Center for Information Technology
In research, Center for Information Technology stands highest in Physical Sciences (#5,370 of 12,888 worldwide), 2022–2025. Relative to its size it is most specialised in Computer Science — Computer Science is 5.0× its share of world research.
- World rank, 2022–2025
- #6,789 of 28,054 · #5,914 all time
- Rank in United States
- #906 of 4,192
- Research works
- 1.5k ▼ 16% vs 2013–17
- Citations
- 54k 35.2 per fractional work
- Top-10% rate
- 28.1% record average 16.5%
- Open access
- 30% world 28%
What is Center for Information Technology 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 | #5,370 of 12,888 | 19.8% | 79 | #5462 |
Each strip is that field’s whole ranked pool, with the notch where Center for Information Technology 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 Center for Information Technology specialise in?
Where its research is concentrated relative to its size: Computer Science takes 5.0× the share of its output that it takes of world research.
- Computer ScienceField · 46.5 works5.0×
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, 5.0×. Every wedge is a field page.
- Computer Science 5.0×
- Physics and Astronomy 2.2×
- Decision Sciences 1.6×
- Engineering 1.2×
- Biochemistry, Genetics and Molecular Biology 1.1×
- Neuroscience 1.1×
- Veterinary 1.0×
- Social Sciences 1.0×
- Dentistry 0.8×
- Immunology and Microbiology 0.5×
- Earth and Planetary Sciences 0.5×
- Health Professions 0.5×
- Psychology 0.5×
- Materials Science 0.4×
- Business, Management and Accounting 0.3×
- Medicine 0.3×
- Arts and Humanities 0.3×
- Mathematics 0.2×
- Chemistry 0.2×
- Pharmacology, Toxicology and Pharmaceutics 0.2×
- Economics, Econometrics and Finance 0.2×
- Environmental Science 0.1×
- Chemical Engineering 0.1×
- Agricultural and Biological Sciences 0.0×
Who are the top researchers at Center for Information Technology?
Ranked on the composite score, Norbert Streitz, Rosalie Steier and Hans‐Rüdiger Pfister lead among researchers whose main affiliation is Center for Information Technology.
- 1 Norbert Streitz United States · #51,974 worldwide 324 citations · 47 works
- 2 Rosalie Steier United States · #311,649 worldwide 1 citations · 29 works
- 3 Hans‐Rüdiger Pfister United States · #644,427 worldwide 59 citations · 26 works
- 4 Seth United States · #1,049,384 worldwide 11 citations · 20 works
- 5 Erik United States · #1,087,412 worldwide 3 citations · 17 works
- 6 Yuan Gao United States · #1,271,127 worldwide 14 citations · 15 works
- 7 Manfred Bogen United States · #1,392,360 worldwide 7 citations · 16 works
Which keywords describe research at Center for Information Technology?
By fractional works in 2022–2025, weighted toward what it does more of than the world: Deep Learning, Neural Networks, Machine Learning, Social Media, Topic Modeling, Convolutional Neural Networks, Machine Translation and Word Representation.
- Depth Estimation
- Polarization
- Optical Modulators
- Image Captioning
- Bioinformatics
- Microwave Photonics
- Energy Harvesting
- Multi-hop Networks
- Wireless Communication
- Media Use
- Wireless Sensor Networks
- Online Communication
- Digital Divide
- Statistical Machine Translation
- Artificial Intelligence
- Wireless Networks
- Word Representation
- Topic Modeling
- Social Media
- Machine Learning
- Deep Learning
- Neural Networks
- Convolutional Neural Networks
- Machine Translation
- Big Data
- Energy Efficiency
- Neural Machine Translation
- Healthcare
- Natural Language Processing
- Unsupervised Learning
- Deliberative Democracy
- Political Participation
- Convolutional Networks
- 5G Networks
- Age of Information
- Real-time Status Updates
- Data Analysis
- Visual Question Answering
- Transfer Learning
- Resource Allocation
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 Learning20▲ 4.9×48 topics
- Machine Learning13▲ 3.4×34 topics
- Neural Networks11▲ 6.1×20 topics
- Social Media8▲ 4.7×15 topics
- Convolutional Neural Networks5▲ 5.8×10 topics
- Topic Modeling5▲ 26×2 topics
- Machine Translation4▲ 21×1 topic
- Word Representation4▲ 29×1 topic
- Big Data4▲ 3.5×10 topics
- Wireless Networks4▲ 20×5 topics
- Energy Efficiency4▲ 3.2×6 topics
- Artificial Intelligence3▲ 1.99×11 topics
- Neural Machine Translation3▲ 28×1 topic
- Statistical Machine Translation3▲ 28×1 topic
- Healthcare3▲ 2.3×6 topics
- Digital Divide3▲ 9.3×3 topics
- Natural Language Processing3▲ 9.6×5 topics
- Online Communication3▲ 15×3 topics
- Unsupervised Learning3▲ 16×3 topics
- Wireless Sensor Networks3▲ 5.0×9 topics
- Deliberative Democracy3▲ 28×2 topics
- Media Use2▲ 34×1 topic
- Political Participation2▲ 24×1 topic
- Wireless Communication2▲ 13×3 topics
- Convolutional Networks2▲ 13×3 topics
- Multi-hop Networks2▲ 88×2 topics
- 5G Networks2▲ 8.6×3 topics
- Energy Harvesting2▲ 9.6×2 topics
- Age of Information2▲ 123×1 topic
- Microwave Photonics2▲ 19×2 topics
- Real-time Status Updates2▲ 123×1 topic
- Bioinformatics2▲ 14×4 topics
- Data Analysis2▲ 5.7×5 topics
- Image Captioning2▲ 33×1 topic
- Visual Question Answering2▲ 20×1 topic
- Optical Modulators2▲ 10×3 topics
- Transfer Learning2▲ 7.7×3 topics
- Polarization2▲ 9.2×3 topics
- Resource Allocation2▲ 8.0×3 topics
- Depth Estimation2▲ 16×2 topics
Which research topics does Center for Information Technology publish most on?
By volume in 2022–2025: Topic Modeling, Natural Language Processing Techniques, Social Media and Politics and Age of Information Optimization.
Area is fractional works; colour is the subfield each topic belongs to.
- 1 Topic Modeling Artificial Intelligence 4 works
- 2 Natural Language Processing Techniques Artificial Intelligence 3 works
- 3 Social Media and Politics Communication 2 works
- 4 Age of Information Optimization Computer Networks and Communications 2 works
- 5 Multimodal Machine Learning Applications Computer Vision and Pattern Recognition 2 works
- 6 Advanced Neural Network Applications Computer Vision and Pattern Recognition 2 works
- 7 Advanced Fiber Laser Technologies Atomic and Molecular Physics, and Optics 1 works
- 8 Hate Speech and Cyberbullying Detection Artificial Intelligence 1 works
- 9 Misinformation and Its Impacts Sociology and Political Science 1 works
- 10 IoT Networks and Protocols Electrical and Electronic Engineering 1 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 Center for Information Technology'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.
Other research institutions in Bethesda
- National Institutes of Health
- National Cancer Institute
- Uniformed Services University of the Health Sciences
- National Institute of Allergy and Infectious Diseases
- Lockheed Martin (United States)
- National Heart Lung and Blood Institute
- National Institute of Mental Health
- National Institute of Diabetes and Digestive and Kidney Diseases
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.