Science Explorer Back to mapMap
Discussion
Researcher · Stanford University · United States

David Fan

David Fan publishes mostly in Computer Vision and Pattern Recognition, Artificial Intelligence and Molecular Biology, on topics such as Human Pose and Action Recognition, Video Analysis and Summarization and Advanced Vision and Imaging.

ORCID 0000-0002-9217-5451 OpenAlex
World rank
#2,450,536
of 7,710,434 ranked researchers
Rank in United States
#724,721
of 1,627,098
Works
26
Citations
444
Citations per work
17.1
h-index
10
i10-index 11Top 45% in Computer Vision and Pattern Recognition
David Fan

What does David Fan research?

David Fan's work is mostly in Computer Science (48%), Neuroscience (12%), Biochemistry, Genetics and Molecular Biology (8%).

Physical Sciences: 12 works · 48.0% of their workComputer Science: 12 works · 48.0% of their workComputer Vision and Pattern Recognition: 10 works · 37.3% of their workArtificial Intelligence: 3 works · 10.7% of their workEverything else: 7 works · 25.3% of their workLife Sciences: 5 works · 20.0% of their workNeuroscience: 3 works · 12.0% of their workCellular and Molecular Neuroscience: 2 works · 6.7% of their workCognitive Neuroscience: 1 works · 5.3% of their workBiochemistry, Genetics and Molecular Biology: 2 works · 8.0% of their workMolecular Biology: 2 works · 8.0% of their workHealth Sciences: 2 works · 6.7% of their workMedicine: 2 works · 6.7% of their workObstetrics and Gynecology: 2 works · 6.7% of their workTHEIR WORKDavid Fan26works
Life Sciences20%Physical Sciences48%Health Sciences7%

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. Computer Science1248.0%
  2. Everything else725.3%
    1. Neuroscience312.0%
    2. Biochemistry, Genetics and Molecular Biology28.0%
    1. Medicine26.7%
  1. 1Computer Vision and Pattern Recognition37% of their works
  2. 2Artificial Intelligence11% of their works
  3. 3Molecular Biology8% of their works
  4. 4Obstetrics and Gynecology7% of their works
  5. 5Cellular and Molecular Neuroscience7% of their works
  6. 6Cognitive Neuroscience5% of their works

Research topics

Which keywords describe David Fan's research?

The keywords of their largest research topics: Convolutional Networks, Deep Learning, Action Recognition, Pose Estimation, Content-Based Retrieval, Video Summarization, Prefrontal Cortex and Depth Estimation.

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.

All 19 words, with their numbers
  1. Convolutional Networks112 topics
  2. Deep Learning102 topics
  3. Action Recognition71 topic
  4. Pose Estimation71 topic
  5. Content-Based Retrieval61 topic
  6. Video Summarization61 topic
  7. Prefrontal Cortex52 topics
  8. Depth Estimation41 topic
  9. Stereo Vision41 topic
  10. Dopamine31 topic
  11. Image Captioning31 topic
  12. Placental Development31 topic
  13. Preeclampsia31 topic
  14. Serotonin31 topic
  15. Visual Question Answering31 topic
  16. Hippocampus21 topic
  17. Memory21 topic
  18. Neurotransmission21 topic
  19. Synaptic Plasticity21 topic

Where does David Fan work?

David Fan's main affiliation in the publication record is Stanford University, United States.

How many publications and citations does David Fan have?

OpenAlex counts 26 works and 444 citations for David Fan, an h-index of 10, ranking #2,450,536 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised 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.

Discussion

Ask a question or share a note about David Fan. Posts are plain text and can be reported.