RTX (United States)
In research, RTX (United States) stands highest in Physical Sciences (#4,835 of 12,888 worldwide) and Engineering (#4,266 of 6,636 worldwide), 2022–2025. Relative to its size it is most specialised in Aerospace Engineering — Aerospace Engineering is 7.4× its share of world research.
- World rank, 2022–2025
- #8,651 of 28,054 · #1,010 all time
- Rank in United States
- #1,152 of 4,192
- Research works
- 7.6k ▼ 35% vs 2013–17
- Citations
- 135k 17.6 per fractional work
- Top-10% rate
- 11.5% record average 16.5%
- Open access
- 11% world 28%
What is RTX (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 |
|---|---|---|---|---|---|
| Physical SciencesDomain | #4,835 of 12,888 | 12.5% | 243 | #714 | |
| EngineeringField | #4,266 of 6,636 | 10.6% | 136 | #348 |
Each strip is that field’s whole ranked pool, with the notch where RTX (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 RTX (United States) specialise in?
Where its research is concentrated relative to its size: Aerospace Engineering takes 7.4× the share of its output that it takes of world research.
- Aerospace EngineeringSubfield · 25.4 works7.4×
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: Physics and Astronomy, 4.5×. Every wedge is a field page.
- Physics and Astronomy 4.5×
- Engineering 3.1×
- Decision Sciences 2.8×
- Computer Science 2.3×
- Chemical Engineering 1.7×
- Earth and Planetary Sciences 0.9×
- Materials Science 0.8×
- Mathematics 0.7×
- Business, Management and Accounting 0.6×
- Biochemistry, Genetics and Molecular Biology 0.6×
- Health Professions 0.6×
- Chemistry 0.4×
- Environmental Science 0.4×
- Psychology 0.3×
- Energy 0.3×
- Arts and Humanities 0.2×
- Social Sciences 0.2×
- Neuroscience 0.2×
- Nursing 0.2×
- Pharmacology, Toxicology and Pharmaceutics 0.2×
- Medicine 0.1×
- Agricultural and Biological Sciences 0.1×
- Economics, Econometrics and Finance 0.0×
- Immunology and Microbiology 0.0×
Who are the top researchers at RTX (United States)?
Ranked on the composite score, W. C. Brown, Fred Daum and R.A. Pucel lead among researchers whose main affiliation is RTX (United States).
- 1 W. C. Brown United States · #35,821 worldwide 478 citations · 38 works
- 2 Fred Daum United States · #69,022 worldwide 448 citations · 29 works
- 3 R.A. Pucel United States · #89,795 worldwide 327 citations · 25 works
- 4 Jim Huang United States · #130,500 worldwide 306 citations · 26 works
- 5 Ernst Schlömann United States · #153,531 worldwide 174 citations · 21 works
- 6 David K. Barton United States · #171,242 worldwide 136 citations · 22 works
- 7 Ram Ramanathan United States · #196,193 worldwide 157 citations · 27 works
- 8 Colm A. Ryan United States · #205,458 worldwide 239 citations · 18 works
- 9 William Dunlap United States · #240,928 worldwide 103 citations · 19 works
- 10 W. E. Hoke United States · #272,130 worldwide 197 citations · 56 works
Which keywords describe research at RTX (United States)?
By fractional works in 2022–2025, weighted toward what it does more of than the world: Machine Learning, Neural Networks, Deep Learning, Photon Counting, Microwave Photonics, Radiation Detection, Thermal Management and Product Development.
