Huawei Technologies (United States)
In research, Huawei Technologies (United States) stands highest in Computer Science (#2,605 of 4,667 worldwide) and Physical Sciences (#8,669 of 12,888 worldwide), 2022–2025. Relative to its size it is most specialised in Computer Networks and Communications, Electrical and Electronic Engineering and Computer Science — Computer Networks and Communications is 17.4× its share of world research.
- World rank, 2022–2025
- #16,640 of 28,054 · #14,488 all time
- Rank in United States
- #2,368 of 4,192
- Research works
- 889 ▼ 16% vs 2013–17
- Citations
- 16k 17.7 per fractional work
- Top-10% rate
- 13.2% record average 16.5%
- Open access
- 16% world 28%
What is Huawei Technologies (United States) 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 | #2,605 of 4,667 | 14.9% | 65 | #2205 | |
| Physical SciencesDomain | #8,669 of 12,888 | 13.5% | 126 | #8318 |
Each strip is that field’s whole ranked pool, with the notch where Huawei Technologies (United States) 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 Huawei Technologies (United States) specialise in?
Where its research is concentrated relative to its size: Computer Networks and Communications takes 17.4× the share of its output that it takes of world research.
- Computer Networks and CommunicationsSubfield · 20.9 works17×
- Electrical and Electronic EngineeringSubfield · 34.6 works7.2×
- Computer ScienceField · 65.2 works6.2×
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, 6.2×. Every wedge is a field page.
- Computer Science 6.2×
- Engineering 2.7×
- Physics and Astronomy 0.9×
- Decision Sciences 0.8×
- Materials Science 0.6×
- Business, Management and Accounting 0.5×
- Earth and Planetary Sciences 0.4×
- Energy 0.2×
- Mathematics 0.2×
- Neuroscience 0.2×
- Biochemistry, Genetics and Molecular Biology 0.2×
- Economics, Econometrics and Finance 0.1×
- Social Sciences 0.1×
- Environmental Science 0.1×
- Chemical Engineering 0.1×
- Medicine 0.1×
- Immunology and Microbiology 0.0×
- Agricultural and Biological Sciences 0.0×
Who are the top researchers at Huawei Technologies (United States)?
Ranked on the composite score, Xiang Liu, Frank Effenberger and Yuanqiu Luo lead among researchers whose main affiliation is Huawei Technologies (United States).
- 1 Xiang Liu United States · #32,017 worldwide 360 citations · 65 works
- 2 Frank Effenberger United States · #70,549 worldwide 223 citations · 52 works
- 3 Yuanqiu Luo United States · #159,866 worldwide 181 citations · 20 works
- 4 Anthony C. K. Soong United States · #388,048 worldwide 153 citations · 21 works
- 5 Richard Li United States · #883,286 worldwide 106 citations · 53 works
- 6 Jiafeng Zhu United States · #965,880 worldwide 14 citations · 20 works
- 7 Ravishankar Ravindran United States · #989,958 worldwide 81 citations · 18 works
- 8 Aytac Azgin United States · #1,024,738 worldwide 81 citations · 19 works
- 9 Ning Cheng United States · #1,071,336 worldwide 38 citations · 33 works
- 10 Lijun Dong United States · #1,127,455 worldwide 49 citations · 38 works
Which keywords describe research at Huawei Technologies (United States)?
By fractional works in 2022–2025, weighted toward what it does more of than the world: Deep Learning, Energy Efficiency, Neural Networks, Wireless Networks, 5G Networks, Microwave Photonics, Optical Access Networks and Photonic Signal Processing.
- Edge Computing
- Mobile Edge Computing
- Integrated Circuits
- Word Representation
- Machine Translation
- Network Coding
- Neural Machine Translation
- Wireless Communication
- Information-Centric Networking
- IoT Security
- Security
- Content Delivery
- Software-Defined Networking
- Optical Fiber
- Optical Networks
- Photonic Signal Processing
- Convolutional Neural Networks
- Machine Learning
- Wireless Networks
- Energy Efficiency
- Deep Learning
- Neural Networks
- 5G Networks
- Microwave Photonics
- Optical Access Networks
- Elastic Optical Networks
- Coherent Detection
- Network Virtualization
- Distributed Systems
- Internet of Things
- Mobile Networks
- Caching
- Massive MIMO
- Cloud Computing
- Statistical Machine Translation
- Resource Allocation
- Parallel Computing
- Beamforming
- Virtualization
- Security and Privacy
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 Learning22▲ 4.9×49 topics
- Energy Efficiency12▲ 9.3×10 topics
- Neural Networks11▲ 5.2×18 topics
- Wireless Networks8▲ 41×6 topics
- 5G Networks8▲ 28×4 topics
- Machine Learning7▲ 1.58×23 topics
- Microwave Photonics7▲ 58×2 topics
- Convolutional Neural Networks6▲ 6.4×9 topics
- Optical Access Networks6▲ 139×1 topic
- Photonic Signal Processing6▲ 139×1 topic
- Elastic Optical Networks6▲ 269×1 topic
- Optical Networks6▲ 269×1 topic
- Coherent Detection5▲ 91×1 topic
- Optical Fiber5▲ 37×1 topic
- Network Virtualization4▲ 86×1 topic
- Software-Defined Networking4▲ 86×1 topic
- Distributed Systems4▲ 18×6 topics
- Content Delivery4▲ 75×2 topics
- Internet of Things4▲ 3.1×7 topics
- Security4▲ 4.1×12 topics
- Mobile Networks4▲ 66×2 topics
- IoT Security3▲ 7.9×3 topics
- Caching3▲ 77×1 topic
- Information-Centric Networking3▲ 77×1 topic
- Massive MIMO3▲ 29×3 topics
- Wireless Communication3▲ 16×6 topics
- Cloud Computing3▲ 8.3×6 topics
- Neural Machine Translation3▲ 24×1 topic
- Statistical Machine Translation3▲ 24×1 topic
- Network Coding3▲ 46×2 topics
- Resource Allocation3▲ 12×6 topics
- Machine Translation3▲ 12×1 topic
- Parallel Computing3▲ 17×3 topics
- Word Representation3▲ 16×1 topic
- Beamforming3▲ 18×4 topics
- Integrated Circuits3▲ 12×3 topics
- Virtualization2▲ 23×2 topics
- Mobile Edge Computing2▲ 10×2 topics
- Security and Privacy2▲ 8.5×2 topics
- Edge Computing2▲ 12×2 topics
Which research topics does Huawei Technologies (United States) publish most on?
By volume in 2022–2025: Advanced Photonic Communication Systems, Advanced Optical Network Technologies, Optical Network Technologies and Software-Defined Networks and 5G.
Area is fractional works; colour is the subfield each topic belongs to.
- 1 Advanced Photonic Communication Systems Electrical and Electronic Engineering 6 works
- 2 Advanced Optical Network Technologies Electrical and Electronic Engineering 6 works
- 3 Optical Network Technologies Electrical and Electronic Engineering 5 works
- 4 Software-Defined Networks and 5G Computer Networks and Communications 4 works
- 5 Caching and Content Delivery Computer Networks and Communications 3 works
- 6 Natural Language Processing Techniques Artificial Intelligence 3 works
- 7 Topic Modeling Artificial Intelligence 3 works
- 8 IoT and Edge/Fog Computing Computer Networks and Communications 2 works
- 9 Speech Recognition and Synthesis Artificial Intelligence 2 works
- 10 Network Traffic and Congestion Control Computer Networks and Communications 2 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 Huawei Technologies (United States)'s research output changed?
Output in 2018–2022 was 16% lower 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.
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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.