Alibaba Group (China)
In research, Alibaba Group (China) stands highest in Computer Science (#76 of 4,417 worldwide), Artificial Intelligence (#76 of 1,862 worldwide) and Physical Sciences (#437 of 10,670 worldwide), 2022-now. Relative to its size it is most specialised in Computer Vision and Pattern Recognition, Signal Processing and Hardware and Architecture (Computer Vision and Pattern Recognition is 16.4× its share of world research).
- World rank, 2022-now
- #782 of 22,385 · #838 all time
- Rank in China
- #190 of 2,481
- Research works
- 3.7k ▲ 41% vs 2018-21
- Citations
- 94k 25.2 per fractional work
- Top-10% rate
- 19.7% all institutions 10.0%
- vs its own fields
- 1.66× 1.00× is exactly expected
- Open access
- 40% world 40%
- International
- 42% world 18%
What is Alibaba Group (China) 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 | #76 of 4,417 | 21.4% | 1,294 | #98 | |
| Artificial IntelligenceSubfield | #76 of 1,862 | 20.3% | 486 | #67 | |
| Physical SciencesDomain | #437 of 10,670 | 21.2% | 1,592 | #405 | |
| Computer Vision and Pattern RecognitionSubfield | #54 of 963 | 21.9% | 387 | #61 | |
| Information SystemsSubfield | #141 of 1,321 | 19.9% | 134 | #123 | |
| EngineeringField | #656 of 5,901 | 20.2% | 230 | #670 | |
| Computer Networks and CommunicationsSubfield | #88 of 728 | 22.2% | 140 | #152 | |
| Electrical and Electronic EngineeringSubfield | #485 of 2,176 | 18.5% | 70 | #602 | |
| Signal ProcessingSubfield | #45 of 169 | 27.7% | 71 | #82 | |
| Social SciencesDomain | #2,704 of 9,585 | 18.8% | 155 | #1769 |
Each strip is that field's whole ranked pool, with the notch where Alibaba Group (China) 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#98 #76
- Artificial Intelligence#67 #76
- Physical Sciences#405 #437
- Computer Vision and Pattern Recognition#61 #54
- Information Systems#123 #141
- Engineering#670 #656
- Computer Networks and Communications#152 #88
- Electrical and Electronic Engineering#602 #485
- Signal Processing#82 #45
- Social Sciences#1,769 #2,704
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 Alibaba Group (China) work in?
In 2022-now, 86% of research at Alibaba Group (China) is in Physical Sciences, 8% in Social Sciences. Its largest fields are Computer Science (71%), Engineering (12%), Social Sciences (3%). It does 2.2× 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 26 fields, with their numbers
- Physical Sciences1,78586.4%
- Computer Science1,45970.6%
- Engineering24912.1%
- Environmental Science211.0%
- Physics and Astronomy170.8%
- Mathematics130.6%
- Earth and Planetary Sciences120.6%
- Materials Science90.4%
- Energy30.1%
- Chemistry20.1%
- Chemical Engineering00.0%
- Social Sciences1748.4%
- Social Sciences562.7%
- Decision Sciences422.0%
- Business, Management and Accounting381.8%
- Psychology180.9%
- Arts and Humanities100.5%
- Economics, Econometrics and Finance100.5%
- Health Sciences572.7%
- Medicine502.4%
- Health Professions50.2%
- Dentistry10.1%
- Nursing10.0%
- Veterinary00.0%
- Life Sciences492.4%
What does Alibaba Group (China) specialise in?
Where its research is concentrated relative to its size: Computer Vision and Pattern Recognition takes 16.4× the share of its output that it takes of world research.
- Computer Vision and Pattern RecognitionSubfield · 426.4 works16×
- Signal ProcessingSubfield · 78.8 works13×
- Hardware and ArchitectureSubfield · 27.1 works12×
- Artificial IntelligenceSubfield · 552.9 works11×
- Computer ScienceField · 1,458.7 works9.1×
- Computer Networks and CommunicationsSubfield · 155.8 works8.5×
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, 9.1×. Every wedge is a field page.
