Nvidia (United States)
In research, Nvidia (United States) stands highest in Computer Science (#47 of 4,667 worldwide), Physical Sciences (#693 of 12,888 worldwide) and Engineering (#1,130 of 6,636 worldwide), 2022–2025. Relative to its size it is most specialised in Hardware and Architecture, Computer Vision and Pattern Recognition and Computer Networks and Communications — Hardware and Architecture is 60.8× its share of world research.
- World rank, 2022–2025
- #1,103 of 28,054 · #2,067 all time
- Rank in United States
- #190 of 4,192
- Research works
- 1.6k ▲ 140% vs 2013–17
- Citations
- 53k 33.2 per fractional work
- Top-10% rate
- 30.6% record average 16.5%
- Open access
- 34% world 28%
What is Nvidia (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 |
|---|---|---|---|---|---|
| Computer ScienceField | #47 of 4,667 | 32.6% | 366 | #132 | |
| Physical SciencesDomain | #693 of 12,888 | 30.3% | 654 | #1419 | |
| EngineeringField | #1,130 of 6,636 | 24.8% | 219 | #2332 | |
| Artificial IntelligenceSubfield | #338 of 1,884 | 33.6% | 120 | #761 | |
| Computer Vision and Pattern RecognitionSubfield | #209 of 941 | 45.2% | 73 | #285 | |
| Electrical and Electronic EngineeringSubfield | #1,068 of 2,318 | 20.8% | 94 | #1885 |
Each strip is that field’s whole ranked pool, with the notch where Nvidia (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).
Which of those standings moved
The same fields on both windows: where it stood over the whole record, and where it stands in 2022–2025. The distance is the story, and it is the one thing the two rank columns above cannot show.
- Computer Science#132 #47
- Physical Sciences#1,419 #693
- Engineering#2,332 #1,130
- Artificial Intelligence#761 #338
- Computer Vision and Pattern Recognition#285 #209
- Electrical and Electronic Engineering#1,885 #1,068
A dot further right is a better standing. Fields it was not ranked in over the whole record are left out.
What does Nvidia (United States) specialise in?
Where its research is concentrated relative to its size: Hardware and Architecture takes 60.8× the share of its output that it takes of world research.
- Hardware and ArchitectureSubfield · 50.6 works61×
- Computer Vision and Pattern RecognitionSubfield · 73.1 works7.8×
- Computer Networks and CommunicationsSubfield · 49.2 works7.5×
- Artificial IntelligenceSubfield · 120.0 works6.7×
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×
- Engineering 2.0×
- Decision Sciences 1.6×
- Physics and Astronomy 1.3×
- Earth and Planetary Sciences 1.1×
- Mathematics 0.8×
- Neuroscience 0.7×
- Biochemistry, Genetics and Molecular Biology 0.5×
- Materials Science 0.4×
- Environmental Science 0.3×
- Business, Management and Accounting 0.2×
- Psychology 0.2×
- Chemistry 0.2×
- Medicine 0.2×
- Chemical Engineering 0.1×
- Health Professions 0.1×
- Economics, Econometrics and Finance 0.1×
- Social Sciences 0.1×
- Pharmacology, Toxicology and Pharmaceutics 0.1×
- Nursing 0.1×
- Immunology and Microbiology 0.0×
- Agricultural and Biological Sciences 0.0×
- Dentistry 0.0×
- Arts and Humanities 0.0×
Who are the top researchers at Nvidia (United States)?
Ranked on the composite score, Holger R. Roth, Brucek Khailany and Michael Wolfe lead among researchers whose main affiliation is Nvidia (United States).
- 1 Holger R. Roth United States · #35,398 worldwide 471 citations · 63 works
- 2 Brucek Khailany United States · #65,006 worldwide 608 citations · 33 works
- 3 Michael Wolfe United States · #72,333 worldwide 284 citations · 38 works
- 4 David B. Kirk United States · #88,107 worldwide 212 citations · 39 works
- 5 John W. Poulton United States · #103,383 worldwide 212 citations · 24 works
- 6 Daguang Xu United States · #122,503 worldwide 345 citations · 66 works
- 7 Wenqi Li United States · #134,527 worldwide 182 citations · 31 works
- 8 Dong Yang United States · #137,547 worldwide 273 citations · 59 works
- 9 Brian Zimmer United States · #163,614 worldwide 269 citations · 23 works
- 10 Siva Kumar Sastry Hari United States · #184,962 worldwide 227 citations · 22 works
Which keywords describe research at Nvidia (United States)?
