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Researcher · Amazon (United States) · United States

Parmida Atighehchian

Parmida Atighehchian publishes mostly in Computer Vision and Pattern Recognition, Artificial Intelligence and Marketing, on topics such as Machine Learning and Data Classification, Generative Adversarial Networks and Image Synthesis and Explainable Artificial Intelligence (XAI).

OpenAlex
World rank
#3,085,360
of 7,710,434 ranked researchers
Rank in United States
#881,744
of 1,627,098
Works
19
Citations
497
Citations per work
26.2
h-index
5
i10-index 5Top 87% in Computer Vision and Pattern Recognition
Parmida Atighehchian

What does Parmida Atighehchian research?

Parmida Atighehchian's work is mostly in Computer Science (76%), Medicine (4%), Business, Management and Accounting (4%).

Physical Sciences: 15 works · 76.5% of their workComputer Science: 15 works · 76.5% of their workComputer Vision and Pattern Recognition: 7 works · 39.2% of their workArtificial Intelligence: 7 works · 35.3% of their workComputer Graphics and Computer-Aided Design: 0 works · 2.0% of their workEverything else: 2 works · 11.8% of their workSocial Sciences: 1 works · 7.8% of their workBusiness, Management and Accounting: 1 works · 3.9% of their workMarketing: 1 works · 3.9% of their workSocial Sciences: 1 works · 3.9% of their workGender Studies: 1 works · 3.9% of their workHealth Sciences: 1 works · 3.9% of their workMedicine: 1 works · 3.9% of their workRadiology, Nuclear Medicine and Imaging: 1 works · 3.9% of their workTHEIR WORKParmidaAtighehchian19works
Physical Sciences76%Health Sciences4%Social Sciences8%

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 Science1576.5%
  2. Everything else211.8%
    1. Business, Management and Accounting13.9%
    2. Social Sciences13.9%
    1. Medicine13.9%
  1. 1Computer Vision and Pattern Recognition39% of their works
  2. 2Artificial Intelligence35% of their works
  3. 3Marketing4% of their works
  4. 4Gender Studies4% of their works
  5. 5Radiology, Nuclear Medicine and Imaging4% of their works
  6. 6Computer Graphics and Computer-Aided Design2% of their works

Research topics

Which keywords describe Parmida Atighehchian's research?

The keywords of their largest research topics: Deep Learning, Neural Networks, Deep Neural Networks, Hyperparameter Optimization, Machine Learning, Noisy Labels, Generative Adversarial Networks and Image Synthesis.

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 Learning145 topics
  2. Neural Networks114 topics
  3. Deep Neural Networks82 topics
  4. Hyperparameter Optimization51 topic
  5. Machine Learning52 topics
  6. Noisy Labels51 topic
  7. Generative Adversarial Networks41 topic
  8. Image Synthesis41 topic
  9. Active Learning31 topic
  10. Content-Based Retrieval31 topic
  11. Image Captioning31 topic
  12. Interpretable Models31 topic
  13. Machine Learning Interpretability31 topic
  14. Semi-Supervised Learning31 topic
  15. Video Summarization31 topic
  16. Visual Question Answering31 topic
  17. Adversarial Examples21 topic
  18. Anomaly Detection21 topic
  19. Robustness21 topic
  20. Unsupervised21 topic

Where does Parmida Atighehchian work?

Parmida Atighehchian's main affiliation in the publication record is Amazon (United States), United States.

How many publications and citations does Parmida Atighehchian have?

OpenAlex counts 19 works and 497 citations for Parmida Atighehchian, an h-index of 5, ranking #3,085,360 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

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