Science Explorer Back to mapMap
Discussion
Researcher · Mila - Quebec Artificial Intelligence Institute · Canada

Md Rifat Arefin

Md Rifat Arefin publishes mostly in Artificial Intelligence, Computer Vision and Pattern Recognition and Geology, on topics such as Topic Modeling, Domain Adaptation and Few-Shot Learning and Multimodal Machine Learning Applications.

ORCID 0000-0002-6433-6764 OpenAlex
World rank
#4,112,075
of 7,710,434 ranked researchers
Rank in Canada
#127,045
of 183,316
Works
15
Citations
137
Citations per work
9.1
h-index
4
i10-index 3Top 90% in Artificial Intelligence
Md Rifat Arefin

What does Md Rifat Arefin research?

Md Rifat Arefin's work is mostly in Computer Science (78%), Earth and Planetary Sciences (3%), Engineering (3%).

Physical Sciences: 13 works · 84.3% of their workComputer Science: 12 works · 78.1% of their workArtificial Intelligence: 6 works · 40.6% of their workComputer Vision and Pattern Recognition: 5 works · 31.3% of their workComputer Networks and Communications: 0 works · 3.1% of their workSoftware: 0 works · 3.1% of their workEarth and Planetary Sciences: 0 works · 3.1% of their workGeology: 0 works · 3.1% of their workEngineering: 0 works · 3.1% of their workAutomotive Engineering: 0 works · 3.1% of their workEverything else: 2 works · 15.7% of their workTHEIR WORKMd Rifat Arefin15works
Physical Sciences84%

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 Science1278.1%
    2. Earth and Planetary Sciences03.1%
    3. Engineering03.1%
  2. Everything else215.7%
  1. 1Artificial Intelligence41% of their works
  2. 2Computer Vision and Pattern Recognition31% of their works
  3. 3Geology3% of their works
  4. 4Automotive Engineering3% of their works
  5. 5Software3% of their works
  6. 6Computer Networks and Communications3% of their works

Research topics

Which keywords describe Md Rifat Arefin's research?

The keywords of their largest research topics: Neural Networks, Deep Learning, Transfer Learning, Domain Adaptation, Few-Shot Learning, Machine Translation, Word Representation and Image Captioning.

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 19 words, with their numbers
  1. Neural Networks83 topics
  2. Deep Learning74 topics
  3. Transfer Learning52 topics
  4. Domain Adaptation41 topic
  5. Few-Shot Learning41 topic
  6. Machine Translation41 topic
  7. Word Representation41 topic
  8. Image Captioning31 topic
  9. Visual Question Answering31 topic
  10. Neural Machine Translation21 topic
  11. Object Tracking21 topic
  12. Statistical Machine Translation21 topic
  13. Visual Tracking21 topic
  14. Anomaly Detection11 topic
  15. Brain Tumor11 topic
  16. Brain-Computer Interfaces11 topic
  17. EEG Analysis11 topic
  18. MRI11 topic
  19. Unsupervised11 topic

Where does Md Rifat Arefin work?

Md Rifat Arefin's main affiliation in the publication record is Mila - Quebec Artificial Intelligence Institute, Canada.

How many publications and citations does Md Rifat Arefin have?

OpenAlex counts 15 works and 137 citations for Md Rifat Arefin, an h-index of 4, ranking #4,112,075 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.

Discussion

Ask a question or share a note about Md Rifat Arefin. Keep it to the research: no personal attacks, advertising or links. Any reader can report a post, which collapses it for everyone until it is opened.