All 26 fields, with their numbers
- Computer Science9.08×1,459 works
- Decision Sciences2.11×42 works
- Engineering0.81×249 works
- Business, Management and Accounting0.57×38 works
- Mathematics0.54×13 works
- Neuroscience0.43×14 works
- Earth and Planetary Sciences0.39×12 works
- Physics and Astronomy0.36×17 works
- Psychology0.29×18 works
- Biochemistry, Genetics and Molecular Biology0.22×24 works
- Economics, Econometrics and Finance0.22×10 works
- Social Sciences0.22×56 works
- Environmental Science0.20×21 works
- Arts and Humanities0.17×10 works
- Energy0.14×3 works
- Medicine0.13×50 works
- Materials Science0.12×9 works
- Dentistry0.12×1 works
- Health Professions0.09×5 works
- Agricultural and Biological Sciences0.08×8 works
- Pharmacology, Toxicology and Pharmaceutics0.08×1 works
- Immunology and Microbiology0.07×1 works
- Chemistry0.07×2 works
- Veterinary0.06×0 works
- Nursing0.05×0 works
- Chemical Engineering0.04×0 works
- Computer Science 9.1×
- Decision Sciences 2.1×
- Engineering 0.8×
- Business, Management and Accounting 0.6×
- Mathematics 0.5×
- Neuroscience 0.4×
- Earth and Planetary Sciences 0.4×
- Physics and Astronomy 0.4×
- Psychology 0.3×
- Biochemistry, Genetics and Molecular Biology 0.2×
- Economics, Econometrics and Finance 0.2×
- Social Sciences 0.2×
- Environmental Science 0.2×
- Arts and Humanities 0.2×
- Energy 0.1×
- Medicine 0.1×
- Materials Science 0.1×
- Dentistry 0.1×
- Health Professions 0.1×
- Agricultural and Biological Sciences 0.1×
- Pharmacology, Toxicology and Pharmaceutics 0.1×
- Immunology and Microbiology 0.1×
- Chemistry 0.1×
- Veterinary 0.1×
- Nursing 0.1×
- Chemical Engineering 0.0×
Who are the top researchers at Alibaba Group (China)?
Ranked on the quality score, Jingren Zhou, Fei Long Sun and Chang Zhou lead among researchers whose main affiliation is Alibaba Group (China).
- 1
Jingren Zhou
China · #25,385 worldwide 8.7k citations · 363 works
- 2
Fei Long Sun
China · #71,459 worldwide 11k citations · 148 works
- 3
Chang Zhou
China · #86,620 worldwide 5.7k citations · 111 works
- 4
Wei Lin
China · #97,422 worldwide 3.4k citations · 137 works
- 5
Xuansong Xie
China · #105,716 worldwide 2.7k citations · 115 works
- 6
Feifei Li
China · #109,311 worldwide 3.9k citations · 186 works
- 7
Wenwu Ou
China · #116,642 worldwide 5.1k citations · 84 works
- 8
Jianqiang Huang
China · #141,230 worldwide 6.7k citations · 180 works
- 9
Peiran Ren
China · #156,409 worldwide 2.4k citations · 69 works
- 10
Zilong Dong
China · #160,744 worldwide 1.5k citations · 94 works
Which keywords describe research at Alibaba Group (China)?
By fractional works in 2022-now, weighted toward what it does more of than the world: Deep Learning, Neural Networks, Convolutional Neural Networks, Information Retrieval, Text Classification, Representation Learning, Machine Learning and Unsupervised Learning.
