Toyota Research Institute
In research, Toyota Research Institute stands highest in Physical Sciences (#3,329 of 12,888 worldwide) and Engineering (#3,002 of 6,636 worldwide), 2022–2025. Relative to its size it is most specialised in Computer Vision and Pattern Recognition — Computer Vision and Pattern Recognition is 7.5× its share of world research.
- World rank, 2022–2025
- #5,065 of 28,054 · #7,144 all time
- Rank in ??
- #67 of 692
- Research works
- 595 ▲ 68% vs 2013–17
- Citations
- 24k 39.7 per fractional work
- Top-10% rate
- 30.6% record average 16.5%
- Open access
- 37% world 28%
What is Toyota Research Institute 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 | #3,329 of 12,888 | 29.0% | 193 | #4545 | |
| EngineeringField | #3,002 of 6,636 | 26.7% | 105 | #2867 |
Each strip is that field’s whole ranked pool, with the notch where Toyota Research 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 world mark, because the world rate differs by field (from about 6% to 21% in this record).
What does Toyota Research Institute specialise in?
Where its research is concentrated relative to its size: Computer Vision and Pattern Recognition takes 7.5× the share of its output that it takes of world research.
- Computer Vision and Pattern RecognitionSubfield · 21.2 works7.5×
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: Engineering, 3.1×. Every wedge is a field page.
- Engineering 3.1×
- Energy 3.1×
- Computer Science 3.0×
- Psychology 2.0×
- Materials Science 2.0×
- Chemical Engineering 1.4×
- Physics and Astronomy 1.2×
- Decision Sciences 1.1×
- Neuroscience 1.1×
- Chemistry 0.6×
- Earth and Planetary Sciences 0.5×
- Mathematics 0.2×
- Environmental Science 0.2×
- Social Sciences 0.2×
- Health Professions 0.2×
- Biochemistry, Genetics and Molecular Biology 0.1×
- Economics, Econometrics and Finance 0.1×
- Medicine 0.0×
- Business, Management and Accounting 0.0×
- Arts and Humanities 0.0×
- Agricultural and Biological Sciences 0.0×
Who are the top researchers at Toyota Research Institute?
Ranked on the composite score, Adrien Gaidon, Pavel Tokmakov and Ercan M. Dede lead among researchers whose main affiliation is Toyota Research Institute.
- 1 Adrien Gaidon ?? · #121,630 worldwide 286 citations · 45 works
- 2 Pavel Tokmakov ?? · #156,594 worldwide 328 citations · 26 works
- 3 Ercan M. Dede ?? · #195,338 worldwide 230 citations · 42 works
- 4 Chen Ling ?? · #298,128 worldwide 210 citations · 22 works
- 5 Simon Stent ?? · #353,528 worldwide 127 citations · 23 works
- 6 Shailesh N. Joshi ?? · #397,147 worldwide 99 citations · 18 works
- 7 Feng Zhou ?? · #422,102 worldwide 129 citations · 22 works
- 8 Timothy S. Arthur ?? · #514,345 worldwide 168 citations · 16 works
- 9 Vitor Guizilini ?? · #851,143 worldwide 78 citations · 31 works
- 10 Rareş Ambruş ?? · #1,117,574 worldwide 79 citations · 32 works
Which keywords describe research at Toyota Research Institute?
By fractional works in 2022–2025, weighted toward what it does more of than the world: Deep Learning, Autonomous Vehicles, Neural Networks, Cathode Materials, Machine Learning, Electric Vehicles, Thermal Management and Convolutional Networks.
