Gabriel Goh
Gabriel Goh publishes mostly in Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing, on topics such as Adversarial Robustness in Machine Learning, Generative Adversarial Networks and Image Synthesis and Anomaly Detection Techniques and Applications.
- World rank
- #1,470,271 of 7,710,434 ranked researchers
- Rank in United States
- #461,922 of 1,627,098
- Works
- 23
- Citations
- 7.9k
- Citations per work
- 345.2
What does Gabriel Goh research?
Gabriel Goh's work is mostly in Computer Science (63%), Engineering (6%), Biochemistry, Genetics and Molecular Biology (2%).
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
- Physical Sciences1669.5%
- Computer Science1563.5%
- Engineering16.0%
- Everything else729.0%
- Life Sciences01.5%
- 1Artificial Intelligence35% of their works
- 2Computer Vision and Pattern Recognition24% of their works
- 3Signal Processing4% of their works
- 4Electrical and Electronic Engineering3% of their works
- 5Industrial and Manufacturing Engineering3% of their works
- 6Biophysics2% of their works
Research topics
- Adversarial Robustness in Machine Learning
- Generative Adversarial Networks and Image Synthesis
- Anomaly Detection Techniques and Applications
- Multimodal Machine Learning Applications
- Neural Networks and Applications
- Machine Learning and Data Classification
- Imbalanced Data Classification Techniques
- Data Stream Mining Techniques
Which keywords describe Gabriel Goh's research?
The keywords of their largest research topics: Deep Learning, Neural Networks, Adversarial Examples, Robustness, Classification, Generative Adversarial Networks, Image Synthesis and Anomaly Detection.
- SMOTE
- Imbalanced Data
- Data Streams
- Backpropagation Learning
- Unsupervised
- Anomaly Detection
- Generative Adversarial Networks
- Robustness
- Neural Networks
- Deep Learning
- Adversarial Examples
- Classification
- Image Synthesis
- Image Captioning
- Visual Question Answering
- Concept Drift
- Hyperparameter Optimization
- Noisy Labels
- Self-Organizing Maps
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
- Deep Learning175 topics
- Neural Networks175 topics
- Adversarial Examples51 topic
- Robustness51 topic
- Classification42 topics
- Generative Adversarial Networks41 topic
- Image Synthesis41 topic
- Anomaly Detection31 topic
- Image Captioning31 topic
- Unsupervised31 topic
- Visual Question Answering31 topic
- Backpropagation Learning21 topic
- Concept Drift21 topic
- Data Streams21 topic
- Hyperparameter Optimization21 topic
- Imbalanced Data21 topic
- Noisy Labels21 topic
- SMOTE21 topic
- Self-Organizing Maps21 topic
Where does Gabriel Goh work?
Gabriel Goh's main affiliation in the publication record is OpenAI (United States), United States.
How many publications and citations does Gabriel Goh have?
OpenAlex counts 23 works and 7,940 citations for Gabriel Goh, an h-index of 16, ranking #1,470,271 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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