Tsinghua–Berkeley Shenzhen Institute
In research, Tsinghua–Berkeley Shenzhen Institute stands highest in Engineering (#141 of 6,636 worldwide), Electrical and Electronic Engineering (#68 of 2,318 worldwide) and Physical Sciences (#382 of 12,888 worldwide), 2022–2025. Relative to its size it is most specialised in Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Automotive Engineering — Electrical and Electronic Engineering is 5.9× its share of world research.
- World rank, 2022–2025
- #671 of 28,054 · #2,317 all time
- Rank in China
- #222 of 3,058
- Research works
- 2.8k ▲ 1315% vs 2013–17
- Citations
- 70k 24.8 per fractional work
- Top-10% rate
- 30.9% record average 16.5%
- Open access
- 35% world 28%
What is Tsinghua–Berkeley Shenzhen Institute 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 |
|---|---|---|---|---|---|
| EngineeringField | #141 of 6,636 | 32.7% | 703 | #742 | |
| Electrical and Electronic EngineeringSubfield | #68 of 2,318 | 36.9% | 343 | #353 | |
| Physical SciencesDomain | #382 of 12,888 | 31.3% | 1,386 | #1595 | |
| Computer ScienceField | #515 of 4,667 | 25.4% | 283 | #1699 | |
| Materials ScienceField | #487 of 2,468 | 35.7% | 120 | #1469 | |
| Computer Vision and Pattern RecognitionSubfield | #186 of 941 | 29.9% | 112 | #733 | |
| Environmental ScienceField | #995 of 3,551 | 35.5% | 111 | #2022 | |
| Life SciencesDomain | #2,211 of 7,800 | 29.2% | 109 | #5482 | |
| Materials ChemistrySubfield | #545 of 1,556 | 32.3% | 75 | #1358 | |
| Biomedical EngineeringSubfield | #579 of 1,568 | 23.7% | 86 | #1445 |
Each strip is that field’s whole ranked pool, with the notch where Tsinghua–Berkeley Shenzhen Institute 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.
- Engineering#742 #141
- Electrical and Electronic Engineering#353 #68
- Physical Sciences#1,595 #382
- Computer Science#1,699 #515
- Materials Science#1,469 #487
- Computer Vision and Pattern Recognition#733 #186
- Environmental Science#2,022 #995
- Life Sciences#5,482 #2,211
- Materials Chemistry#1,358 #545
- Biomedical Engineering#1,445 #579
A dot further right is a better standing. Fields it was not ranked in over the whole record are left out.
What does Tsinghua–Berkeley Shenzhen Institute specialise in?
Where its research is concentrated relative to its size: Electrical and Electronic Engineering takes 5.9× the share of its output that it takes of world research.
- Electrical and Electronic EngineeringSubfield · 343.2 works5.9×
- Computer Vision and Pattern RecognitionSubfield · 112.0 works5.4×
- Automotive EngineeringSubfield · 41.8 works4.8×
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: Energy, 3.5×. Every wedge is a field page.
- Energy 3.5×
- Engineering 2.9×
- Computer Science 2.2×
- Materials Science 2.1×
- Chemical Engineering 1.7×
- Environmental Science 1.4×
- Physics and Astronomy 1.3×
- Chemistry 1.2×
- Earth and Planetary Sciences 0.9×
- Decision Sciences 0.9×
- Neuroscience 0.8×
- Biochemistry, Genetics and Molecular Biology 0.7×
- Immunology and Microbiology 0.5×
- Pharmacology, Toxicology and Pharmaceutics 0.4×
- Medicine 0.2×
- Economics, Econometrics and Finance 0.2×
- Mathematics 0.2×
- Psychology 0.2×
- Agricultural and Biological Sciences 0.2×
- Business, Management and Accounting 0.2×
- Health Professions 0.1×
- Dentistry 0.1×
- Nursing 0.1×
- Social Sciences 0.1×
- Arts and Humanities 0.0×
- Veterinary 0.0×
Who are the top researchers at Tsinghua–Berkeley Shenzhen Institute?
Ranked on the composite score, Bilu Liu, Yinliang Xu and Min Ye lead among researchers whose main affiliation is Tsinghua–Berkeley Shenzhen Institute.
- 1 Bilu Liu China · #89,178 worldwide 518 citations · 42 works
- 2 Yinliang Xu China · #114,113 worldwide 550 citations · 63 works
- 3 Min Ye China · #556,566 worldwide 87 citations · 23 works
- 4 Shoujie Li China · #1,191,688 worldwide 35 citations · 22 works
- 5 Shaohua Ma China · #1,401,104 worldwide 27 citations · 33 works
- 6 Peiwu Qin China · #1,495,629 worldwide 23 citations · 24 works
- 7 Rui Yin China · #1,540,193 worldwide 48 citations · 16 works
- 8 Vijay Pandey China · #1,565,453 worldwide 11 citations · 19 works
- 9 Yiqing Liu China · #1,567,082 worldwide 10 citations · 20 works
- 10 Ye Guo China · #1,580,277 worldwide 13 citations · 20 works
Which keywords describe research at Tsinghua–Berkeley Shenzhen Institute?