- Trajectory Prediction
- Battery Technology
- 3D Reconstruction
- Sensor Fusion
- High-Throughput
- Quantum Mechanics
- Hydrogen Evolution
- Rechargeable Batteries
- Proton Exchange Membranes
- Metal-Organic Frameworks
- Electrocatalysis
- Catalysts
- Unsupervised Learning
- Model Predictive Control
- Energy Storage
- Depth Estimation
- Convolutional Networks
- Electric Vehicles
- Autonomous Vehicles
- Machine Learning
- Deep Learning
- Neural Networks
- Cathode Materials
- Thermal Management
- Lithium-ion Batteries
- Control Systems
- Energy Conversion
- Collision Avoidance
- Human-Robot Interaction
- Fuel Cells
- Robotics
- Polymer Electrolyte Membranes
- Optical Flow
- Stereo Vision
- Oxygen Reduction
- Driver Behavior
- Materials Informatics
- Power Electronics
- Point Clouds
- Driver Assistance Systems
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 Learning30▲ 3.9×40 topics
- Machine Learning16▲ 2.2×31 topics
- Neural Networks13▲ 3.8×22 topics
- Autonomous Vehicles12▲ 25×4 topics
- Cathode Materials9▲ 10×3 topics
- Electric Vehicles8▲ 13×4 topics
- Thermal Management8▲ 11×3 topics
- Convolutional Networks8▲ 26×3 topics
- Lithium-ion Batteries7▲ 7.6×2 topics
- Depth Estimation7▲ 37×2 topics
- Control Systems7▲ 16×4 topics
- Energy Storage7▲ 4.6×7 topics
- Energy Conversion7▲ 14×3 topics
- Model Predictive Control7▲ 11×5 topics
- Collision Avoidance6▲ 16×3 topics
- Unsupervised Learning6▲ 20×3 topics
- Human-Robot Interaction6▲ 27×3 topics
- Catalysts6▲ 13×3 topics
- Fuel Cells6▲ 17×2 topics
- Electrocatalysis6▲ 9.0×2 topics
- Robotics6▲ 10×4 topics
- Metal-Organic Frameworks6▲ 5.9×3 topics
- Polymer Electrolyte Membranes6▲ 33×1 topic
- Proton Exchange Membranes6▲ 33×1 topic
- Optical Flow5▲ 48×1 topic
- Rechargeable Batteries5▲ 8.9×2 topics
- Stereo Vision5▲ 48×1 topic
- Hydrogen Evolution5▲ 18×1 topic
- Oxygen Reduction5▲ 18×1 topic
- Quantum Mechanics5▲ 29×2 topics
- Driver Behavior5▲ 30×2 topics
- High-Throughput5▲ 43×1 topic
- Materials Informatics5▲ 43×1 topic
- Sensor Fusion5▲ 20×3 topics
- Power Electronics5▲ 6.3×5 topics
- 3D Reconstruction4▲ 22×2 topics
- Point Clouds4▲ 22×2 topics
- Battery Technology4▲ 6.9×2 topics
- Driver Assistance Systems4▲ 35×1 topic
- Trajectory Prediction4▲ 35×1 topic
Which research topics does Toyota Research Institute publish most on?
By volume in 2022–2025: Fuel Cells and Related Materials, Advanced Vision and Imaging, Electrocatalysts for Energy Conversion and Machine Learning in Materials Science.
Area is fractional works; colour is the subfield each topic belongs to.
- 1 Fuel Cells and Related Materials Electrical and Electronic Engineering 6 works
- 2 Advanced Vision and Imaging Computer Vision and Pattern Recognition 5 works
- 3 Electrocatalysts for Energy Conversion Renewable Energy, Sustainability and the Environment 5 works
- 4 Machine Learning in Materials Science Materials Chemistry 5 works
- 5 Autonomous Vehicle Technology and Safety Automotive Engineering 4 works
- 6 Advanced Battery Technologies Research Automotive Engineering 4 works
- 7 Robot Manipulation and Learning Control and Systems Engineering 4 works
- 8 Advanced Battery Materials and Technologies Electrical and Electronic Engineering 4 works
- 9 Social Robot Interaction and HRI Social Psychology 3 works
- 10 Advancements in Battery Materials Electrical and Electronic 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 Toyota Research Institute's research output changed?
Output in 2018–2022 was 68% higher 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 Palo Alto
- Stanford Cancer Institute
- VMware (United States)
- Arc Research Institute
- Institute for Stem Cell Biology and Regenerative Medicine
- Emerson Collective (United States)
- Peninsula Open Space Trust
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.