Shanghai Artificial Intelligence Laboratory
In research, Shanghai Artificial Intelligence Laboratory stands highest in Computer Science (#161 of 4,417 worldwide), Computer Vision and Pattern Recognition (#50 of 963 worldwide) and Physical Sciences (#594 of 10,670 worldwide), 2022-now. 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 23.6× its share of world research).
- World rank, 2022-now
- #1,158 of 22,385 · #2,115 all time
- Rank in ??
- #2 of 487
- Research works
- 698 ▲ 2758% vs 2018-21
- Citations
- 19k 27.4 per fractional work
- Top-10% rate
- 30.1% all institutions 10.0%
- vs its own fields
- 1.67× 1.00× is exactly expected
- Open access
- 32% world 40%
- International
- 41% world 18%
What is Shanghai Artificial Intelligence Laboratory known for in research?
The fields where it stands highest, 2022-now, ranked among every institution above the floor in each field.
| Field | World rank | Where that sits | Top-10% rate | Works | All time |
|---|---|---|---|---|---|
| Computer ScienceField | #161 of 4,417 | 30.9% | 363 | #418 | |
| Computer Vision and Pattern RecognitionSubfield | #50 of 963 | 33.0% | 188 | #123 | |
| Physical SciencesDomain | #594 of 10,670 | 32.1% | 521 | #1060 | |
| Artificial IntelligenceSubfield | #195 of 1,862 | 25.4% | 123 | #391 | |
| EngineeringField | #705 of 5,901 | 37.1% | 116 | #1403 |
Each strip is that field's whole ranked pool, with the notch where Shanghai Artificial Intelligence Laboratory 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 average mark, because the average differs by field (from about 6% in Dentistry to 21% in Economics).
Which of those standings moved
The same fields on both windows: where it stood over the whole record, and where it stands in 2022-now. The distance is the story, and it is the one thing the two rank columns above cannot show.
- Computer Science#418 #161
- Computer Vision and Pattern Recognition#123 #50
- Physical Sciences#1,060 #594
- Artificial Intelligence#391 #195
- Engineering#1,403 #705
A dot further right is a better standing. Fields it was not ranked in over the whole record are left out.
Which fields of science does Shanghai Artificial Intelligence Laboratory work in?
In 2022-now, 83% of research at Shanghai Artificial Intelligence Laboratory is in Physical Sciences, 6% in Life Sciences. Its largest fields are Computer Science (58%), Engineering (18%), Medicine (5%). It does 2.1× the world's share of Physical Sciences.
Each ring splits the one inside it: the four domains of science, their fields, their subfields. Size is fractional works in 2022-now. Every slice is a page; the interactive view zooms down to single topics and colours each by how much more of it this institution does than the world.
Its 4 domains and 25 fields, with their numbers
- Physical Sciences56483.4%
- Computer Science39458.2%
- Engineering12218.0%
- Earth and Planetary Sciences131.9%
- Physics and Astronomy121.7%
- Environmental Science101.5%
- Chemistry50.8%
- Materials Science50.7%
- Mathematics30.5%
- Energy00.0%
- Chemical Engineering00.0%
- Life Sciences395.7%
- Health Sciences385.6%
- Medicine355.1%
- Health Professions30.4%
- Dentistry00.0%
- Veterinary00.0%
- Social Sciences365.3%
What does Shanghai Artificial Intelligence Laboratory specialise in?
Where its research is concentrated relative to its size: Computer Vision and Pattern Recognition takes 23.6× the share of its output that it takes of world research.
- Computer Vision and Pattern RecognitionSubfield · 201.0 works24×
- Artificial IntelligenceSubfield · 136.0 works8.3×
- Computer ScienceField · 394.1 works7.5×
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, 7.5×. Every wedge is a field page.
