Xabier Echeberria-Barrio
Xabier Echeberria-Barrio publishes mostly in Artificial Intelligence, Signal Processing and Computer Networks and Communications, on topics such as Adversarial Robustness in Machine Learning, Advanced Malware Detection Techniques and Anomaly Detection Techniques and Applications.
- World rank
- #6,262,325 of 7,710,434 ranked researchers
- Rank in Spain
- #152,591 of 204,306
- Works
- 16
- Citations
- 55
- Citations per work
- 3.4
What does Xabier Echeberria-Barrio research?
Xabier Echeberria-Barrio's work is mostly in Computer Science (77%), Biochemistry, Genetics and Molecular Biology (4%), Medicine (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 Sciences1277.3%
- Computer Science1277.3%
- Everything else315.9%
- Life Sciences14.5%
- Health Sciences02.3%
- Medicine02.3%
- 1Artificial Intelligence41% of their works
- 2Signal Processing18% of their works
- 3Computer Networks and Communications9% of their works
- 4Information Systems9% of their works
- 5Molecular Biology4% of their works
- 6Radiology, Nuclear Medicine and Imaging2% of their works
Research topics
- Adversarial Robustness in Machine Learning
- Advanced Malware Detection Techniques
- Anomaly Detection Techniques and Applications
- Network Security and Intrusion Detection
- Blockchain Technology Applications and Security
- Bacillus and Francisella bacterial research
- AI in cancer detection
- Explainable Artificial Intelligence (XAI)
Which keywords describe Xabier Echeberria-Barrio's research?
The keywords of their largest research topics: Deep Learning, Machine Learning, IoT Security, Neural Networks, Security, Adversarial Examples, Android Malware and Anomaly Detection.
- Tularemia
- Machine Learning Interpretability
- Histopathology Images
- Internet of Things
- Unsupervised
- Network Security
- Robustness
- Anomaly Detection
- Adversarial Examples
- Neural Networks
- Machine Learning
- Deep Learning
- IoT Security
- Security
- Android Malware
- Detection
- Intrusion Detection
- Outlier Detection
- Blockchain
- Anthrax
- Interpretable Models
- Medical Image Analysis
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 22 words, with their numbers
- Deep Learning265 topics
- Machine Learning224 topics
- IoT Security122 topics
- Neural Networks122 topics
- Security112 topics
- Adversarial Examples81 topic
- Android Malware81 topic
- Anomaly Detection82 topics
- Detection81 topic
- Robustness81 topic
- Intrusion Detection41 topic
- Network Security41 topic
- Outlier Detection41 topic
- Unsupervised41 topic
- Blockchain31 topic
- Internet of Things31 topic
- Anthrax21 topic
- Histopathology Images21 topic
- Interpretable Models21 topic
- Machine Learning Interpretability21 topic
- Medical Image Analysis21 topic
- Tularemia21 topic
Where does Xabier Echeberria-Barrio work?
Xabier Echeberria-Barrio's main affiliation in the publication record is Vicomtech, Spain.
How many publications and citations does Xabier Echeberria-Barrio have?
OpenAlex counts 16 works and 55 citations for Xabier Echeberria-Barrio, an h-index of 5, ranking #6,262,325 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 Xabier Echeberria-Barrio. 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.