Embedded Systems (United States)
In research, Embedded Systems (United States) stands highest in Computer Science (#2,592 of 4,667 worldwide), Engineering (#4,027 of 6,636 worldwide) and Physical Sciences (#8,575 of 12,888 worldwide), 2022–2025. Relative to its size it is most specialised in Hardware and Architecture, Computer Networks and Communications and Control and Systems Engineering — Hardware and Architecture is 49.4× its share of world research.
- World rank, 2022–2025
- #13,669 of 28,054 · #7,596 all time
- Rank in United States
- #1,901 of 4,192
- Research works
- 2.2k ▼ 24% vs 2013–17
- Citations
- 30k 13.9 per fractional work
- Top-10% rate
- 9.9% record average 16.5%
- Open access
- 30% world 28%
What is Embedded Systems (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 | #2,592 of 4,667 | 8.7% | 115 | #792 | |
| EngineeringField | #4,027 of 6,636 | 10.9% | 133 | #2868 | |
| Physical SciencesDomain | #8,575 of 12,888 | 9.9% | 273 | #4927 | |
| Social SciencesDomain | #7,735 of 10,521 | 10.3% | 75 | #5164 |
Each strip is that field’s whole ranked pool, with the notch where Embedded Systems (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).
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.
- Computer Science#792 #2,592
- Engineering#2,868 #4,027
- Physical Sciences#4,927 #8,575
- Social Sciences#5,164 #7,735
A dot further right is a better standing. Fields it was not ranked in over the whole record are left out.
What does Embedded Systems (United States) specialise in?
Where its research is concentrated relative to its size: Hardware and Architecture takes 49.4× the share of its output that it takes of world research.
- Hardware and ArchitectureSubfield · 21.1 works49×
- Computer Networks and CommunicationsSubfield · 20.7 works6.1×
- Control and Systems EngineeringSubfield · 20.7 works5.0×
- Computer Vision and Pattern RecognitionSubfield · 22.7 works4.7×
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, 3.9×. Every wedge is a field page.
- Computer Science 3.9×
- Engineering 2.3×
- Arts and Humanities 2.3×
- Decision Sciences 1.0×
- Energy 0.9×
- Neuroscience 0.8×
- Psychology 0.8×
- Mathematics 0.8×
- Social Sciences 0.7×
- Physics and Astronomy 0.5×
- Chemical Engineering 0.5×
- Health Professions 0.5×
- Environmental Science 0.3×
- Earth and Planetary Sciences 0.3×
- Dentistry 0.3×
- Chemistry 0.3×
- Business, Management and Accounting 0.2×
- Veterinary 0.2×
- Agricultural and Biological Sciences 0.2×
- Nursing 0.2×
- Materials Science 0.2×
- Biochemistry, Genetics and Molecular Biology 0.2×
- Medicine 0.2×
- Economics, Econometrics and Finance 0.1×
- Immunology and Microbiology 0.1×
- Pharmacology, Toxicology and Pharmaceutics 0.0×
Who are the top researchers at Embedded Systems (United States)?
Ranked on the composite score, Søren Holst and Don Martí lead among researchers whose main affiliation is Embedded Systems (United States).
- 1 Søren Holst United States · #910,015 worldwide 0 citations · 17 works
- 2 Don Martí United States · #1,528,773 worldwide 1 citations · 25 works
Which keywords describe research at Embedded Systems (United States)?
By fractional works in 2022–2025, weighted toward what it does more of than the world: Deep Learning, Neural Networks, Convolutional Neural Networks, Machine Learning, Computer Vision, Embedded Systems, CMOS Technology and Internet of Things.
- Stability Analysis
- Resource Allocation
- Religious Education
- Reconfigurable Computing
- Sensor Fusion
- Performance Optimization
- Feedback Control
- Smart Grid
- High-Performance Computing
- Electric Vehicles
- Low-Power
- Parallel Computing
- Image Recognition
- FPGA
- Fault Tolerance
- CMOS Technology
- Embedded Systems
- Computer Vision
- Convolutional Neural Networks
- Neural Networks
- Deep Learning
- Machine Learning
- Internet of Things
- Security
- Energy Efficiency
- IoT
- Autonomous Vehicles
- Image Classification
- Object Detection
- Process Variation
- Theology
- Collision Avoidance
- Neuromorphic Computing
- Secularism
- GPU Computing
- Citizenship
- High-Level Synthesis
- Nanoelectronics
- Diversity
- Security Analysis
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 Learning55▲ 4.2×62 topics
- Neural Networks26▲ 4.4×33 topics
- Machine Learning24▲ 1.91×47 topics
- Convolutional Neural Networks14▲ 5.2×12 topics
- Internet of Things13▲ 4.1×16 topics
- Computer Vision11▲ 11×5 topics
- Security11▲ 4.5×16 topics
- Embedded Systems11▲ 66×4 topics
- Energy Efficiency11▲ 3.0×18 topics
- CMOS Technology10▲ 33×5 topics
- IoT9▲ 6.5×11 topics
- Fault Tolerance9▲ 14×7 topics
- Autonomous Vehicles8▲ 11×4 topics
- FPGA8▲ 59×3 topics
- Image Classification8▲ 13×2 topics
- Image Recognition8▲ 16×1 topic
- Object Detection8▲ 17×1 topic
- Parallel Computing8▲ 18×4 topics
- Process Variation8▲ 36×2 topics
- Low-Power8▲ 51×2 topics
- Theology8▲ 22×4 topics
- Electric Vehicles8▲ 6.8×4 topics
- Collision Avoidance8▲ 11×4 topics
- High-Performance Computing7▲ 24×2 topics
- Neuromorphic Computing7▲ 17×2 topics
- Smart Grid7▲ 5.1×7 topics
- Secularism7▲ 17×5 topics
- Feedback Control7▲ 11×7 topics
- GPU Computing7▲ 46×1 topic
- Performance Optimization7▲ 28×1 topic
- Citizenship6▲ 14×3 topics
- Sensor Fusion6▲ 15×3 topics
- High-Level Synthesis6▲ 74×1 topic
- Reconfigurable Computing6▲ 62×1 topic
- Nanoelectronics6▲ 17×2 topics
- Religious Education6▲ 8.7×3 topics
- Diversity6▲ 8.3×3 topics
- Resource Allocation6▲ 8.3×6 topics
- Security Analysis5▲ 8.3×4 topics
- Stability Analysis5▲ 8.7×4 topics
Which research topics does Embedded Systems (United States) publish most on?
By volume in 2022–2025: Advanced Neural Network Applications, Parallel Computing and Optimization Techniques, Embedded Systems Design Techniques and Autonomous Vehicle Technology and Safety.
Area is fractional works; colour is the subfield each topic belongs to.
- 1 Advanced Neural Network Applications Computer Vision and Pattern Recognition 8 works
- 2 Parallel Computing and Optimization Techniques Hardware and Architecture 7 works
- 3 Embedded Systems Design Techniques Hardware and Architecture 6 works
- 4 Autonomous Vehicle Technology and Safety Automotive Engineering 5 works
- 5 Low-power high-performance VLSI design Electrical and Electronic Engineering 5 works
- 6 Biblical Studies and Interpretation Religious studies 5 works
- 7 Religious Education and Schools Education 5 works
- 8 Advanced Memory and Neural Computing Electrical and Electronic Engineering 5 works
- 9 Education, Healthcare and Sociology Research Social Psychology 4 works
- 10 Real-Time Systems Scheduling Hardware and Architecture 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 Embedded Systems (United States)'s research output changed?
Output in 2018–2022 was 24% 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.
Other research institutions in Middletown
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.