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Researcher · Carnegie Mellon University · United States

Ravi Teja Mullapudi

Ravi Teja Mullapudi publishes mostly in Artificial Intelligence, Computer Vision and Pattern Recognition and Hardware and Architecture, on topics such as Domain Adaptation and Few-Shot Learning, Parallel Computing and Optimization Techniques and Advanced Neural Network Applications.

OpenAlex
World rank
#2,495,623
of 7,710,434 ranked researchers
Rank in United States
#736,062
of 1,627,098
Works
16
Citations
639
Citations per work
39.9
h-index
8
i10-index 8Top 56% in Artificial Intelligence
Ravi Teja Mullapudi

What does Ravi Teja Mullapudi research?

Ravi Teja Mullapudi's work is mostly in Computer Science (86%), Medicine (4%), Decision Sciences (4%).

Physical Sciences: 14 works · 85.5% of their workComputer Science: 14 works · 85.5% of their workArtificial Intelligence: 6 works · 37.5% of their workComputer Vision and Pattern Recognition: 4 works · 25.0% of their workHardware and Architecture: 3 works · 16.7% of their workComputer Networks and Communications: 1 works · 6.3% of their workEverything else: 1 works · 6.1% of their workHealth Sciences: 1 works · 4.2% of their workMedicine: 1 works · 4.2% of their workHealth Informatics: 1 works · 4.2% of their workSocial Sciences: 1 works · 4.2% of their workDecision Sciences: 1 works · 4.2% of their workInformation Systems and Management: 1 works · 4.2% of their workTHEIR WORKRavi TejaMullapudi16works
Physical Sciences86%Health Sciences4%Social Sciences4%

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 Science1485.5%
  2. Everything else16.1%
    1. Medicine14.2%
    1. Decision Sciences14.2%
  1. 1Artificial Intelligence38% of their works
  2. 2Computer Vision and Pattern Recognition25% of their works
  3. 3Hardware and Architecture17% of their works
  4. 4Computer Networks and Communications6% of their works
  5. 5Information Systems and Management4% of their works
  6. 6Health Informatics4% of their works

Research topics

Which keywords describe Ravi Teja Mullapudi's research?

The keywords of their largest research topics: Deep Learning, Meta-Learning, High-Performance Computing, Semi-Supervised Learning, Image Classification, Domain Adaptation, Parallel Computing and Performance Optimization.

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 22 words, with their numbers
  1. Deep Learning144 topics
  2. Meta-Learning92 topics
  3. High-Performance Computing82 topics
  4. Semi-Supervised Learning82 topics
  5. Image Classification72 topics
  6. Domain Adaptation61 topic
  7. Parallel Computing61 topic
  8. Performance Optimization61 topic
  9. Transfer Learning61 topic
  10. Convolutional Neural Networks51 topic
  11. Image Recognition51 topic
  12. Machine Learning52 topics
  13. Feature Matching41 topic
  14. Local Descriptors41 topic
  15. Adversarial Examples31 topic
  16. Hyperparameter Optimization31 topic
  17. Noisy Labels31 topic
  18. Robustness31 topic
  19. Active Learning21 topic
  20. Distributed Systems21 topic
  21. Gaussian Processes21 topic
  22. Grid Computing21 topic

Where does Ravi Teja Mullapudi work?

Ravi Teja Mullapudi's main affiliation in the publication record is Carnegie Mellon University, United States.

How many publications and citations does Ravi Teja Mullapudi have?

OpenAlex counts 16 works and 639 citations for Ravi Teja Mullapudi, an h-index of 8, ranking #2,495,623 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.

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