not to anything off the page.
How concentrated the city is
The same institutions as shares of everything the list accounts for. A city that is one university and a city that is twelve read alike as a table and not at all alike here.
Shares of the rows listed above, not of the whole node.
What is Cupertino strongest at in research?
Relative to its size, research in Cupertino is most concentrated in Artificial Intelligence and Computer Science (4.7× the world share in Artificial Intelligence).
- Artificial IntelligenceSubfield · 43.0 works4.7×
- Computer ScienceField · 107.6 works3.6×
Location quotient against the world baseline. Inside a single field a city is a meaningful unit, which is why this is where a city is measured at all.
Which keywords describe research in Cupertino?
By fractional works in 2022–2025, weighted toward what it does more of than the world: Deep Learning, Neural Networks, Machine Learning, Information Retrieval, Text Classification, Deep Neural Networks, Energy Efficiency and Distributed Systems.
- Skyrmions
- Low-Power
- Hidden Markov Models
- Circadian Rhythms
- Semiconductor Manufacturing
- Delta-Sigma Modulator
- Channel Modeling
- Statistical Machine Translation
- Human-Computer Interaction
- Unsupervised Learning
- CMOS Technology
- Anomaly Detection
- Integrated Circuits
- Machine Translation
- Distributed Systems
- Text Classification
- Security
- Information Retrieval
- Energy Efficiency
- Neural Networks
- Deep Learning
- Machine Learning
- Big Data
- Convolutional Neural Networks
- Data Mining
- Deep Neural Networks
- Classification
- Word Representation
- Machine Vision
- CMOS
- Texture Analysis
- Corpus Linguistics
- Neural Machine Translation
- Representation Learning
- Meta-Learning
- Fabric Defect Detection
- Approximation Algorithms
- Heterogeneous Networks
- Fault Localization
- Magnetic Tunnel Junctions
Size is fractional works in 2022–2025 in the topics tagged with each word; colour is the word's share of this city'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 Learning43▲ 3.3×64 topics
- Neural Networks25▲ 4.3×25 topics
- Machine Learning25▲ 2.0×52 topics
- Energy Efficiency10▲ 2.7×16 topics
- Big Data9▲ 2.6×13 topics
- Information Retrieval8▲ 9.5×4 topics
- Convolutional Neural Networks7▲ 2.6×11 topics
- Security7▲ 2.7×12 topics
- Data Mining6▲ 2.1×6 topics
- Text Classification6▲ 9.6×2 topics
- Deep Neural Networks6▲ 14×3 topics
- Distributed Systems5▲ 8.5×6 topics
- Classification5▲ 3.0×11 topics
- Machine Translation5▲ 8.2×1 topic
- Word Representation5▲ 11×1 topic
- Integrated Circuits5▲ 8.4×3 topics
- Machine Vision5▲ 5.8×4 topics
- Anomaly Detection5▲ 4.1×3 topics
- CMOS4▲ 22×2 topics
- CMOS Technology4▲ 14×4 topics
- Texture Analysis4▲ 4.8×3 topics
- Unsupervised Learning4▲ 7.9×3 topics
- Corpus Linguistics4▲ 4.9×2 topics
- Human-Computer Interaction4▲ 5.9×6 topics
- Neural Machine Translation4▲ 11×1 topic
- Statistical Machine Translation4▲ 11×1 topic
- Representation Learning4▲ 7.0×3 topics
- Channel Modeling4▲ 7.5×5 topics
- Meta-Learning4▲ 11×2 topics
- Delta-Sigma Modulator3▲ 27×2 topics
- Fabric Defect Detection3▲ 11×1 topic
- Semiconductor Manufacturing3▲ 11×1 topic
- Approximation Algorithms3▲ 12×4 topics
- Circadian Rhythms3▲ 8.1×2 topics
- Heterogeneous Networks3▲ 8.9×2 topics
- Hidden Markov Models3▲ 14×2 topics
- Fault Localization3▲ 12×2 topics
- Low-Power3▲ 19×2 topics
- Magnetic Tunnel Junctions3▲ 29×1 topic
- Skyrmions3▲ 29×1 topic
What research is done in Cupertino?
Area is fractional works; colour is the subfield each topic belongs to.
- 1 Topic Modeling Artificial Intelligence 5 works
- 2 Natural Language Processing Techniques Artificial Intelligence 4 works
- 3 Industrial Vision Systems and Defect Detection Industrial and Manufacturing Engineering 3 works
- 4 Magnetic properties of thin films Atomic and Molecular Physics, and Optics 3 works
- 5 Multimodal Machine Learning Applications Computer Vision and Pattern Recognition 3 works
- 6 Speech Recognition and Synthesis Artificial Intelligence 2 works
- 7 Analog and Mixed-Signal Circuit Design Biomedical Engineering 2 works
- 8 Adhesion, Friction, and Surface Interactions Mechanics of Materials 2 works
- 9 Advanced Neural Network Applications Computer Vision and Pattern Recognition 2 works
- 10 Electrostatic Discharge in Electronics Electrical and Electronic Engineering 2 works
Research output over time
The same series as a ribbon — one cell per year, darker for more.