Vector Institute
In research, Vector Institute stands highest in Physical Sciences (#1,197 of 10,670 worldwide), Computer Science (#504 of 4,417 worldwide) and Artificial Intelligence (#369 of 1,862 worldwide), 2022-now. Relative to its size it is most specialised in Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Science (Artificial Intelligence is 10.4× its share of world research).
- World rank, 2022-now
- #1,859 of 22,385 · #1,681 all time
- Rank in Canada
- #46 of 305
- Research works
- 547 ▲ 78% vs 2018-21
- Citations
- 21k 37.8 per fractional work
- Top-10% rate
- 22.2% all institutions 10.0%
- vs its own fields
- 1.33× 1.00× is exactly expected
- Open access
- 69% world 40%
- International
- 45% world 18%
What is Vector Institute 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 |
|---|---|---|---|---|---|
| Physical SciencesDomain | #1,197 of 10,670 | 23.5% | 193 | #1195 | |
| Computer ScienceField | #504 of 4,417 | 21.9% | 126 | #568 | |
| Artificial IntelligenceSubfield | #369 of 1,862 | 19.9% | 73 | #375 |
Each strip is that field's whole ranked pool, with the notch where Vector Institute 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.
- Physical Sciences#1,195 #1,197
- Computer Science#568 #504
- Artificial Intelligence#375 #369
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 Vector Institute work in?
In 2022-now, 65% of research at Vector Institute is in Physical Sciences, 14% in Health Sciences. Its largest fields are Computer Science (43%), Medicine (12%), Engineering (10%). 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 23 fields, with their numbers
- Physical Sciences22565.4%
- Computer Science14843.1%
- Engineering3510.2%
- Materials Science133.9%
- Physics and Astronomy123.5%
- Mathematics51.5%
- Chemistry51.4%
- Environmental Science30.8%
- Energy10.4%
- Chemical Engineering10.3%
- Earth and Planetary Sciences10.3%
- Health Sciences4814.0%
- Medicine4212.3%
- Health Professions61.8%
- Life Sciences3610.5%
- Social Sciences3410.0%
What does Vector Institute specialise in?
Where its research is concentrated relative to its size: Artificial Intelligence takes 10.4× the share of its output that it takes of world research.
- Artificial IntelligenceSubfield · 86.0 works10×
- Computer Vision and Pattern RecognitionSubfield · 35.8 works8.3×
- Computer ScienceField · 148.1 works5.5×
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, 5.5×. Every wedge is a field page.
All 23 fields, with their numbers
- Computer Science5.54×148 works
- Decision Sciences2.33×8 works
- Neuroscience2.26×13 works
- Physics and Astronomy1.59×12 works
- Mathematics1.24×5 works
- Biochemistry, Genetics and Molecular Biology1.14×21 works
- Materials Science1.12×14 works
- Chemical Engineering1.00×1 works
- Chemistry0.87×5 works
- Psychology0.84×9 works
- Engineering0.68×35 works
- Health Professions0.67×6 works
- Medicine0.64×42 works
- Pharmacology, Toxicology and Pharmaceutics0.57×1 works
- Energy0.43×1 works
- Immunology and Microbiology0.30×1 works
- Social Sciences0.29×12 works
- Arts and Humanities0.22×2 works
- Earth and Planetary Sciences0.21×1 works
- Business, Management and Accounting0.20×2 works
- Environmental Science0.17×3 works
- Economics, Econometrics and Finance0.13×1 works
- Agricultural and Biological Sciences0.06×1 works
- Computer Science 5.5×
- Decision Sciences 2.3×
- Neuroscience 2.3×
- Physics and Astronomy 1.6×
- Mathematics 1.2×
- Biochemistry, Genetics and Molecular Biology 1.1×
- Materials Science 1.1×
- Chemical Engineering 1.0×
- Chemistry 0.9×
- Psychology 0.8×
- Engineering 0.7×
- Health Professions 0.7×
- Medicine 0.6×
- Pharmacology, Toxicology and Pharmaceutics 0.6×
- Energy 0.4×
- Immunology and Microbiology 0.3×
- Social Sciences 0.3×
- Arts and Humanities 0.2×
- Earth and Planetary Sciences 0.2×
- Business, Management and Accounting 0.2×
- Environmental Science 0.2×
- Economics, Econometrics and Finance 0.1×
- Agricultural and Biological Sciences 0.1×
Who are the top researchers at Vector Institute?
Ranked on the quality score, Shaina Raza, Jiacheng Yang and Sedef Akinli Koçak lead among researchers whose main affiliation is Vector Institute.
- 1
Shaina Raza
Canada · #165,585 worldwide 1.6k citations · 142 works
- 2
Jiacheng Yang
Canada · #600,274 worldwide 1.5k citations · 38 works
- 3
Sedef Akinli Koçak
Canada · #1,062,712 worldwide 629 citations · 41 works
- 4
D. B. Emerson
Canada · #1,921,195 worldwide 315 citations · 39 works
- 5
Felix Dangel
Canada · #2,209,504 worldwide 149 citations · 37 works
- 6
Faiza Khan Khattak
Canada · #2,221,591 worldwide 310 citations · 23 works
- 7
Nikhil Kandpal
Canada · #2,335,239 worldwide 251 citations · 20 works
- 8
Eu Wern Teh
Canada · #2,846,724 worldwide 130 citations · 17 works
- 9
Arash Afkanpour
Canada · #3,225,308 worldwide 56 citations · 27 works
Which keywords describe research at Vector Institute?
