NetEase (China)
In research, NetEase (China) stands highest in Computer Science (#2,148 of 4,667 worldwide) and Physical Sciences (#9,716 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 18.5× its share of world research.
- World rank, 2022–2025
- #16,388 of 28,054 · #26,074 all time
- Rank in China
- #2,566 of 3,058
- Research works
- 303 ▲ 415% vs 2013–17
- Citations
- 4.5k 14.8 per fractional work
- Top-10% rate
- 24.3% record average 16.5%
- Open access
- 34% world 28%
What is NetEase (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 | #2,148 of 4,667 | 22.7% | 116 | #2635 | |
| Physical SciencesDomain | #9,716 of 12,888 | 22.6% | 136 | #14834 |
Each strip is that field’s whole ranked pool, with the notch where NetEase (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 NetEase (China) specialise in?
Where its research is concentrated relative to its size: Computer Vision and Pattern Recognition takes 18.5× the share of its output that it takes of world research.
- Computer Vision and Pattern RecognitionSubfield · 37.0 works18×
- Artificial IntelligenceSubfield · 46.9 works12×
- Computer ScienceField · 115.9 works9.4×
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, 9.4×. Every wedge is a field page.
- Computer Science 9.4×
- Psychology 1.5×
- Neuroscience 1.0×
- Decision Sciences 1.0×
- Engineering 0.7×
- Economics, Econometrics and Finance 0.5×
- Physics and Astronomy 0.3×
- Business, Management and Accounting 0.3×
- Mathematics 0.3×
- Earth and Planetary Sciences 0.2×
- Social Sciences 0.2×
- Health Professions 0.1×
- Chemistry 0.1×
- Arts and Humanities 0.1×
- Biochemistry, Genetics and Molecular Biology 0.1×
- Dentistry 0.1×
- Nursing 0.1×
- Medicine 0.1×
- Environmental Science 0.1×
- Agricultural and Biological Sciences 0.0×
- Immunology and Microbiology 0.0×
- Materials Science 0.0×
Who are the top researchers at NetEase (China)?
Ranked on the composite score, Runze Wu, Changjie Fan and Yingfeng Chen lead among researchers whose main affiliation is NetEase (China).
- 1 Runze Wu China · #361,222 worldwide 140 citations · 23 works
- 2 Changjie Fan China · #638,363 worldwide 157 citations · 61 works
- 3 Yingfeng Chen China · #859,387 worldwide 55 citations · 18 works
- 4 Lincheng Li China · #1,418,404 worldwide 25 citations · 18 works
- 5 Zhipeng Hu China · #1,510,732 worldwide 20 citations · 15 works
Which keywords describe research at NetEase (China)?
By fractional works in 2022–2025, weighted toward what it does more of than the world: Deep Learning, Neural Networks, Convolutional Neural Networks, Pose Estimation, Deep Neural Networks, Feature Extraction, Corpus Linguistics and Convolutional Networks.
- Reinforcement Learning
- Semi-Supervised Learning
- Generative Adversarial Networks
- Facial Landmark Detection
- Virtual Reality
- Age Estimation
- Matrix Factorization
- Human-Computer Interaction
- Audio-Visual Speech Recognition
- Audio Signal Classification
- Word Representation
- Topic Modeling
- Text Classification
- Acoustic Modeling
- Statistical Machine Translation
- Information Retrieval
- Corpus Linguistics
- Pose Estimation
- Machine Learning
- Neural Networks
- Deep Learning
- Convolutional Neural Networks
- Deep Neural Networks
- Feature Extraction
- Convolutional Networks
- Neural Machine Translation
- Unsupervised Learning
- Speaker Verification
- Representation Learning
- Machine Translation
- Face Recognition
- Music Information Retrieval
- Speech Enhancement
- Collaborative Filtering
- Action Recognition
- Spatiotemporal Features
- 3D Face Reconstruction
- Anomaly Detection
- Image Captioning
- Visual Question Answering
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 Learning69▲ 13×45 topics
- Neural Networks38▲ 15×18 topics
- Convolutional Neural Networks21▲ 18×11 topics
- Machine Learning13▲ 2.6×27 topics
- Deep Neural Networks10▲ 56×3 topics
- Pose Estimation10▲ 54×2 topics
- Feature Extraction9▲ 13×5 topics
- Corpus Linguistics8▲ 25×2 topics
- Convolutional Networks8▲ 38×3 topics
- Information Retrieval8▲ 24×3 topics
- Neural Machine Translation8▲ 54×1 topic
- Statistical Machine Translation8▲ 54×1 topic
- Unsupervised Learning8▲ 36×3 topics
- Acoustic Modeling8▲ 132×1 topic
- Speaker Verification8▲ 132×1 topic
- Text Classification8▲ 31×2 topics
- Representation Learning8▲ 35×3 topics
- Topic Modeling8▲ 32×2 topics
- Machine Translation7▲ 28×1 topic
- Word Representation7▲ 38×1 topic
- Face Recognition6▲ 32×2 topics
- Audio Signal Classification6▲ 89×1 topic
- Music Information Retrieval6▲ 89×1 topic
- Audio-Visual Speech Recognition5▲ 63×1 topic
- Speech Enhancement5▲ 63×1 topic
- Human-Computer Interaction5▲ 19×5 topics
- Collaborative Filtering5▲ 89×1 topic
- Matrix Factorization5▲ 89×1 topic
- Action Recognition5▲ 63×1 topic
- Age Estimation5▲ 48×2 topics
- Spatiotemporal Features5▲ 63×1 topic
- Virtual Reality5▲ 6.1×3 topics
- 3D Face Reconstruction5▲ 73×1 topic
- Facial Landmark Detection5▲ 73×1 topic
- Anomaly Detection5▲ 10×3 topics
- Generative Adversarial Networks5▲ 36×2 topics
- Image Captioning5▲ 60×1 topic
- Semi-Supervised Learning5▲ 26×3 topics
- Visual Question Answering5▲ 37×1 topic
- Reinforcement Learning4▲ 25×4 topics
Which research topics does NetEase (China) publish most on?
By volume in 2022–2025: Natural Language Processing Techniques, Speech Recognition and Synthesis, Topic Modeling and Music and Audio Processing.
Area is fractional works; colour is the subfield each topic belongs to.
- 1 Natural Language Processing Techniques Artificial Intelligence 8 works
- 2 Speech Recognition and Synthesis Artificial Intelligence 8 works
- 3 Topic Modeling Artificial Intelligence 7 works
- 4 Music and Audio Processing Signal Processing 6 works
- 5 Speech and Audio Processing Signal Processing 5 works
- 6 Recommender Systems and Techniques Information Systems 5 works
- 7 Human Pose and Action Recognition Computer Vision and Pattern Recognition 5 works
- 8 Face recognition and analysis Computer Vision and Pattern Recognition 5 works
- 9 Multimodal Machine Learning Applications Computer Vision and Pattern Recognition 5 works
- 10 Generative Adversarial Networks and Image Synthesis Computer Vision and Pattern Recognition 4 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 NetEase (China)'s research output changed?
Output in 2018–2022 was 415% 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.