Laboratoire Bordelais de Recherche en Informatique
In research, Laboratoire Bordelais de Recherche en Informatique stands highest in Computer Science (#2,031 of 4,667 worldwide) and Physical Sciences (#7,076 of 12,888 worldwide), 2022–2025. Relative to its size it is most specialised in Computational Theory and Mathematics and Computer Networks and Communications — Computational Theory and Mathematics is 24.7× its share of world research.
- World rank, 2022–2025
- #12,681 of 28,054 · #5,984 all time
- Rank in France
- #520 of 1,422
- Research works
- 1.9k ▼ 29% vs 2013–17
- Citations
- 23k 12.5 per fractional work
- Top-10% rate
- 9.4% record average 16.5%
- Open access
- 49% world 28%
What is Laboratoire Bordelais de Recherche en Informatique 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 |
|---|---|---|---|---|---|
| Computer ScienceField | #2,031 of 4,667 | 9.3% | 120 | #807 | |
| Physical SciencesDomain | #7,076 of 12,888 | 9.4% | 180 | #3750 |
Each strip is that field’s whole ranked pool, with the notch where Laboratoire Bordelais de Recherche en Informatique 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 Laboratoire Bordelais de Recherche en Informatique specialise in?
Where its research is concentrated relative to its size: Computational Theory and Mathematics takes 24.7× the share of its output that it takes of world research.
- Computational Theory and MathematicsSubfield · 24.6 works25×
- Computer Networks and CommunicationsSubfield · 24.7 works12×
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, 6.6×. Every wedge is a field page.
- Computer Science 6.6×
- Mathematics 6.2×
- Neuroscience 2.8×
- Decision Sciences 1.6×
- Physics and Astronomy 1.4×
- Engineering 0.9×
- Biochemistry, Genetics and Molecular Biology 0.7×
- Psychology 0.6×
- Economics, Econometrics and Finance 0.4×
- Arts and Humanities 0.3×
- Social Sciences 0.2×
- Environmental Science 0.2×
- Medicine 0.2×
- Agricultural and Biological Sciences 0.2×
- Business, Management and Accounting 0.2×
- Chemistry 0.2×
- Materials Science 0.1×
- Veterinary 0.1×
- Health Professions 0.1×
- Immunology and Microbiology 0.0×
- Energy 0.0×
- Earth and Planetary Sciences 0.0×
Who are the top researchers at Laboratoire Bordelais de Recherche en Informatique?
Ranked on the composite score, Fabien Lotte, Martin Hachet and J. M. Robson lead among researchers whose main affiliation is Laboratoire Bordelais de Recherche en Informatique.
- 1 Fabien Lotte France · #23,864 worldwide 639 citations · 89 works
- 2 Martin Hachet France · #100,134 worldwide 239 citations · 67 works
- 3 J. M. Robson France · #119,408 worldwide 194 citations · 37 works
- 4 Mathieu Faverge France · #163,655 worldwide 145 citations · 35 works
- 5 Grégoire Sutre France · #206,478 worldwide 450 citations · 17 works
- 6 Robert Cori France · #210,764 worldwide 149 citations · 28 works
- 7 André Raspaud France · #240,337 worldwide 174 citations · 42 works
- 8 David Auber France · #250,037 worldwide 157 citations · 32 works
- 9 Arnaud Casteigts France · #290,364 worldwide 137 citations · 34 works
- 10 Toufik Ahmed France · #313,422 worldwide 189 citations · 67 works
Which keywords describe research at Laboratoire Bordelais de Recherche en Informatique?
By fractional works in 2022–2025, weighted toward what it does more of than the world: Deep Learning, Distributed Systems, High-Performance Computing, Neural Networks, Parallel Computing, Approximation Algorithms, Machine Learning and Resource Management.
