Carnegie Mellon University
In research, Carnegie Mellon University stands highest in Computer Science (#7 of 4,417 worldwide), Artificial Intelligence (#11 of 1,862 worldwide) and Physical Sciences (#67 of 10,670 worldwide), 2022-now. Relative to its size it is most specialised in Software, Human-Computer Interaction and Hardware and Architecture (Software is 9.3× its share of world research).
- World rank, 2022-now
- #115 of 22,385 · #91 all time
- Rank in United States
- #37 of 3,332
- Research works
- 83k ▼ 25% vs 2018-21
- Citations
- 4.2M 50.4 per fractional work
- Top-10% rate
- 14.4% all institutions 10.0%
- vs its own fields
- 1.37× 1.00× is exactly expected
- Open access
- 33% world 40%
- International
- 15% world 18%
What is Carnegie Mellon University known for in research?
The fields where it stands highest, 2022-now, ranked among every institution above the floor in each field.
| Field | World rank | Where that sits | Top-10% rate | Works | All time |
|---|---|---|---|---|---|
| Computer ScienceField | #7 of 4,417 | 16.0% | 2,815 | #4 | |
| Artificial IntelligenceSubfield | #11 of 1,862 | 15.0% | 1,077 | #8 | |
| Physical SciencesDomain | #67 of 10,670 | 14.9% | 5,854 | #62 | |
| Social SciencesDomain | #102 of 9,585 | 15.9% | 1,677 | #72 | |
| Information SystemsSubfield | #17 of 1,321 | 17.1% | 259 | #7 | |
| EngineeringField | #79 of 5,901 | 14.0% | 1,747 | #50 | |
| Human-Computer InteractionSubfield | #1 of 72 | 22.1% | 131 | #3 | |
| Computer Vision and Pattern RecognitionSubfield | #19 of 963 | 18.0% | 480 | #9 | |
| Social SciencesField | #158 of 5,988 | 17.5% | 693 | #137 | |
| Control and Systems EngineeringSubfield | #26 of 804 | 15.6% | 237 | #24 |
Each strip is that field's whole ranked pool, with the notch where Carnegie Mellon University 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 average mark, because the average differs by field (from about 6% in Dentistry to 21% in Economics).
Which of those standings moved
The same fields on both windows: where it stood over the whole record, and where it stands in 2022-now. The distance is the story, and it is the one thing the two rank columns above cannot show.
- Computer Science#4 #7
- Artificial Intelligence#8 #11
- Physical Sciences#62 #67
- Social Sciences#72 #102
- Information Systems#7 #17
- Engineering#50 #79
- Human-Computer Interaction#3 #1
- Computer Vision and Pattern Recognition#9 #19
- Social Sciences#137 #158
- Control and Systems Engineering#24 #26
A dot further right is a better standing. Fields it was not ranked in over the whole record are left out.
Which fields of science does Carnegie Mellon University work in?
In 2022-now, 67% of research at Carnegie Mellon University is in Physical Sciences, 19% in Social Sciences. Its largest fields are Computer Science (33%), Engineering (19%), Social Sciences (8%). It does 1.7× the world's share of Physical Sciences.
Each ring splits the one inside it: the four domains of science, their fields, their subfields. Size is fractional works in 2022-now. Every slice is a page; the interactive view zooms down to single topics and colours each by how much more of it this institution does than the world.
Its 4 domains and 26 fields, with their numbers
- Physical Sciences6,59367.0%
- Computer Science3,20732.6%
- Engineering1,91719.5%
- Physics and Astronomy3523.6%
- Materials Science3223.3%
- Mathematics2772.8%
- Environmental Science2122.2%
- Chemistry1171.2%
- Earth and Planetary Sciences850.9%
- Energy760.8%
- Chemical Engineering280.3%
- Social Sciences1,91319.4%
- Social Sciences7827.9%
- Psychology3723.8%
- Decision Sciences2482.5%
- Business, Management and Accounting2022.1%
- Economics, Econometrics and Finance1551.6%
- Arts and Humanities1541.6%
- Life Sciences8018.1%
- Health Sciences5365.4%
- Medicine4334.4%
- Health Professions920.9%
- Nursing70.1%
- Dentistry30.0%
- Veterinary10.0%
What does Carnegie Mellon University specialise in?
Where its research is concentrated relative to its size: Software takes 9.3× the share of its output that it takes of world research.
- SoftwareSubfield · 58.6 works9.3×
- Human-Computer InteractionSubfield · 149.3 works7.3×
- Hardware and ArchitectureSubfield · 81.1 works7.3×
- Computer Graphics and Computer-Aided DesignSubfield · 53.4 works6.6×
- Discrete Mathematics and CombinatoricsSubfield · 22.3 works5.7×
- Artificial IntelligenceSubfield · 1,255.4 works5.3×
- Statistics and ProbabilitySubfield · 110.3 works5.3×
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, 4.2×. Every wedge is a field page.