- Semiconductor Lasers
- Hidden Markov Models
- Optical Frequency Combs
- Genetic Algorithms
- Sensitivity Analysis
- Technology Readiness Levels
- Fiber Lasers
- Infrared
- Time-of-Flight
- Nanowires
- Integrated Circuits
- Nonlinear Optics
- Sparse Representation
- Detector Performance
- Microwave Photonics
- Heat Transfer
- Thermal Management
- Biosensors
- Supply Chain Management
- Deep Learning
- Machine Learning
- Neural Networks
- Risk Assessment
- Artificial Neural Networks
- Photon Counting
- Detection
- Radiation Detection
- Product Development
- Fault Diagnosis
- Infrared Detectors
- Laser Ranging
- Semiconductor Materials
- Band Parameters
- Small Target
- System Maturity
- Microresonators
- Complex Adaptive Systems
- Photovoltaics
- Ultrafast Lasers
- Particle Swarm Optimization
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
- Machine Learning20▲ 2.1×34 topics
- Deep Learning16▲ 1.55×28 topics
- Neural Networks12▲ 2.7×16 topics
- Supply Chain Management7▲ 2.6×9 topics
- Risk Assessment7▲ 3.5×7 topics
- Biosensors6▲ 3.9×7 topics
- Artificial Neural Networks6▲ 4.1×7 topics
- Thermal Management6▲ 5.7×6 topics
- Photon Counting6▲ 27×3 topics
- Heat Transfer5▲ 3.6×13 topics
- Detection5▲ 5.8×4 topics
- Microwave Photonics5▲ 19×2 topics
- Radiation Detection5▲ 38×2 topics
- Detector Performance5▲ 49×2 topics
- Product Development5▲ 29×2 topics
- Sparse Representation5▲ 8.0×3 topics
- Fault Diagnosis4▲ 11×5 topics
- Nonlinear Optics4▲ 14×4 topics
- Infrared Detectors4▲ 116×1 topic
- Integrated Circuits4▲ 9.3×3 topics
- Laser Ranging4▲ 60×1 topic
- Nanowires4▲ 10×3 topics
- Semiconductor Materials4▲ 116×1 topic
- Time-of-Flight4▲ 37×1 topic
- Band Parameters4▲ 26×2 topics
- Infrared4▲ 44×1 topic
- Small Target4▲ 44×1 topic
- Fiber Lasers4▲ 14×2 topics
- System Maturity4▲ 64×1 topic
- Technology Readiness Levels4▲ 64×1 topic
- Microresonators4▲ 16×3 topics
- Sensitivity Analysis4▲ 13×3 topics
- Complex Adaptive Systems4▲ 45×2 topics
- Genetic Algorithms4▲ 8.9×3 topics
- Photovoltaics4▲ 7.9×2 topics
- Optical Frequency Combs4▲ 23×1 topic
- Ultrafast Lasers4▲ 23×1 topic
- Hidden Markov Models4▲ 21×3 topics
- Particle Swarm Optimization4▲ 10×3 topics
- Semiconductor Lasers4▲ 18×2 topics
Which research topics does RTX (United States) publish most on?
By volume in 2022–2025: Advanced Semiconductor Detectors and Materials, Advanced Optical Sensing Technologies, Infrared Target Detection Methodologies and Technology Assessment and Management.
Area is fractional works; colour is the subfield each topic belongs to.
- 1 Advanced Semiconductor Detectors and Materials Electrical and Electronic Engineering 4 works
- 2 Advanced Optical Sensing Technologies Instrumentation 4 works
- 3 Infrared Target Detection Methodologies Aerospace Engineering 4 works
- 4 Technology Assessment and Management Safety, Risk, Reliability and Quality 4 works
- 5 Advanced Fiber Laser Technologies Atomic and Molecular Physics, and Optics 4 works
- 6 Systems Engineering Methodologies and Applications Control and Systems Engineering 3 works
- 7 Engineering and Test Systems Control and Systems Engineering 3 works
- 8 Calibration and Measurement Techniques Aerospace Engineering 3 works
- 9 Digital Transformation in Industry Industrial and Manufacturing Engineering 3 works
- 10 Antenna Design and Optimization Aerospace Engineering 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 RTX (United States)'s research output changed?
Output in 2018–2022 was 35% 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 Arlington
- Marymount University
- United States Army
- The Nature Conservancy
- United States Department of the Army
- In-Q-Tel
- United States Department of the Navy
- United States Air Force
- Industrial Research Institute
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.