- Motor Imagery
- Routing Protocols
- Data Integration
- Knowledge Representation
- Cloud Computing
- Temporal Logic
- Graph Labeling
- Regular Expressions
- Feature Extraction
- Grid Computing
- Workflow Management
- GPU Computing
- Parameterized Complexity
- Model Checking
- Convolutional Neural Networks
- Graph Theory
- Resource Management
- Parallel Computing
- Distributed Systems
- Machine Learning
- Deep Learning
- Neural Networks
- High-Performance Computing
- Approximation Algorithms
- Algorithmic Applications
- Automata
- Big Data
- Fixed-Parameter Algorithms
- Energy Efficiency
- Performance Optimization
- Fault Tolerance
- Task Scheduling
- Formal Languages
- Deep Neural Networks
- Metric Dimension
- Resource Allocation
- Image Segmentation
- Virtualization
- Human-Computer Interaction
- Wireless Networks
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 Learning33▲ 4.1×57 topics
- Machine Learning16▲ 2.1×47 topics
- Neural Networks14▲ 3.9×26 topics
- Distributed Systems12▲ 32×6 topics
- High-Performance Computing11▲ 55×2 topics
- Parallel Computing9▲ 33×4 topics
- Approximation Algorithms9▲ 55×5 topics
- Resource Management8▲ 20×3 topics
- Algorithmic Applications8▲ 93×2 topics
- Graph Theory7▲ 28×2 topics
- Automata7▲ 108×2 topics
- Convolutional Neural Networks6▲ 3.8×12 topics
- Big Data6▲ 3.0×11 topics
- Model Checking6▲ 58×3 topics
- Fixed-Parameter Algorithms6▲ 116×1 topic
- Parameterized Complexity6▲ 116×1 topic
- Energy Efficiency6▲ 2.6×14 topics
- GPU Computing6▲ 63×1 topic
- Performance Optimization6▲ 37×1 topic
- Workflow Management6▲ 34×2 topics
- Fault Tolerance5▲ 14×5 topics
- Grid Computing5▲ 64×1 topic
- Task Scheduling5▲ 64×1 topic
- Feature Extraction5▲ 4.6×9 topics
- Formal Languages4▲ 183×1 topic
- Regular Expressions4▲ 183×1 topic
- Deep Neural Networks4▲ 17×3 topics
- Graph Labeling4▲ 134×1 topic
- Metric Dimension4▲ 134×1 topic
- Temporal Logic4▲ 55×2 topics
- Resource Allocation4▲ 8.8×6 topics
- Cloud Computing3▲ 5.1×6 topics
- Image Segmentation3▲ 11×3 topics
- Knowledge Representation3▲ 15×3 topics
- Virtualization3▲ 16×2 topics
- Data Integration3▲ 7.5×4 topics
- Human-Computer Interaction3▲ 7.1×5 topics
- Routing Protocols3▲ 24×3 topics
- Wireless Networks3▲ 8.1×9 topics
- Motor Imagery3▲ 9.5×2 topics
Which research topics does Laboratoire Bordelais de Recherche en Informatique publish most on?
By volume in 2022–2025: Advanced Graph Theory Research, Parallel Computing and Optimization Techniques, Distributed and Parallel Computing Systems and semigroups and automata theory.
Area is fractional works; colour is the subfield each topic belongs to.
- 1 Advanced Graph Theory Research Computational Theory and Mathematics 6 works
- 2 Parallel Computing and Optimization Techniques Hardware and Architecture 6 works
- 3 Distributed and Parallel Computing Systems Computer Networks and Communications 5 works
- 4 semigroups and automata theory Computational Theory and Mathematics 4 works
- 5 Graph Labeling and Dimension Problems Computational Theory and Mathematics 4 works
- 6 EEG and Brain-Computer Interfaces Cognitive Neuroscience 3 works
- 7 Cloud Computing and Resource Management Information Systems 3 works
- 8 Formal Methods in Verification Computational Theory and Mathematics 3 works
- 9 Distributed systems and fault tolerance Computer Networks and Communications 2 works
- 10 Advanced Data Storage Technologies Computer Networks and Communications 2 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 Laboratoire Bordelais de Recherche en Informatique's research output changed?
Output in 2018–2022 was 29% 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.
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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.