All 26 fields, with their numbers
- Computer Science4.19×3,207 works
- Decision Sciences2.60×248 works
- Mathematics2.39×277 works
- Neuroscience2.07×330 works
- Physics and Astronomy1.61×352 works
- Engineering1.30×1,917 works
- Psychology1.24×372 works
- Materials Science0.94×322 works
- Energy0.84×76 works
- Chemical Engineering0.80×28 works
- Chemistry0.76×117 works
- Biochemistry, Genetics and Molecular Biology0.74×387 works
- Economics, Econometrics and Finance0.74×155 works
- Business, Management and Accounting0.64×202 works
- Social Sciences0.63×782 works
- Earth and Planetary Sciences0.55×85 works
- Arts and Humanities0.54×154 works
- Environmental Science0.43×212 works
- Health Professions0.35×92 works
- Medicine0.23×433 works
- Pharmacology, Toxicology and Pharmaceutics0.21×7 works
- Immunology and Microbiology0.20×20 works
- Nursing0.15×7 works
- Agricultural and Biological Sciences0.12×57 works
- Veterinary0.08×1 works
- Dentistry0.07×3 works
- Computer Science 4.2×
- Decision Sciences 2.6×
- Mathematics 2.4×
- Neuroscience 2.1×
- Physics and Astronomy 1.6×
- Engineering 1.3×
- Psychology 1.2×
- Materials Science 0.9×
- Energy 0.8×
- Chemical Engineering 0.8×
- Chemistry 0.8×
- Biochemistry, Genetics and Molecular Biology 0.7×
- Economics, Econometrics and Finance 0.7×
- Business, Management and Accounting 0.6×
- Social Sciences 0.6×
- Earth and Planetary Sciences 0.6×
- Arts and Humanities 0.5×
- Environmental Science 0.4×
- Health Professions 0.3×
- Medicine 0.2×
- Pharmacology, Toxicology and Pharmaceutics 0.2×
- Immunology and Microbiology 0.2×
- Nursing 0.1×
- Agricultural and Biological Sciences 0.1×
- Veterinary 0.1×
- Dentistry 0.1×
Who are the top researchers at Carnegie Mellon University?
Ranked on the quality score, George F. Loewenstein, Ignacio E. Grossmann and Rongchao Jin lead among researchers whose main affiliation is Carnegie Mellon University.
- 1
George F. Loewenstein
United States · #1,548 worldwide 105k citations · 698 works
- 2
Ignacio E. Grossmann
United States · #1,649 worldwide 55k citations · 943 works
- 3
Rongchao Jin
United States · #1,743 worldwide 69k citations · 520 works
- 4
John Anthony Pople
United States · #2,847 worldwide 202k citations · 611 works
- 5
Deva Ramanan
United States · #3,063 worldwide 86k citations · 336 works
- 6
Daniel S. Nagin
United States · #3,912 worldwide 55k citations · 334 works
- 7
Abhinav Gupta
United States · #5,563 worldwide 39k citations · 222 works
- 8
Onur Mutlu
United States · #5,670 worldwide 44k citations · 835 works
- 9
Michael F. Scheier
United States · #6,066 worldwide 89k citations · 262 works
- 10
Gregory Victor Lowry
United States · #6,363 worldwide 40k citations · 368 works
Which keywords describe research at Carnegie Mellon University?
By fractional works in 2022-now, weighted toward what it does more of than the world: Deep Learning, Machine Learning, Neural Networks, Big Data, Multi-Agent Systems, Information Retrieval, Text Classification and Topic Modeling.
- Gesture Recognition
- Convex Optimization
- Model Checking
- Algorithmic Bias
- Accountability
- Discrimination
- Fairness
- Statistical Machine Translation
- Collision Avoidance
- Approximation Algorithms
- Corpus Linguistics
- Deep Neural Networks
- Word Representation
- Machine Translation
- Topic Modeling
- Multi-Agent Systems
- Information Retrieval
- Convolutional Neural Networks
- Big Data
- Machine Learning
- Deep Learning
- Neural Networks
- Artificial Intelligence
- Data Mining
- Surveillance
- Text Classification
- Security
- Semantic Similarity
- Autonomous Vehicles
- Robotics
- Distributed Systems
- Reinforcement Learning
- Neural Machine Translation
- Unsupervised Learning
- Anomaly Detection
- Representation Learning
- Transparency
- Semi-Supervised Learning
- Convolutional Networks
- Mobile Robots
Size is fractional works in 2022-now 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 Learning1,138▲ 3.4×82 topics
- Machine Learning886▲ 2.7×86 topics
- Neural Networks634▲ 4.2×38 topics
- Big Data276▲ 2.9×27 topics
- Artificial Intelligence270▲ 1.93×47 topics
- Convolutional Neural Networks208▲ 2.9×14 topics
- Data Mining166▲ 2.3×20 topics
- Information Retrieval156▲ 7.3×5 topics
- Surveillance156▲ 5.7×6 topics
- Multi-Agent Systems151▲ 8.0×6 topics
- Text Classification147▲ 9.2×3 topics
- Topic Modeling145▲ 9.6×3 topics
- Security141▲ 2.1×24 topics
- Machine Translation138▲ 8.4×2 topics
- Semantic Similarity137▲ 11×1 topic
- Word Representation137▲ 11×1 topic
- Autonomous Vehicles135▲ 6.6×5 topics
- Deep Neural Networks130▲ 11×3 topics
