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Researcher · VeDeCoM Institute · France

Mohamed-Cherif Rahal

Mohamed-Cherif Rahal publishes mostly in Automotive Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence, on topics such as Autonomous Vehicle Technology and Safety, Traffic control and management and Target Tracking and Data Fusion in Sensor Networks.

ORCID 0009-0002-3504-1382 OpenAlex
World rank
#4,004,698
of 7,710,434 ranked researchers
Rank in France
#168,597
of 324,115
Works
23
Citations
223
Citations per work
9.7
h-index
6
i10-index 5Top 70% in Automotive Engineering
Mohamed-Cherif Rahal

What does Mohamed-Cherif Rahal research?

Mohamed-Cherif Rahal's work is mostly in Engineering (40%), Computer Science (34%), Psychology (5%).

Physical Sciences: 17 works · 74.2% of their workEngineering: 9 works · 40.4% of their workAutomotive Engineering: 6 works · 25.8% of their workAerospace Engineering: 2 works · 8.1% of their workControl and Systems Engineering: 1 works · 6.5% of their workComputer Science: 8 works · 33.8% of their workComputer Vision and Pattern Recognition: 4 works · 17.7% of their workArtificial Intelligence: 4 works · 16.1% of their workEverything else: 5 works · 21.0% of their workSocial Sciences: 1 works · 4.8% of their workPsychology: 1 works · 4.8% of their workSocial Psychology: 1 works · 4.8% of their workTHEIR WORKMohamed-CherifRahal23works
Physical Sciences74%Social Sciences5%

Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.

The fields and subfields, with their numbers
    1. Engineering940.4%
    2. Computer Science833.8%
  2. Everything else521.0%
    1. Psychology14.8%
  1. 1Automotive Engineering26% of their works
  2. 2Computer Vision and Pattern Recognition18% of their works
  3. 3Artificial Intelligence16% of their works
  4. 4Aerospace Engineering8% of their works
  5. 5Control and Systems Engineering6% of their works
  6. 6Social Psychology5% of their works

Research topics

Which keywords describe Mohamed-Cherif Rahal's research?

The keywords of their largest research topics: Deep Learning, Sensor Fusion, Autonomous Vehicles, Collision Avoidance, Driver Assistance Systems, Trajectory Prediction, Microscopic Simulation and Traffic Flow.

Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most. The words come from the keyword list OpenAlex gives each topic, not from the text of the papers, so a word can appear that none of the papers uses.

All 20 words, with their numbers
  1. Deep Learning193 topics
  2. Sensor Fusion172 topics
  3. Autonomous Vehicles162 topics
  4. Collision Avoidance162 topics
  5. Driver Assistance Systems141 topic
  6. Trajectory Prediction141 topic
  7. Microscopic Simulation41 topic
  8. Traffic Flow41 topic
  9. 3D Mapping31 topic
  10. Convolutional Neural Networks31 topic
  11. Image Recognition31 topic
  12. Nonlinear Estimation31 topic
  13. Particle Filters31 topic
  14. SLAM31 topic
  15. Adversarial Examples21 topic
  16. Hyperparameter Optimization21 topic
  17. Noisy Labels21 topic
  18. Optimal Motion Planning21 topic
  19. Robustness21 topic
  20. Sampling-Based Algorithms21 topic

Where does Mohamed-Cherif Rahal work?

Mohamed-Cherif Rahal's main affiliation in the publication record is VeDeCoM Institute, France.

How many publications and citations does Mohamed-Cherif Rahal have?

OpenAlex counts 23 works and 223 citations for Mohamed-Cherif Rahal, an h-index of 6, ranking #4,004,698 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised citation excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.

Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.

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