Science Explorer Back to mapMap
Discussion
Researcher · Universität Ulm · Germany

Christoph Bösch

Christoph Bösch publishes mostly in Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems, on topics such as Cryptography and Data Security, Privacy-Preserving Technologies in Data and Privacy, Security, and Data Protection.

ORCID 0000-0001-9312-8000 OpenAlex
World rank
#925,954
of 7,710,434 ranked researchers
Rank in Germany
#45,595
of 364,343
Works
44
Citations
1.4k
Citations per work
31.3
h-index
13
i10-index 14Top 28% in Artificial Intelligence
Christoph Bösch

What does Christoph Bösch research?

Christoph Bösch's work is mostly in Computer Science (65%), Social Sciences (10%).

Physical Sciences: 29 works · 64.9% of their workComputer Science: 29 works · 64.9% of their workArtificial Intelligence: 14 works · 31.3% of their workComputer Vision and Pattern Recognition: 6 works · 12.5% of their workInformation Systems: 4 works · 10.2% of their workComputer Networks and Communications: 3 works · 7.0% of their workSignal Processing: 2 works · 3.9% of their workEverything else: 11 works · 24.9% of their workSocial Sciences: 4 works · 10.2% of their workSocial Sciences: 4 works · 10.2% of their workSociology and Political Science: 4 works · 10.2% of their workTHEIR WORKChristoph Bösch44works
Physical Sciences65%Social Sciences10%

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 Science2964.9%
  2. Everything else1124.9%
    1. Social Sciences410.2%
  1. 1Artificial Intelligence31% of their works
  2. 2Computer Vision and Pattern Recognition12% of their works
  3. 3Information Systems10% of their works
  4. 4Sociology and Political Science10% of their works
  5. 5Computer Networks and Communications7% of their works
  6. 6Signal Processing4% of their works

Research topics

Which keywords describe Christoph Bösch's research?

The keywords of their largest research topics: Machine Learning, Deep Learning, Homomorphic Encryption, Identity-Based Encryption, Differential Privacy, Federated Learning, Online Social Networks and Privacy Concerns.

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 18 words, with their numbers
  1. Machine Learning254 topics
  2. Deep Learning194 topics
  3. Homomorphic Encryption151 topic
  4. Identity-Based Encryption151 topic
  5. Differential Privacy131 topic
  6. Federated Learning131 topic
  7. Online Social Networks101 topic
  8. Privacy Concerns101 topic
  9. Blockchain81 topic
  10. Internet of Things81 topic
  11. Reversible Data Embedding71 topic
  12. Steganography71 topic
  13. Android Malware41 topic
  14. Classification41 topic
  15. Detection41 topic
  16. Histopathology Images41 topic
  17. Internet Traffic41 topic
  18. Medical Image Analysis41 topic

Where does Christoph Bösch work?

Christoph Bösch's main affiliation in the publication record is Universität Ulm, Germany.

How many publications and citations does Christoph Bösch have?

OpenAlex counts 44 works and 1,378 citations for Christoph Bösch, an h-index of 13, ranking #925,954 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.

Other researchers named Christoph Bösch

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 Christoph Bösch. 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.