By fractional works in 2022–2025, weighted toward what it does more of than the world: Deep Learning, Machine Learning, Neural Networks, Convolutional Neural Networks, Parallel Computing, High-Performance Computing, GPU Computing and Performance Optimization.
- Embedded Cores
- Distributed Storage
- Acoustic Modeling
- Image Recognition
- Power Optimization
- Fault Tolerance
- Heat Exchangers
- CMOS Technology
- Computer Graphics
- Integrated Circuits
- FPGA
- Simulation
- Image Classification
- Heat Transfer
- Distributed Systems
- Big Data
- GPU Computing
- High-Performance Computing
- Convolutional Neural Networks
- Machine Learning
- Deep Learning
- Neural Networks
- Parallel Computing
- Energy Efficiency
- Performance Optimization
- Unsupervised Learning
- Deep Neural Networks
- Resource Management
- Visualization
- Thermal Management
- Convolutional Networks
- Texture Analysis
- Rendering
- Computer Vision
- Hidden Markov Models
- Network Coding
- Representation Learning
- Object Detection
- Speaker Verification
- Flash Memory
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 Learning138▲ 5.5×67 topics
- Machine Learning76▲ 3.1×67 topics
- Neural Networks57▲ 5.0×29 topics
- Convolutional Neural Networks43▲ 7.9×14 topics
- Parallel Computing40▲ 46×4 topics
- High-Performance Computing35▲ 57×3 topics
- Energy Efficiency26▲ 3.8×15 topics
- GPU Computing26▲ 93×1 topic
- Performance Optimization26▲ 55×1 topic
- Big Data22▲ 3.3×16 topics
- Unsupervised Learning22▲ 21×3 topics
- Distributed Systems22▲ 17×6 topics
- Deep Neural Networks19▲ 24×3 topics
- Heat Transfer18▲ 4.9×10 topics
- Resource Management17▲ 14×2 topics
- Image Classification17▲ 13×3 topics
- Visualization17▲ 41×2 topics
- Simulation16▲ 8.3×8 topics
- Thermal Management16▲ 6.4×7 topics
- FPGA16▲ 56×3 topics
- Convolutional Networks15▲ 15×3 topics
- Integrated Circuits15▲ 13×3 topics
- Texture Analysis15▲ 8.6×3 topics
- Computer Graphics14▲ 74×1 topic
- Rendering14▲ 74×1 topic
- CMOS Technology14▲ 24×5 topics
- Computer Vision14▲ 7.1×3 topics
- Heat Exchangers14▲ 25×2 topics
- Hidden Markov Models14▲ 33×3 topics
- Fault Tolerance14▲ 12×7 topics
- Network Coding14▲ 40×2 topics
- Power Optimization14▲ 72×2 topics
- Representation Learning14▲ 14×3 topics
- Image Recognition14▲ 14×1 topic
- Object Detection14▲ 15×1 topic
- Acoustic Modeling14▲ 50×1 topic
- Speaker Verification14▲ 50×1 topic
- Distributed Storage13▲ 64×1 topic
- Flash Memory13▲ 64×1 topic
- Embedded Cores12▲ 108×1 topic
Which research topics does Nvidia (United States) publish most on?
By volume in 2022–2025: Parallel Computing and Optimization Techniques, Computer Graphics and Visualization Techniques, Advanced Neural Network Applications and Speech Recognition and Synthesis.
Area is fractional works; colour is the subfield each topic belongs to.
- 1 Parallel Computing and Optimization Techniques Hardware and Architecture 26 works
- 2 Computer Graphics and Visualization Techniques Computer Graphics and Computer-Aided Design 14 works
- 3 Advanced Neural Network Applications Computer Vision and Pattern Recognition 14 works
- 4 Speech Recognition and Synthesis Artificial Intelligence 14 works
- 5 Advanced Data Storage Technologies Computer Networks and Communications 13 works
- 6 VLSI and Analog Circuit Testing Hardware and Architecture 12 works
- 7 Natural Language Processing Techniques Artificial Intelligence 11 works
- 8 Advanced Vision and Imaging Computer Vision and Pattern Recognition 10 works
- 9 Heat Transfer and Optimization Mechanical Engineering 9 works
- 10 3D Shape Modeling and Analysis Computational Mechanics 9 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 Nvidia (United States)'s research output changed?
Output in 2018–2022 was 140% 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 Santa Clara
- Intel (United States)
- Santa Clara University
- Agilent Technologies (United States)
- Applied Materials (United States)
- GlobalFoundries (United States)
- Coherent (United States)
- Renesas Electronics (United States)
- Evans Analytical Group (United States)
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.