By fractional works in 2022–2025, weighted toward what it does more of than the world: Deep Learning, Cathode Materials, Energy Storage, Lithium-ion Batteries, Rechargeable Batteries, Neural Networks, Battery Technology and Renewable Energy.
- Metal Recovery
- Unsupervised Learning
- Demand Response
- Game Theory
- Aqueous Zinc-Ion Batteries
- Thermal Runaway
- Biosensors
- Water Splitting
- Metal-Organic Frameworks
- Electric Vehicles
- Convolutional Neural Networks
- Biomedical Applications
- Nanostructured Cathodes
- Ionic Conductivity
- Nanostructured Anodes
- Nanomaterials
- Rechargeable Batteries
- Renewable Energy
- Neural Networks
- Cathode Materials
- Deep Learning
- Energy Storage
- Lithium-ion Batteries
- Machine Learning
- Battery Technology
- Battery Materials
- Smart Grid
- Lithium-Sulfur Batteries
- Solid-State Electrolytes
- Environmental Impact
- Graphene
- Renewable Energy Integration
- Thermal Management
- Battery Management Systems
- Electrocatalysis
- Energy Management
- Zinc Anode
- Smart Home
- Electricity Markets
- Convolutional Networks
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 Learning207▲ 3.7×80 topics
- Cathode Materials122▲ 19×3 topics
- Energy Storage109▲ 10×12 topics
- Neural Networks99▲ 3.9×32 topics
- Lithium-ion Batteries92▲ 13×3 topics
- Renewable Energy90▲ 3.8×30 topics
- Machine Learning81▲ 1.51×64 topics
- Rechargeable Batteries77▲ 17×2 topics
- Battery Technology69▲ 15×3 topics
- Nanomaterials59▲ 3.4×16 topics
- Battery Materials53▲ 19×1 topic
- Nanostructured Anodes53▲ 19×1 topic
- Smart Grid49▲ 7.9×9 topics
- Ionic Conductivity46▲ 20×2 topics
- Lithium-Sulfur Batteries46▲ 19×2 topics
- Nanostructured Cathodes45▲ 23×1 topic
- Solid-State Electrolytes45▲ 23×1 topic
- Biomedical Applications44▲ 2.3×33 topics
- Environmental Impact43▲ 1.54×37 topics
- Convolutional Neural Networks42▲ 3.5×14 topics
- Graphene41▲ 3.6×11 topics
- Electric Vehicles40▲ 8.2×4 topics
- Renewable Energy Integration34▲ 6.2×5 topics
- Metal-Organic Frameworks32▲ 4.7×6 topics
- Thermal Management32▲ 5.9×6 topics
- Water Splitting31▲ 5.1×4 topics
- Battery Management Systems27▲ 11×1 topic
- Biosensors27▲ 3.2×12 topics
- Electrocatalysis27▲ 5.8×5 topics
- Thermal Runaway27▲ 11×1 topic
- Energy Management24▲ 8.7×2 topics
- Aqueous Zinc-Ion Batteries24▲ 14×1 topic
- Zinc Anode24▲ 14×1 topic
- Game Theory23▲ 8.4×5 topics
- Smart Home23▲ 8.2×2 topics
- Demand Response22▲ 15×1 topic
- Electricity Markets22▲ 15×1 topic
- Unsupervised Learning22▲ 9.5×3 topics
- Convolutional Networks20▲ 8.8×3 topics
- Metal Recovery20▲ 6.1×3 topics
Which research topics does Tsinghua–Berkeley Shenzhen Institute publish most on?
By volume in 2022–2025: Advancements in Battery Materials, Advanced Battery Materials and Technologies, Advanced Battery Technologies Research and Advanced battery technologies research.
Area is fractional works; colour is the subfield each topic belongs to.
- 1 Advancements in Battery Materials Electrical and Electronic Engineering 53 works
- 2 Advanced Battery Materials and Technologies Electrical and Electronic Engineering 45 works
- 3 Advanced Battery Technologies Research Automotive Engineering 27 works
- 4 Advanced battery technologies research Electrical and Electronic Engineering 24 works
- 5 Smart Grid Energy Management Electrical and Electronic Engineering 22 works
- 6 Electrocatalysts for Energy Conversion Renewable Energy, Sustainability and the Environment 15 works
- 7 Advanced Photocatalysis Techniques Renewable Energy, Sustainability and the Environment 15 works
- 8 Extraction and Separation Processes Mechanical Engineering 13 works
- 9 Advanced Sensor and Energy Harvesting Materials Biomedical Engineering 12 works
- 10 Advanced Neural Network Applications Computer Vision and Pattern Recognition 12 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 Tsinghua–Berkeley Shenzhen Institute's research output changed?
Output in 2018–2022 was 1315% 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 Shenzhen
- Shenzhen University
- Southern University of Science and Technology
- Shenzhen Institutes of Advanced Technology
- Chinese University of Hong Kong, Shenzhen
- Huawei Technologies (China)
- Shenzhen Polytechnic University
- Peng Cheng Laboratory
- University Town of Shenzhen
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.