All 25 fields, with their numbers
- Computer Science7.49×394 works
- Neuroscience1.29×14 works
- Engineering1.20×122 works
- Earth and Planetary Sciences1.19×13 works
- Decision Sciences0.82×5 works
- Physics and Astronomy0.78×12 works
- Biochemistry, Genetics and Molecular Biology0.62×22 works
- Chemistry0.48×5 works
- Mathematics0.41×3 works
- Psychology0.34×7 works
- Environmental Science0.31×10 works
- Economics, Econometrics and Finance0.28×4 works
- Medicine0.27×35 works
- Business, Management and Accounting0.21×4 works
- Materials Science0.20×5 works
- Pharmacology, Toxicology and Pharmaceutics0.18×0 works
- Social Sciences0.17×14 works
- Health Professions0.15×3 works
- Chemical Engineering0.10×0 works
- Dentistry0.10×0 works
- Agricultural and Biological Sciences0.05×2 works
- Immunology and Microbiology0.05×0 works
- Energy0.05×0 works
- Arts and Humanities0.05×1 works
- Veterinary0.04×0 works
- Computer Science 7.5×
- Neuroscience 1.3×
- Engineering 1.2×
- Earth and Planetary Sciences 1.2×
- Decision Sciences 0.8×
- Physics and Astronomy 0.8×
- Biochemistry, Genetics and Molecular Biology 0.6×
- Chemistry 0.5×
- Mathematics 0.4×
- Psychology 0.3×
- Environmental Science 0.3×
- Economics, Econometrics and Finance 0.3×
- Medicine 0.3×
- Business, Management and Accounting 0.2×
- Materials Science 0.2×
- Pharmacology, Toxicology and Pharmaceutics 0.2×
- Social Sciences 0.2×
- Health Professions 0.1×
- Chemical Engineering 0.1×
- Dentistry 0.1×
- Agricultural and Biological Sciences 0.1×
- Immunology and Microbiology 0.1×
- Energy 0.1×
- Arts and Humanities 0.1×
- Veterinary 0.0×
Who are the top researchers at Shanghai Artificial Intelligence Laboratory?
Ranked on the quality score, Jiangmiao Pang, Yuenan Hou and Junjun He lead among researchers whose main affiliation is Shanghai Artificial Intelligence Laboratory.
- 1 Jiangmiao Pang #22,189 worldwide 9.4k citations · 116 works
- 2 Yuenan Hou #55,385 worldwide 3k citations · 82 works
- 3 Junjun He #73,154 worldwide 3.7k citations · 211 works
- 4 Yuhang Zang #106,047 worldwide 2.4k citations · 92 works
- 5 Shixiang Tang #124,739 worldwide 1.4k citations · 95 works
- 6 Conghui He #133,686 worldwide 3.1k citations · 202 works
- 7 Botian Shi #142,098 worldwide 1.7k citations · 107 works
- 8 Lei Bai #148,335 worldwide 4.5k citations · 308 works
- 9 Lewei Lu #152,625 worldwide 6.2k citations · 67 works
- 10 Haodong Duan #158,672 worldwide 2.2k citations · 77 works
Which keywords describe research at Shanghai Artificial Intelligence Laboratory?
By fractional works in 2022-now, weighted toward what it does more of than the world: Deep Learning, Neural Networks, Convolutional Neural Networks, Unsupervised Learning, Machine Learning, Convolutional Networks, Representation Learning and Image Classification.