- Robotics125▲ 5.2×9 topics
- Corpus Linguistics118▲ 5.7×4 topics
- Distributed Systems110▲ 6.5×6 topics
- Approximation Algorithms106▲ 15×5 topics
- Reinforcement Learning106▲ 9.4×4 topics
- Collision Avoidance103▲ 5.8×4 topics
- Neural Machine Translation102▲ 11×1 topic
- Statistical Machine Translation102▲ 11×1 topic
- Unsupervised Learning102▲ 6.8×3 topics
- Fairness100▲ 9.8×2 topics
- Anomaly Detection98▲ 3.5×5 topics
- Discrimination93▲ 4.5×7 topics
- Representation Learning92▲ 5.9×3 topics
- Accountability90▲ 7.2×4 topics
- Transparency89▲ 6.3×3 topics
- Algorithmic Bias87▲ 10×1 topic
- Semi-Supervised Learning84▲ 7.0×3 topics
- Model Checking83▲ 18×3 topics
- Convolutional Networks78▲ 5.8×3 topics
- Convex Optimization77▲ 9.3×5 topics
- Mobile Robots77▲ 8.1×3 topics
- Gesture Recognition73▲ 9.9×3 topics
Which research topics does Carnegie Mellon University publish most on?
By volume in 2022-now: Topic Modeling, Natural Language Processing Techniques, Ethics and Social Impacts of AI and Multimodal Machine Learning Applications.
Area is fractional works; colour is the subfield each topic belongs to.
- 1 Topic Modeling Artificial Intelligence 137 works
- 2 Natural Language Processing Techniques Artificial Intelligence 102 works
- 3 Ethics and Social Impacts of AI Safety Research 87 works
- 4 Multimodal Machine Learning Applications Computer Vision and Pattern Recognition 65 works
- 5 Robotic Path Planning Algorithms Computer Vision and Pattern Recognition 64 works
- 6 Robot Manipulation and Learning Control and Systems Engineering 58 works
- 7 Reinforcement Learning in Robotics Artificial Intelligence 56 works
- 8 Explainable Artificial Intelligence (XAI) Artificial Intelligence 54 works
- 9 Speech Recognition and Synthesis Artificial Intelligence 54 works
- 10 Software Engineering Research Information Systems 52 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: 40% of research is openly available.
World: 18% is written across borders.
How has Carnegie Mellon University's research output changed?
Output in 2022-2025 was 25% lower than in 2018-2021.
The same series as a ribbon: one cell per year, darker for more. The line above answers how much; this answers when.
Its share of all research
Growing output can still be a shrinking share: all of science grows. This is Carnegie Mellon University as a percentage of every work published that year, 0.038% in 2024.
Fractional works of Carnegie Mellon University over all fractional works that year. How the balance of science has shifted.
How much of it reaches the world top 10%
Year by year, against all institutions in the same year.
Of each year's output, the share that reached the world's 10% most cited for its field and year. Peak 23.0% in 2007.
Other research institutions in Pittsburgh
- University of Pittsburgh
- University of Pittsburgh Medical Center
- Duquesne University
- La Roche College
- Allegheny Health Network
- UPMC Health System
- Robert Morris University
- PPG Industries (United States)
Which institutions have research most like Carnegie Mellon University's?
Among the world's leading institutions, The University of Texas at Dallas has the research profile closest to Carnegie Mellon University's, with both strong in Computer Science.
- 1
The University of Texas at Dallas
United States · Both strong in Computer Science, Neuroscience, Decision Sciences 0.92 Compare
- 2
Northeastern University
United States · Both strong in Computer Science, Neuroscience, Decision Sciences 0.90 Compare
- 3
Nanyang Technological University
Singapore · Both strong in Computer Science, Physics and Astronomy, Engineering 0.89 Compare
- 4
Georgia Institute of Technology
United States · Both strong in Computer Science, Decision Sciences, Mathematics 0.89 Compare
- 5
Eindhoven University of Technology
Netherlands · Both strong in Computer Science, Decision Sciences, Physics and Astronomy 0.88 Compare
Similarity is the correlation of each side's location quotients across every field it publishes in, on a log scale: 1 is the same shape of research, 0 is unrelated. It ignores size. How it is measured.
Compare Carnegie Mellon University with
- vs
University of Birmingham
- vs
Queen Mary University of London
- vs
Erasmus University Rotterdam
- vs
University of Geneva
- vs
Seoul National University
- vs
Indiana University
Research measures only: rankings here say nothing about teaching, admissions or student experience. Comparable institutions and collaboration partners have tabs of their own, above.
Discussion
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