- Data Centers
- Few-Shot Learning
- Parallel Computing
- Virtualization
- Transfer Learning
- Matrix Factorization
- Anomaly Detection
- Cloud Computing
- Multimodal Fusion
- Visual Question Answering
- Statistical Machine Translation
- Convolutional Networks
- Corpus Linguistics
- Semi-Supervised Learning
- Word Representation
- Machine Translation
- Unsupervised Learning
- Text Classification
- Convolutional Neural Networks
- Neural Networks
- Deep Learning
- Machine Learning
- Information Retrieval
- Representation Learning
- Topic Modeling
- Semantic Similarity
- Distributed Systems
- Big Data
- Energy Efficiency
- Neural Machine Translation
- Semantic Reasoning
- Image Captioning
- Resource Management
- Meta-Learning
- Collaborative Filtering
- Graph Convolutional Networks
- Generative Adversarial Networks
- Deep Neural Networks
- Domain Adaptation
- Image Classification
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 Learning689▲ 9.7×79 topics
- Neural Networks440▲ 14×33 topics
- Machine Learning190▲ 2.8×76 topics
- Convolutional Neural Networks141▲ 9.4×14 topics
- Information Retrieval134▲ 30×4 topics
- Text Classification120▲ 36×3 topics
- Representation Learning120▲ 37×3 topics
- Unsupervised Learning108▲ 34×3 topics
- Topic Modeling106▲ 34×3 topics
- Machine Translation105▲ 30×2 topics
- Semantic Similarity105▲ 41×1 topic
- Word Representation105▲ 41×1 topic
- Distributed Systems91▲ 26×6 topics
- Semi-Supervised Learning90▲ 35×3 topics
- Big Data72▲ 3.6×20 topics
- Corpus Linguistics66▲ 15×2 topics
- Energy Efficiency66▲ 3.5×19 topics
- Convolutional Networks66▲ 23×3 topics
- Neural Machine Translation66▲ 35×1 topic
- Statistical Machine Translation66▲ 35×1 topic
- Semantic Reasoning65▲ 34×2 topics
- Visual Question Answering65▲ 34×2 topics
- Image Captioning64▲ 56×1 topic
- Multimodal Fusion64▲ 56×1 topic
- Resource Management56▲ 16×3 topics
- Cloud Computing55▲ 9.4×9 topics
- Meta-Learning55▲ 31×2 topics
- Anomaly Detection55▲ 9.3×5 topics
- Collaborative Filtering54▲ 74×1 topic
- Matrix Factorization54▲ 74×1 topic
- Graph Convolutional Networks52▲ 22×2 topics
- Transfer Learning52▲ 13×3 topics
- Generative Adversarial Networks50▲ 27×2 topics
- Virtualization49▲ 29×3 topics
- Deep Neural Networks48▲ 19×3 topics
- Parallel Computing45▲ 19×5 topics
- Domain Adaptation45▲ 39×1 topic
- Few-Shot Learning45▲ 39×1 topic
- Image Classification44▲ 11×3 topics
- Data Centers44▲ 36×1 topic
Which research topics does Alibaba Group (China) publish most on?
By volume in 2022-now: Topic Modeling, Natural Language Processing Techniques, Multimodal Machine Learning Applications and Recommender Systems and Techniques.
Area is fractional works; colour is the subfield each topic belongs to.
- 1 Topic Modeling Artificial Intelligence 105 works
- 2 Natural Language Processing Techniques Artificial Intelligence 66 works
- 3 Multimodal Machine Learning Applications Computer Vision and Pattern Recognition 64 works
- 4 Recommender Systems and Techniques Information Systems 54 works
- 5 Domain Adaptation and Few-Shot Learning Artificial Intelligence 45 works
- 6 Cloud Computing and Resource Management Information Systems 44 works
- 7 Advanced Image and Video Retrieval Techniques Computer Vision and Pattern Recognition 40 works
- 8 Advanced Graph Neural Networks Artificial Intelligence 40 works
- 9 Advanced Neural Network Applications Computer Vision and Pattern Recognition 38 works
- 10 Generative Adversarial Networks and Image Synthesis Computer Vision and Pattern Recognition 35 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 Alibaba Group (China)'s research output changed?
Output in 2022-2025 was 41% 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.
Its share of all research
Growing output can still be a shrinking share: all of science grows. This is Alibaba Group (China) as a percentage of every work published that year, 0.0071% in 2024.
Fractional works of Alibaba Group (China) over all fractional works that year. How the balance of science has shifted.
How much of it reaches the world top 10%
Year by year, against all institutions in the same year.
Of each year's output, the share that reached the world's 10% most cited for its field and year. Peak 25.4% in 2022.
Other research institutions in Hangzhou
- Zhejiang University
- Zhejiang University of Technology
- Hangzhou Dianzi University
- Zhejiang Sci-Tech University
- Hangzhou Normal University
- China Jiliang University
- Zhejiang Chinese Medical University
- Zhejiang Gongshang University
Compare Alibaba Group (China) with
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Fujian Agriculture and Forestry University
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Colorado School of Mines
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Hospices Civils de Lyon
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Research measures only: rankings here say nothing about teaching, admissions or student experience. Comparable institutions and collaboration partners have tabs of their own, above.
Questions people ask
What does Alibaba publish research on?
In research, Alibaba Group (China) stands highest in Computer Science (#76 of 4,417 worldwide), Artificial Intelligence (#76 of 1,862 worldwide) and Physical Sciences (#437 of 10,670 worldwide), 2022-now. Relative to its size it is most specialised in Computer Vision and Pattern Recognition, Signal Processing and Hardware and Architecture (Computer Vision and Pattern Recognition is 16.4× its share of world research).
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