- Optical Flow
- Local Descriptors
- Medical Image Analysis
- Robotics
- Depth Estimation
- Word Representation
- Machine Translation
- Point Clouds
- Few-Shot Learning
- Text Classification
- Feature Extraction
- Pose Estimation
- Medical Imaging
- Transfer Learning
- Image Captioning
- Image Recognition
- Image Classification
- Convolutional Networks
- Machine Learning
- Neural Networks
- Deep Learning
- Convolutional Neural Networks
- Unsupervised Learning
- Representation Learning
- Computer Vision
- Object Detection
- Visual Question Answering
- Semi-Supervised Learning
- Meta-Learning
- Generative Adversarial Networks
- Information Retrieval
- Domain Adaptation
- 3D Reconstruction
- Topic Modeling
- Semantic Similarity
- Action Recognition
- Spatiotemporal Features
- Object Recognition
- Feature Matching
- Sparse Representation
Size is fractional works in 2022-now 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 Learning282▲ 12×69 topics
- Neural Networks124▲ 12×33 topics
- Convolutional Neural Networks74▲ 15×14 topics
- Machine Learning69▲ 3.1×66 topics
- Unsupervised Learning49▲ 47×3 topics
- Convolutional Networks43▲ 46×3 topics
- Representation Learning38▲ 35×3 topics
- Image Classification32▲ 25×2 topics
- Computer Vision31▲ 17×3 topics
- Image Recognition30▲ 30×1 topic
- Object Detection30▲ 32×1 topic
- Image Captioning30▲ 78×1 topic
- Visual Question Answering30▲ 48×1 topic
- Transfer Learning27▲ 21×3 topics
- Semi-Supervised Learning27▲ 33×3 topics
- Medical Imaging24▲ 6.6×8 topics
- Meta-Learning22▲ 38×2 topics
- Pose Estimation22▲ 29×2 topics
- Generative Adversarial Networks22▲ 36×2 topics
- Feature Extraction22▲ 7.0×9 topics
- Information Retrieval21▲ 14×4 topics
- Text Classification21▲ 19×3 topics
- Domain Adaptation20▲ 54×1 topic
- Few-Shot Learning20▲ 54×1 topic
- 3D Reconstruction19▲ 31×2 topics
- Point Clouds19▲ 31×2 topics
- Topic Modeling19▲ 18×2 topics
- Machine Translation19▲ 17×2 topics
- Semantic Similarity19▲ 22×1 topic
- Word Representation19▲ 22×1 topic
- Action Recognition18▲ 55×1 topic
- Depth Estimation18▲ 34×2 topics
- Spatiotemporal Features18▲ 55×1 topic
- Robotics18▲ 11×7 topics
- Object Recognition17▲ 34×2 topics
- Medical Image Analysis17▲ 14×4 topics
- Feature Matching17▲ 43×1 topic
- Local Descriptors17▲ 43×1 topic
- Sparse Representation16▲ 12×6 topics
- Optical Flow16▲ 48×1 topic
Which research topics does Shanghai Artificial Intelligence Laboratory publish most on?
By volume in 2022-now: Advanced Neural Network Applications, Multimodal Machine Learning Applications, Domain Adaptation and Few-Shot Learning and Topic Modeling.
Area is fractional works; colour is the subfield each topic belongs to.
- 1 Advanced Neural Network Applications Computer Vision and Pattern Recognition 30 works
- 2 Multimodal Machine Learning Applications Computer Vision and Pattern Recognition 30 works
- 3 Domain Adaptation and Few-Shot Learning Artificial Intelligence 20 works
- 4 Topic Modeling Artificial Intelligence 19 works
- 5 Human Pose and Action Recognition Computer Vision and Pattern Recognition 18 works
- 6 Advanced Image and Video Retrieval Techniques Computer Vision and Pattern Recognition 17 works
- 7 Advanced Vision and Imaging Computer Vision and Pattern Recognition 16 works
- 8 3D Shape Modeling and Analysis Computational Mechanics 14 works
- 9 Generative Adversarial Networks and Image Synthesis Computer Vision and Pattern Recognition 13 works
- 10 Natural Language Processing Techniques Artificial Intelligence 13 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: 40% of research is openly available.
World: 18% is written across borders.
How has Shanghai Artificial Intelligence Laboratory's research output changed?
Output in 2022-2025 was 2758% higher than in 2018-2021.
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 Shanghai
- Shanghai Institute of Pollution Control and Ecological Security
- Naval Research Academy
- Shanghai Synchrotron Radiation Facility
- Deepblue Technology (China)
- Shanghai Institute for Mathematics and Interdisciplinary Sciences
- Shanghai Ecological Forecasting and Remote Sensing Center
- Shanghai Marine Meteorological Center
- State Key Laboratory of Special Cable Technology
Research measures only: rankings here say nothing about teaching, admissions or student experience. Comparable institutions and collaboration partners have tabs of their own, above.
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