By fractional works in 2022-now, weighted toward what it does more of than the world: Deep Learning, Machine Learning, Neural Networks, Precision Medicine, Unsupervised Learning, Data Mining, Medical Imaging and Information Retrieval.
- Few-Shot Learning
- Radiology
- Ethical Challenges
- Visual Question Answering
- Predictive Modeling
- Statistical Machine Translation
- Transfer Learning
- Deep Neural Networks
- Security
- High-Throughput
- Computational Chemistry
- Word Representation
- Machine Translation
- Representation Learning
- Information Retrieval
- Healthcare
- Medical Imaging
- Unsupervised Learning
- Data Mining
- Machine Learning
- Deep Learning
- Neural Networks
- Precision Medicine
- Artificial Intelligence
- Convolutional Neural Networks
- Big Data
- Text Classification
- Topic Modeling
- Semantic Similarity
- Molecular Dynamics
- Quantum Mechanics
- Materials Informatics
- Semi-Supervised Learning
- Corpus Linguistics
- Neural Machine Translation
- Meta-Learning
- Image Captioning
- Health Equity
- Clinical Decision Support
- Domain Adaptation
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 Learning71▲ 6.0×58 topics
- Machine Learning66▲ 5.8×53 topics
- Neural Networks47▲ 8.9×28 topics
- Data Mining14▲ 5.8×7 topics
- Precision Medicine14▲ 8.3×5 topics
- Unsupervised Learning14▲ 26×3 topics
- Artificial Intelligence13▲ 2.7×11 topics
- Medical Imaging13▲ 7.2×7 topics
- Convolutional Neural Networks13▲ 5.2×11 topics
- Healthcare13▲ 3.2×11 topics
- Big Data12▲ 3.7×12 topics
- Information Retrieval12▲ 16×4 topics
- Text Classification12▲ 21×3 topics
- Representation Learning12▲ 22×3 topics
- Topic Modeling12▲ 22×2 topics
- Machine Translation11▲ 20×2 topics
- Semantic Similarity11▲ 27×1 topic
- Word Representation11▲ 27×1 topic
- Molecular Dynamics11▲ 18×5 topics
- Computational Chemistry10▲ 34×4 topics
- Quantum Mechanics10▲ 29×3 topics
- High-Throughput9▲ 46×1 topic
- Materials Informatics9▲ 46×1 topic
- Security9▲ 3.9×8 topics
- Semi-Supervised Learning9▲ 21×3 topics
- Deep Neural Networks9▲ 20×3 topics
- Corpus Linguistics8▲ 12×3 topics
- Transfer Learning8▲ 12×3 topics
- Neural Machine Translation8▲ 26×1 topic
- Statistical Machine Translation8▲ 26×1 topic
- Meta-Learning8▲ 27×2 topics
- Predictive Modeling8▲ 7.9×2 topics
- Image Captioning7▲ 36×1 topic
- Visual Question Answering7▲ 22×1 topic
- Health Equity7▲ 6.6×4 topics
- Ethical Challenges6▲ 8.7×2 topics
- Clinical Decision Support6▲ 12×1 topic
- Radiology6▲ 13×1 topic
- Domain Adaptation6▲ 32×1 topic
- Few-Shot Learning6▲ 32×1 topic
Which research topics does Vector Institute publish most on?
By volume in 2022-now: Topic Modeling, Machine Learning in Materials Science, Natural Language Processing Techniques and Multimodal Machine Learning Applications.
Area is fractional works; colour is the subfield each topic belongs to.
- 1 Topic Modeling Artificial Intelligence 11 works
- 2 Machine Learning in Materials Science Materials Chemistry 9 works
- 3 Natural Language Processing Techniques Artificial Intelligence 8 works
- 4 Multimodal Machine Learning Applications Computer Vision and Pattern Recognition 7 works
- 5 Artificial Intelligence in Healthcare and Education Health Informatics 6 works
- 6 Domain Adaptation and Few-Shot Learning Artificial Intelligence 6 works
- 7 Explainable Artificial Intelligence (XAI) Artificial Intelligence 6 works
- 8 Adversarial Robustness in Machine Learning Artificial Intelligence 5 works
- 9 Computational Drug Discovery Methods Computational Theory and Mathematics 4 works
- 10 Generative Adversarial Networks and Image Synthesis Computer Vision and Pattern Recognition 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: 40% of research is openly available.
World: 18% is written across borders.
How has Vector Institute's research output changed?
Output in 2022-2025 was 78% higher 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 Vector Institute as a percentage of every work published that year, 0.0012% in 2024.
Fractional works of Vector Institute 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 30.1% in 2019.
Other research institutions in Toronto
- University of Toronto
- York University
- Toronto Metropolitan University
- Princess Margaret Cancer Centre
- Toronto General Hospital
- SickKids Foundation
- Toronto Western Hospital
- Toronto Public Health
Research measures only: rankings here say nothing about teaching, admissions or student experience. Comparable institutions and collaboration partners have tabs of their own, above.
Questions people ask
What does the Vector Institute research?
In research, Vector Institute stands highest in Physical Sciences (#1,197 of 10,670 worldwide), Computer Science (#504 of 4,417 worldwide) and Artificial Intelligence (#369 of 1,862 worldwide), 2022-now. Relative to its size it is most specialised in Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Science (Artificial Intelligence is 10.4× its share of world research).
Discussion
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