Michael Katell

703 citations
24 papers · 355 indexed · h-index 8

Michael Katell

20 papers receiving 341 citations

Peers

Michael Katell
Comparison fields: 5 of 76
  • Health Informatics 42
  • Safety Research 218
  • Computer Science Applications 48
  • Human-Computer Interaction 42
  • Artificial Intelligence 116
Replace Milagros Miceli with:
Milagros Miceli Germany
Hao-Fei Cheng United States
Mark Díaz United States
Elettra Bietti United States
Salomé Viljoen United States
Reuben Binns United Kingdom
Janghee Cho United States
Nina Grgić-Hlača Germany
Lennart Hofeditz Germany
Ken Holstein United States
Michael Katell relative to Milagros Miceli Germany Milagros Miceli's profile →
Citations per field
00.5×5.3×
Milagros Miceli · 1×
Citations per year

Countries citing papers authored by Michael Katell

Since Specialization
Citations

This map shows the geographic impact of Michael Katell's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michael Katell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Katell more than expected).

Fields of papers citing papers by Michael Katell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Katell. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael Katell. The network helps show where Michael Katell may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Michael Katell, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Michael Katell Line = papers co-authored together Michael Katell links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 20249
3 20243
4 20240
5 20245
6 20222
7 20227
8 20220
9 20217
10 202130
11 202110
12 202150
13 202085
14 202058
15 20206
16 20195
17 201931
18 20195
19 20163
20 20150

About Michael Katell

Michael Katell is a scholar working on Safety Research, Computer Science Applications, Human-Computer Interaction, Law and History and Philosophy of Science, having authored 24 papers that have together received 355 indexed citations. Recurring topics across this work include Ethics and Social Impacts of AI (14 papers), Privacy, Security, and Data Protection (5 papers), Privacy-Preserving Technologies in Data (4 papers), COVID-19 Digital Contact Tracing (3 papers), Mobile Crowdsensing and Crowdsourcing (3 papers), Law, AI, and Intellectual Property (2 papers), Legal and Policy Issues (2 papers) and Data Quality and Management (2 papers). The work is most often cited by research in Health Informatics (42 citations), Safety Research (218 citations), Computer Science Applications (48 citations), Human-Computer Interaction (42 citations) and Artificial Intelligence (116 citations). Michael Katell has collaborated with scholars based in United Kingdom, United States and Ireland. Frequent co-authors include Meg Young, P. M. Krafft, Dharma Dailey, Karen Huang, David Leslie, Mhairi Aitken, Christopher Burr, Josh Cowls, Jennifer E. Lee and Jennifer Lee. Their work appears in journals such as interactions, Nature Reviews Genetics, Big Data & Society, Law Innovation and Technology and Proceedings of the Association for Information Science and Technology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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