Lenovo (China)
In research, Lenovo (China) stands highest in Computer Science (#1,790 of 4,667 worldwide) and Physical Sciences (#6,823 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 17.1× its share of world research.
- World rank, 2022–2025
- #10,927 of 28,054 · #21,416 all time
- Rank in China
- #1,957 of 3,058
- Research works
- 466 ▲ 137% vs 2013–17
- Citations
- 6.6k 14.3 per fractional work
- Top-10% rate
- 24.4% record average 16.5%
- Open access
- 24% world 28%
What is Lenovo (China) 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 | #1,790 of 4,667 | 25.8% | 123 | #3055 | |
| Physical SciencesDomain | #6,823 of 12,888 | 24.8% | 186 | #13111 |
Each strip is that field’s whole ranked pool, with the notch where Lenovo (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 world mark, because the world rate differs by field (from about 6% to 21% in this record).
What does Lenovo (China) specialise in?
Where its research is concentrated relative to its size: Computer Vision and Pattern Recognition takes 17.1× the share of its output that it takes of world research.
- Computer Vision and Pattern RecognitionSubfield · 44.8 works17×
- Artificial IntelligenceSubfield · 44.1 works8.8×
- Computer ScienceField · 122.9 works7.6×
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, 7.6×. Every wedge is a field page.
- Computer Science 7.6×
- Engineering 1.8×
- Decision Sciences 1.1×
- Physics and Astronomy 0.5×
- Psychology 0.5×
- Mathematics 0.4×
- Neuroscience 0.4×
- Materials Science 0.3×
- Pharmacology, Toxicology and Pharmaceutics 0.3×
- Economics, Econometrics and Finance 0.3×
- Business, Management and Accounting 0.2×
- Earth and Planetary Sciences 0.2×
- Social Sciences 0.1×
- Medicine 0.1×
- Biochemistry, Genetics and Molecular Biology 0.1×
- Chemistry 0.1×
- Energy 0.1×
- Environmental Science 0.1×
- Agricultural and Biological Sciences 0.1×
- Health Professions 0.1×
- Arts and Humanities 0.1×
- Immunology and Microbiology 0.0×
Who are the top researchers at Lenovo (China)?
Ranked on the composite score, Jun Luo, Zhiqiang He and Cheng Zhong lead among researchers whose main affiliation is Lenovo (China).
- 1 Jun Luo China · #412,265 worldwide 120 citations · 33 works
- 2 Zhiqiang He China · #490,661 worldwide 156 citations · 18 works
- 3 Cheng Zhong China · #671,647 worldwide 87 citations · 16 works
- 4 Zhongchao Shi China · #900,024 worldwide 63 citations · 33 works
- 5 Qianying Wang China · #1,202,983 worldwide 58 citations · 44 works
- 6 Jun Xie China · #1,482,211 worldwide 15 citations · 23 works
Which keywords describe research at Lenovo (China)?
By fractional works in 2022–2025, weighted toward what it does more of than the world: Deep Learning, Neural Networks, Convolutional Neural Networks, Unsupervised Learning, Representation Learning, Information Retrieval, Text Classification and Semi-Supervised Learning.
- Object Tracking
- Visual Attention
- Feature Selection
- Sparse Representation
- Statistical Machine Translation
- Object Detection
- Real-time Tracking
- Computer Vision
- 5G Networks
- Few-Shot Learning
- Pose Estimation
- Visual Question Answering
- Image Captioning
- Word Representation
- Topic Modeling
- Semi-Supervised Learning
- Text Classification
- Representation Learning
- Machine Learning
- Neural Networks
- Deep Learning
- Convolutional Neural Networks
- Unsupervised Learning
- Information Retrieval
- Energy Efficiency
- Convolutional Networks
- Machine Translation
- Transfer Learning
- Internet of Things
- Meta-Learning
- Domain Adaptation
- Heterogeneous Networks
- Image Classification
- Generative Adversarial Networks
- Image Recognition
- Neural Machine Translation
- Action Recognition
- Spatiotemporal Features
- Graph Convolutional Networks
- Time Series
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 Learning67▲ 9.5×64 topics
- Neural Networks39▲ 12×30 topics
- Convolutional Neural Networks17▲ 11×13 topics
- Machine Learning15▲ 2.1×39 topics
- Unsupervised Learning11▲ 38×3 topics
- Representation Learning11▲ 39×3 topics
- Information Retrieval11▲ 24×4 topics
- Text Classification10▲ 31×2 topics
- Energy Efficiency9▲ 4.8×16 topics
- Semi-Supervised Learning8▲ 37×3 topics
- Convolutional Networks8▲ 27×3 topics
- Topic Modeling8▲ 26×2 topics
- Machine Translation8▲ 23×1 topic
- Word Representation8▲ 31×1 topic
- Transfer Learning6▲ 16×3 topics
- Image Captioning6▲ 59×1 topic
- Internet of Things6▲ 3.4×10 topics
- Visual Question Answering6▲ 36×1 topic
- Meta-Learning6▲ 34×2 topics
- Pose Estimation6▲ 24×2 topics
- Domain Adaptation5▲ 49×1 topic
- Few-Shot Learning5▲ 49×1 topic
- Heterogeneous Networks5▲ 26×2 topics
- 5G Networks5▲ 11×5 topics
- Image Classification5▲ 13×2 topics
- Computer Vision5▲ 8.2×3 topics
- Generative Adversarial Networks4▲ 26×2 topics
- Real-time Tracking4▲ 20×2 topics
- Image Recognition4▲ 15×1 topic
- Object Detection4▲ 16×1 topic
- Neural Machine Translation4▲ 21×1 topic
- Statistical Machine Translation4▲ 21×1 topic
- Action Recognition4▲ 39×1 topic
- Sparse Representation4▲ 9.9×6 topics
- Spatiotemporal Features4▲ 39×1 topic
- Feature Selection4▲ 8.3×4 topics
- Graph Convolutional Networks4▲ 16×2 topics
- Visual Attention4▲ 33×2 topics
- Time Series4▲ 10×3 topics
- Object Tracking4▲ 25×1 topic
Which research topics does Lenovo (China) publish most on?
By volume in 2022–2025: Topic Modeling, Multimodal Machine Learning Applications, Domain Adaptation and Few-Shot Learning and Advanced Neural Network Applications.
Area is fractional works; colour is the subfield each topic belongs to.
- 1 Topic Modeling Artificial Intelligence 8 works
- 2 Multimodal Machine Learning Applications Computer Vision and Pattern Recognition 6 works
- 3 Domain Adaptation and Few-Shot Learning Artificial Intelligence 5 works
- 4 Advanced Neural Network Applications Computer Vision and Pattern Recognition 4 works
- 5 Natural Language Processing Techniques Artificial Intelligence 4 works
- 6 Human Pose and Action Recognition Computer Vision and Pattern Recognition 4 works
- 7 Video Surveillance and Tracking Methods Computer Vision and Pattern Recognition 4 works
- 8 Generative Adversarial Networks and Image Synthesis Computer Vision and Pattern Recognition 3 works
- 9 Anomaly Detection Techniques and Applications Artificial Intelligence 3 works
- 10 Advanced Vision and Imaging Computer Vision and Pattern Recognition 3 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 Lenovo (China)'s research output changed?
Output in 2018–2022 was 137% 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 Beijing
- Chinese Academy of Sciences
- Tsinghua University
- Peking University
- University of Chinese Academy of Sciences
- Beihang University
- Beijing Institute of Technology
- Chinese Academy of Medical Sciences & Peking Union Medical College
- North China Electric Power 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.